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ggml-cpu: enable IBM NNPA Vector Intrinsics (#14317)

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* ggml-cpu: add nnpa compile flag

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
(cherry picked from commit 4a9f60c201)

* ggml-cpu: add fp16->fp32 nnpa first

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
(cherry picked from commit 8d4a7987f9)

* ggml-cpu: add fp32->fp16

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
(cherry picked from commit 0ff0d65162)

* ggml-cpu: better variable names

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
(cherry picked from commit 2f58bbcbb8)

* docs: update s390x docs

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
(cherry picked from commit 01b929491b)

* ggml-cpu: add debugging prints to see if dlf16 is correct

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: fix print vs printf

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: fix float placeholder

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: ensure fp16 and fp32 load and stores are called

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: fp16 load ensured to hit

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: remove sigint from fp16 store

for some reason, the function is not getting a hit when debugged with
    gdb. we will need to investigate further

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: activate nnpa for ggml_cpu_fp16_to_fp32

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: nnpa activate ggml_cpu_fp16_to_fp32 for 8 elements

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: nnpa switch to vec_xst test

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: switch to vec_xst for 4 element loops also

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: rework noop

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: remove noop, general code cleanup

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: clarify variable naming

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: activate nnpa for ggml_cpu_fp32_to_fp16

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: add breakpoint for debugging

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: test fix for conversion failure

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: disable fp32->fp16 nnpa conversions for now

there are some conversion failures in nnpa that requires the eyes of an
ibm stsm. will create a separate pr to introduce the fp32->fp16 change.

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: switch to elif macro

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: reattempt fp32->fp16

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: fix typo

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: reattempt fp32->fp16

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: fix compiler types

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: change to typedef vector types

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: add 4 element loops for fp32->fp16

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: clarified vector naming

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: bring back fp32->fp16 store nnpa

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: activate nnpa fp32->fp16 or fp16->fp32 compute

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: add nnpa macro check in ggml-impl

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: add missing __func__

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: diagnose why __NNPA__ macro is not being defined

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: import vecintrin.h to fix compiler errors

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: update macro tests

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: move s390x typedef to own header file

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* Revert "ggml-cpu: move s390x typedef to own header file"

This reverts commit 157f856c34.

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: switch to importing ggml-cpu-impl instead

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: fix macro declaration

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: test more macros

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: add debug prints

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: bruteforce macro definitions

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: move macro definitions

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: add ggml-impl.h to cmakelists

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: switch to private macros

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: move s390x typedef to own header file

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
(cherry picked from commit 157f856c34)

* ggml-cpu: move things around

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: bring back compile macros

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: switch to quotes for import

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: add compiler error macro

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: add s390x detection in ggml-src

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: bring back compile definitions

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: undo cmakelists work

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* Revert "ggml-cpu: move s390x typedef to own header file"

This reverts commit 18d79e1a30.

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: remove typedefs.h

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: remove typedef from cmakelists

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: add ggml-impl.h future notes

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: add todo comment for future reference

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: clarify naming of dlf16

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: remove unnecessary target compile definitions

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: move nnpa fp16->fp32 and fp32->fp16 to simd-mappings

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml: refactor fp32->fp16 and fp16->fp32 simd to ggml-cpu

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* docs: update broken huggingface link for s390x

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: fix duplicate func names during compile

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* Revert "ggml-cpu: fix duplicate func names during compile"

This reverts commit fbb733451f.

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* Revert "ggml: refactor fp32->fp16 and fp16->fp32 simd to ggml-cpu"

This reverts commit bd288e8fa5.

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml: refactor fp16<->fp32 simd to ggml-cpu

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: fix missing simd-mappings.h import in quants.c

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: fix missing simd-mappings.h within repack

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: fix amx mmq missing simd-mappings.h

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: attempt at fixing loongarch failing build

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: move nnpa together with other fp16<->fp32 simd

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: fix wrong refactor of ggml-base

ref: https://github.com/ggml-org/llama.cpp/pull/14317#discussion_r2164176555

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml: remove dependency on ggml-cpu from ggml-base

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: rename all fp16<->fp32 macros to prefix with ggml_cpu

ref: https://github.com/ggml-org/llama.cpp/pull/14317#discussion_r2164449406

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: remove mistaken fallback macro

fallback logic was already implemented but i was too sleepy to realise

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml: move ggml_table_f32_f16 to ggml-cpu

ref: https://github.com/ggml-org/llama.cpp/pull/14317#discussion_r2164775006

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: move ggml_table_f32_f16 back to ggml-base due to ci failures

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* Revert "ggml-cpu: move ggml_table_f32_f16 back to ggml-base due to ci failures"

This reverts commit 32a3533564.

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* Revert "ggml: move ggml_table_f32_f16 to ggml-cpu"

This reverts commit 9e40d984ad.

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml: move ggml_table_f32_f16 to ggml-cpu

ref: https://github.com/ggml-org/llama.cpp/pull/14317#discussion_r2164775006

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
(cherry picked from commit 9e40d984ad)

* ggml: move ggml_table_f32_f16 to ggml-cpu.c

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: extern c ggml_table_f32_f16 + chore docs

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: dedup ggml_table_f32_f16 from simd-mappings.h

we rely on the variable declaration in ggml-cpu.c instead

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* Revert "ggml-cpu: dedup ggml_table_f32_f16 from simd-mappings.h"

This reverts commit f71b21d2f7.

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: bring back ggml_table_f32_f16

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* Revert "ggml-cpu: bring back ggml_table_f32_f16"

This reverts commit 2dce119178.

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* fix ggml time initialization

* fix f32_f16 table init

* remove extra line

---------

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
Co-authored-by: slaren <slarengh@gmail.com>
This commit is contained in:
Aaron Teo
2025-06-26 05:49:04 +08:00
committed by GitHub
parent b193d53069
commit 60ef23d6c1
29 changed files with 1005 additions and 862 deletions
Download Patch File Download Diff File Expand all files Collapse all files

41
docs/build-s390x.md
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@ -28,8 +28,9 @@ cmake --build build --config Release -j $(nproc)
```
**Notes**:
- For faster repeated compilation, install [ccache](https://ccache.dev/)
- By default, VXE/VXE2 is enabled. To disable it (not recommended):
- For faster repeated compilation, install [ccache](https://ccache.dev/)
- By default, VXE/VXE2 is enabled. To disable it (not recommended):
```bash
cmake -S . -B build \
@ -41,18 +42,29 @@ cmake --build build --config Release -j $(nproc)
cmake --build build --config Release -j $(nproc)
```
- For debug builds:
- By default, NNPA is enabled when available. To disable it (not recommended):
```bash
cmake -S . -B build \
-DCMAKE_BUILD_TYPE=Release \
-DGGML_BLAS=ON \
-DGGML_BLAS_VENDOR=OpenBLAS \
-DGGML_NNPA=OFF
cmake --build build --config Release -j $(nproc)
```
- For debug builds:
```bash
cmake -S . -B build \
-DCMAKE_BUILD_TYPE=Debug \
-DGGML_BLAS=ON \
-DGGML_BLAS_VENDOR=OpenBLAS
cmake --build build --config Debug -j $(nproc)
```
- For static builds, add `-DBUILD_SHARED_LIBS=OFF`:
- For static builds, add `-DBUILD_SHARED_LIBS=OFF`:
```bash
cmake -S . -B build \
@ -70,7 +82,7 @@ All models need to be converted to Big-Endian. You can achieve this in three cas
1. **Use pre-converted models verified for use on IBM Z & LinuxONE (easiest)**
You can find popular models pre-converted and verified at [s390x Ready Models](hf.co/collections/taronaeo/s390x-ready-models-672765393af438d0ccb72a08).
You can find popular models pre-converted and verified at [s390x Ready Models](https://huggingface.co/collections/taronaeo/s390x-ready-models-672765393af438d0ccb72a08).
These models and their respective tokenizers are verified to run correctly on IBM Z & LinuxONE.
@ -101,27 +113,33 @@ All models need to be converted to Big-Endian. You can achieve this in three cas
```
For example,
```bash
python3 gguf-py/gguf/scripts/gguf_convert_endian.py granite-3.3-2b-instruct-le.f16.gguf BIG
mv granite-3.3-2b-instruct-le.f16.gguf granite-3.3-2b-instruct-be.f16.gguf
```
**Notes:**
- The GGUF endian conversion script may not support all data types at the moment and may fail for some models/quantizations. When that happens, please try manually converting the safetensors model to GGUF Big-Endian via Step 2.
## IBM Accelerators
### 1. SIMD Acceleration
Only available in IBM z15 or later system with the `-DGGML_VXE=ON` (turned on by default) compile flag. No hardware acceleration is possible with llama.cpp with older systems, such as IBM z14 or EC13. In such systems, the APIs can still run but will use a scalar implementation.
Only available in IBM z15 or later system with the `-DGGML_VXE=ON` (turned on by default) compile flag. No hardware acceleration is possible with llama.cpp with older systems, such as IBM z14/arch12. In such systems, the APIs can still run but will use a scalar implementation.
### 2. zDNN Accelerator
### 2. NNPA Vector Intrinsics Acceleration
*Only available in IBM z16 or later system. No direction at the moment.*
Only available in IBM z16 or later system with the `-DGGML_NNPA=ON` (turned on when available) compile flag. No hardware acceleration is possible with llama.cpp with older systems, such as IBM z15/arch13. In such systems, the APIs can still run but will use a scalar implementation.
### 3. Spyre Accelerator
### 3. zDNN Accelerator
*No direction at the moment.*
_Only available in IBM z16 or later system. No direction at the moment._
### 4. Spyre Accelerator
_No direction at the moment._
## Performance Tuning
@ -154,4 +172,3 @@ IBM VXE/VXE2 SIMD acceleration depends on the BLAS implementation. It is strongl
2. **Other Questions**
Please reach out directly to [aionz@us.ibm.com](mailto:aionz@us.ibm.com).

4
docs/build.md
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@ -557,6 +557,10 @@ ninja
To read documentation for how to build on Android, [click here](./android.md)
## IBM Z & LinuxONE
To read documentation for how to build on IBM Z & LinuxONE, [click here](./build-s390x.md)
## Notes about GPU-accelerated backends
The GPU may still be used to accelerate some parts of the computation even when using the `-ngl 0` option. You can fully disable GPU acceleration by using `--device none`.

1
ggml/CMakeLists.txt
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@ -131,6 +131,7 @@ option(GGML_RVV "ggml: enable rvv" ON)
option(GGML_RV_ZFH "ggml: enable riscv zfh" OFF)
option(GGML_XTHEADVECTOR "ggml: enable xtheadvector" OFF)
option(GGML_VXE "ggml: enable vxe" ON)
option(GGML_NNPA "ggml: enable nnpa" ON)
option(GGML_CPU_ALL_VARIANTS "ggml: build all variants of the CPU backend (requires GGML_BACKEND_DL)" OFF)
set(GGML_CPU_ARM_ARCH "" CACHE STRING "ggml: CPU architecture for ARM")

1
ggml/include/ggml-cpu.h
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@ -101,6 +101,7 @@ extern "C" {
GGML_BACKEND_API int ggml_cpu_has_riscv_v (void);
GGML_BACKEND_API int ggml_cpu_has_vsx (void);
GGML_BACKEND_API int ggml_cpu_has_vxe (void);
GGML_BACKEND_API int ggml_cpu_has_nnpa (void);
GGML_BACKEND_API int ggml_cpu_has_wasm_simd (void);
GGML_BACKEND_API int ggml_cpu_has_llamafile (void);

8
ggml/src/ggml-cpu/CMakeLists.txt
View File

@ -448,6 +448,7 @@ function(ggml_add_cpu_backend_variant_impl tag_name)
# TODO: Separation to determine activation of VX/VXE/VXE2
if (${S390X_M} MATCHES "8561|8562")
set(GGML_NNPA OFF)
message(STATUS "z15 target")
list(APPEND ARCH_FLAGS -march=z15)
elseif (${S390X_M} MATCHES "3931")
@ -464,7 +465,14 @@ function(ggml_add_cpu_backend_variant_impl tag_name)
endif()
if (GGML_VXE)
message(STATUS "VX/VXE/VXE2 enabled")
list(APPEND ARCH_FLAGS -mvx -mzvector)
list(APPEND ARCH_DEFINITIONS GGML_VXE)
endif()
if (GGML_NNPA)
message(STATUS "NNPA enabled")
list(APPEND ARCH_DEFINITIONS GGML_NNPA)
endif()
elseif (CMAKE_SYSTEM_PROCESSOR MATCHES "wasm")
message(STATUS "Wasm detected")

19
ggml/src/ggml-cpu/amx/mmq.cpp
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@ -8,6 +8,7 @@
#include "mmq.h"
#include "ggml-impl.h"
#include "ggml-cpu-impl.h"
#include "simd-mappings.h"
#include "quants.h"
#include "ggml-quants.h"
#include <algorithm>
@ -453,7 +454,7 @@ void quantize_row_q8_K_vnni(const float * RESTRICT x, void * RESTRICT vy, int64_
// Quantize these floats
const float iscale = 127.f / amax;
y[i].d = GGML_FP32_TO_FP16(1 / iscale);
y[i].d = GGML_CPU_FP32_TO_FP16(1 / iscale);
const float id = ( amax != 0.0f ) ? iscale : 0.f;
const __m512 vscale = _mm512_set1_ps(id);
@ -1090,7 +1091,7 @@ struct acc_C<block_q8_0, block_q4_0, is_acc> {
const __m512 vd0 = _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)((const char *)packed_B + offset)));
for (int m = 0; m < nr; ++m) {
const __m512 vd1 = _mm512_set1_ps(GGML_FP16_TO_FP32(A[m * lda].d));
const __m512 vd1 = _mm512_set1_ps(GGML_CPU_FP16_TO_FP32(A[m * lda].d));
const __m512 vtile = _mm512_cvtepi32_ps(_mm512_loadu_si512(tile + m * TILE_N));
__m512 vsum;
@ -1113,8 +1114,8 @@ struct acc_C<block_q8_1, block_q4_1, is_acc> {
const __m512 vm0 = _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)((const char *)packed_B + offset + TILE_N * sizeof(ggml_half))));
for (int m = 0; m < nr; ++m) {
const __m512 vd1 = _mm512_set1_ps(GGML_FP16_TO_FP32(A[m * lda].d));
const __m512 vs1 = _mm512_set1_ps(GGML_FP16_TO_FP32(A[m * lda].s));
const __m512 vd1 = _mm512_set1_ps(GGML_CPU_FP16_TO_FP32(A[m * lda].d));
const __m512 vs1 = _mm512_set1_ps(GGML_CPU_FP16_TO_FP32(A[m * lda].s));
const __m512 vtile = _mm512_cvtepi32_ps(_mm512_loadu_si512(tile + m * TILE_N));
__m512 vsum;
@ -1137,7 +1138,7 @@ struct acc_C<block_q8_0, block_q8_0, is_acc> {
const __m512 vd0 = _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)((const char *)packed_B + offset)));
for (int m = 0; m < nr; ++m) {
const __m512 vd1 = _mm512_set1_ps(GGML_FP16_TO_FP32(A[m * lda].d));
const __m512 vd1 = _mm512_set1_ps(GGML_CPU_FP16_TO_FP32(A[m * lda].d));
const __m512 vtile = _mm512_cvtepi32_ps(_mm512_loadu_si512(tile + m * TILE_N));
__m512 vsum;
@ -1437,7 +1438,7 @@ struct tinygemm_kernel_vnni<block_q8_0, block_q4_0, float, BLOCK_M, BLOCK_N, BLO
va[k] = _mm512_set1_epi32(a_ptr[k]);
vcomp = _mm512_dpbusd_epi32(vcomp, off, va[k]);
}
vd1 = _mm512_set1_ps(GGML_FP16_TO_FP32(A[0 * KB + i].d));
vd1 = _mm512_set1_ps(GGML_CPU_FP16_TO_FP32(A[0 * KB + i].d));
}
// load b
@ -1498,8 +1499,8 @@ struct tinygemm_kernel_vnni<block_q8_1, block_q4_1, float, 1, BLOCK_N, BLOCK_K>
for (int k = 0; k < 8; ++k) {
va[k] = _mm512_set1_epi32(a_ptr[k]);
}
vd1 = _mm512_set1_ps(GGML_FP16_TO_FP32(A[0 * KB + i].d));
vs1 = _mm512_set1_ps(GGML_FP16_TO_FP32(A[0 * KB + i].s));
vd1 = _mm512_set1_ps(GGML_CPU_FP16_TO_FP32(A[0 * KB + i].d));
vs1 = _mm512_set1_ps(GGML_CPU_FP16_TO_FP32(A[0 * KB + i].s));
}
// load b
@ -1571,7 +1572,7 @@ struct tinygemm_kernel_vnni<block_q8_0, block_q8_0, float, BLOCK_M, BLOCK_N, BLO
va[k] = _mm512_set1_epi32(a_ptr[k]);
va[k] = _mm512_add_epi8(va[k], off);
}
vd1 = _mm512_set1_ps(GGML_FP16_TO_FP32(A[0 * KB + i].d));
vd1 = _mm512_set1_ps(GGML_CPU_FP16_TO_FP32(A[0 * KB + i].d));
}
// load b

217
ggml/src/ggml-cpu/arch/arm/quants.c
View File

@ -3,6 +3,7 @@
#include "ggml-quants.h"
#include "ggml-impl.h"
#include "ggml-cpu.h"
#include "simd-mappings.h"
#include "../../quants.h"
#include "../../ggml-cpu-impl.h"
@ -62,7 +63,7 @@ void quantize_row_q8_0(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, i
const float d = amax / ((1 << 7) - 1);
const float id = d ? 1.0f/d : 0.0f;
y[i].d = GGML_FP32_TO_FP16(d);
y[i].d = GGML_CPU_FP32_TO_FP16(d);
for (int j = 0; j < 8; j++) {
const float32x4_t v = vmulq_n_f32(srcv[j], id);
@ -104,7 +105,7 @@ void quantize_row_q8_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, i
const float d = amax / ((1 << 7) - 1);
const float id = d ? 1.0f/d : 0.0f;
y[i].d = GGML_FP32_TO_FP16(d);
y[i].d = GGML_CPU_FP32_TO_FP16(d);
int32x4_t accv = vdupq_n_s32(0);
@ -120,7 +121,7 @@ void quantize_row_q8_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, i
accv = vaddq_s32(accv, vi);
}
y[i].s = GGML_FP32_TO_FP16(d * vaddvq_s32(accv));
y[i].s = GGML_CPU_FP32_TO_FP16(d * vaddvq_s32(accv));
}
#else
GGML_UNUSED(nb);
@ -194,10 +195,10 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
const int8x16_t y1_h = vld1q_s8(b_y1->qs + 16);
float32_t _scale[4] = {
GGML_FP16_TO_FP32(b_x0->d)*GGML_FP16_TO_FP32(b_y0->d),
GGML_FP16_TO_FP32(b_x0->d)*GGML_FP16_TO_FP32(b_y1->d),
GGML_FP16_TO_FP32(b_x1->d)*GGML_FP16_TO_FP32(b_y0->d),
GGML_FP16_TO_FP32(b_x1->d)*GGML_FP16_TO_FP32(b_y1->d)
GGML_CPU_FP16_TO_FP32(b_x0->d)*GGML_CPU_FP16_TO_FP32(b_y0->d),
GGML_CPU_FP16_TO_FP32(b_x0->d)*GGML_CPU_FP16_TO_FP32(b_y1->d),
GGML_CPU_FP16_TO_FP32(b_x1->d)*GGML_CPU_FP16_TO_FP32(b_y0->d),
GGML_CPU_FP16_TO_FP32(b_x1->d)*GGML_CPU_FP16_TO_FP32(b_y1->d)
};
float32x4_t scale = vld1q_f32(_scale);
@ -274,10 +275,10 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
// dot product
sumv0 = svmla_n_f32_x(ph4, sumv0, svcvt_f32_s32_x(ph4, svadd_x(ph4,
svdot_s32(svdup_n_s32(0), qx0ls, qy0l),
svdot_s32(svdup_n_s32(0), qx0hs, qy0h))), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
svdot_s32(svdup_n_s32(0), qx0hs, qy0h))), GGML_CPU_FP16_TO_FP32(x0->d)*GGML_CPU_FP16_TO_FP32(y0->d));
sumv1 = svmla_n_f32_x(ph4, sumv1, svcvt_f32_s32_x(ph4, svadd_x(ph4,
svdot_s32(svdup_n_s32(0), qx1ls, qy1l),
svdot_s32(svdup_n_s32(0), qx1hs, qy1h))), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
svdot_s32(svdup_n_s32(0), qx1hs, qy1h))), GGML_CPU_FP16_TO_FP32(x1->d)*GGML_CPU_FP16_TO_FP32(y1->d));
}
sumf = svaddv_f32(svptrue_b32(), svadd_f32_x(svptrue_b32(), sumv0, sumv1));
@ -313,9 +314,9 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
// dot product
sumv0 = svmla_n_f32_x(svptrue_b32(), sumv0, svcvt_f32_s32_x(svptrue_b32(),
svdot_s32(svdup_n_s32(0), qx0s, qy0)), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
svdot_s32(svdup_n_s32(0), qx0s, qy0)), GGML_CPU_FP16_TO_FP32(x0->d)*GGML_CPU_FP16_TO_FP32(y0->d));
sumv1 = svmla_n_f32_x(svptrue_b32(), sumv1, svcvt_f32_s32_x(svptrue_b32(),
svdot_s32(svdup_n_s32(0), qx1s, qy1)), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
svdot_s32(svdup_n_s32(0), qx1s, qy1)), GGML_CPU_FP16_TO_FP32(x1->d)*GGML_CPU_FP16_TO_FP32(y1->d));
}
sumf = svaddv_f32(svptrue_b32(), svadd_f32_x(svptrue_b32(), sumv0, sumv1));
@ -354,9 +355,9 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
// dot product
sumv0 = svmla_n_f32_x(ph32, sumv0, svcvt_f32_s32_x(ph32,
svdot_s32(svdup_n_s32(0), qx0s, qy0)), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
svdot_s32(svdup_n_s32(0), qx0s, qy0)), GGML_CPU_FP16_TO_FP32(x0->d)*GGML_CPU_FP16_TO_FP32(y0->d));
sumv1 = svmla_n_f32_x(ph32, sumv1, svcvt_f32_s32_x(ph32,
svdot_s32(svdup_n_s32(0), qx1s, qy1)), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
svdot_s32(svdup_n_s32(0), qx1s, qy1)), GGML_CPU_FP16_TO_FP32(x1->d)*GGML_CPU_FP16_TO_FP32(y1->d));
}
sumf = svaddv_f32(ph32, svadd_f32_x(ph32, sumv0, sumv1));
@ -404,8 +405,8 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
const int32x4_t p_0 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), v0_0ls, v1_0l), v0_0hs, v1_0h);
const int32x4_t p_1 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), v0_1ls, v1_1l), v0_1hs, v1_1h);
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(p_0), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(p_1), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(p_0), GGML_CPU_FP16_TO_FP32(x0->d)*GGML_CPU_FP16_TO_FP32(y0->d));
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(p_1), GGML_CPU_FP16_TO_FP32(x1->d)*GGML_CPU_FP16_TO_FP32(y1->d));
}
sumf = vaddvq_f32(sumv0) + vaddvq_f32(sumv1);
@ -423,7 +424,7 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
}
int sumi = sumi0 + sumi1;
sumf += sumi*GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d);
sumf += sumi*GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d);
}
*s = sumf;
@ -464,10 +465,10 @@ void ggml_vec_dot_q4_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
const block_q8_1 * GGML_RESTRICT b_y1 = &vy1[i];
float32_t summs_t[4] = {
GGML_FP16_TO_FP32(b_x0->m) * GGML_FP16_TO_FP32(b_y0->s),
GGML_FP16_TO_FP32(b_x1->m) * GGML_FP16_TO_FP32(b_y0->s),
GGML_FP16_TO_FP32(b_x0->m) * GGML_FP16_TO_FP32(b_y1->s),
GGML_FP16_TO_FP32(b_x1->m) * GGML_FP16_TO_FP32(b_y1->s)
GGML_CPU_FP16_TO_FP32(b_x0->m) * GGML_CPU_FP16_TO_FP32(b_y0->s),
GGML_CPU_FP16_TO_FP32(b_x1->m) * GGML_CPU_FP16_TO_FP32(b_y0->s),
GGML_CPU_FP16_TO_FP32(b_x0->m) * GGML_CPU_FP16_TO_FP32(b_y1->s),
GGML_CPU_FP16_TO_FP32(b_x1->m) * GGML_CPU_FP16_TO_FP32(b_y1->s)
};
summs0 = vaddq_f32(summs0, vld1q_f32(summs_t));
@ -490,10 +491,10 @@ void ggml_vec_dot_q4_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
// mmla into int32x4_t
float32_t _scale[4] = {
GGML_FP16_TO_FP32(b_x0->d)*GGML_FP16_TO_FP32(b_y0->d),
GGML_FP16_TO_FP32(b_x0->d)*GGML_FP16_TO_FP32(b_y1->d),
GGML_FP16_TO_FP32(b_x1->d)*GGML_FP16_TO_FP32(b_y0->d),
GGML_FP16_TO_FP32(b_x1->d)*GGML_FP16_TO_FP32(b_y1->d)
GGML_CPU_FP16_TO_FP32(b_x0->d)*GGML_CPU_FP16_TO_FP32(b_y0->d),
GGML_CPU_FP16_TO_FP32(b_x0->d)*GGML_CPU_FP16_TO_FP32(b_y1->d),
GGML_CPU_FP16_TO_FP32(b_x1->d)*GGML_CPU_FP16_TO_FP32(b_y0->d),
GGML_CPU_FP16_TO_FP32(b_x1->d)*GGML_CPU_FP16_TO_FP32(b_y1->d)
};
float32x4_t scale = vld1q_f32(_scale);
@ -539,7 +540,7 @@ void ggml_vec_dot_q4_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
const block_q8_1 * GGML_RESTRICT y0 = &y[ib + 0];
const block_q8_1 * GGML_RESTRICT y1 = &y[ib + 1];
summs += GGML_FP16_TO_FP32(x0->m) * GGML_FP16_TO_FP32(y0->s) + GGML_FP16_TO_FP32(x1->m) * GGML_FP16_TO_FP32(y1->s);
summs += GGML_CPU_FP16_TO_FP32(x0->m) * GGML_CPU_FP16_TO_FP32(y0->s) + GGML_CPU_FP16_TO_FP32(x1->m) * GGML_CPU_FP16_TO_FP32(y1->s);
const uint8x16_t m4b = vdupq_n_u8(0x0F);
@ -562,8 +563,8 @@ void ggml_vec_dot_q4_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
const int32x4_t p_0 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), v0_0l, v1_0l), v0_0h, v1_0h);
const int32x4_t p_1 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), v0_1l, v1_1l), v0_1h, v1_1h);
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(p_0), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(p_1), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(p_0), GGML_CPU_FP16_TO_FP32(x0->d)*GGML_CPU_FP16_TO_FP32(y0->d));
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(p_1), GGML_CPU_FP16_TO_FP32(x1->d)*GGML_CPU_FP16_TO_FP32(y1->d));
}
sumf = vaddvq_f32(sumv0) + vaddvq_f32(sumv1) + summs;
@ -582,7 +583,7 @@ void ggml_vec_dot_q4_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
}
int sumi = sumi0 + sumi1;
sumf += (GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d))*sumi + GGML_FP16_TO_FP32(x[ib].m)*GGML_FP16_TO_FP32(y[ib].s);
sumf += (GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d))*sumi + GGML_CPU_FP16_TO_FP32(x[ib].m)*GGML_CPU_FP16_TO_FP32(y[ib].s);
}
*s = sumf;
@ -666,10 +667,10 @@ void ggml_vec_dot_q5_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddq_s32(
ggml_vdotq_s32(vdupq_n_s32(0), v0_0lf, v1_0l),
ggml_vdotq_s32(vdupq_n_s32(0), v0_0hf, v1_0h))), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
ggml_vdotq_s32(vdupq_n_s32(0), v0_0hf, v1_0h))), GGML_CPU_FP16_TO_FP32(x0->d)*GGML_CPU_FP16_TO_FP32(y0->d));
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddq_s32(
ggml_vdotq_s32(vdupq_n_s32(0), v0_1lf, v1_1l),
ggml_vdotq_s32(vdupq_n_s32(0), v0_1hf, v1_1h))), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
ggml_vdotq_s32(vdupq_n_s32(0), v0_1hf, v1_1h))), GGML_CPU_FP16_TO_FP32(x1->d)*GGML_CPU_FP16_TO_FP32(y1->d));
}
sumf = vaddvq_f32(sumv0) + vaddvq_f32(sumv1);
@ -694,7 +695,7 @@ void ggml_vec_dot_q5_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
}
int sumi = sumi0 + sumi1;
sumf += (GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d)) * sumi;
sumf += (GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d)) * sumi;
}
*s = sumf;
@ -739,8 +740,8 @@ void ggml_vec_dot_q5_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
const uint8x16_t m4b = vdupq_n_u8(0x0F);
summs0 += GGML_FP16_TO_FP32(x0->m) * GGML_FP16_TO_FP32(y0->s);
summs1 += GGML_FP16_TO_FP32(x1->m) * GGML_FP16_TO_FP32(y1->s);
summs0 += GGML_CPU_FP16_TO_FP32(x0->m) * GGML_CPU_FP16_TO_FP32(y0->s);
summs1 += GGML_CPU_FP16_TO_FP32(x1->m) * GGML_CPU_FP16_TO_FP32(y1->s);
// extract the 5th bit via lookup table ((b) << 4)
memcpy(&qh0, x0->qh, sizeof(qh0));
@ -784,10 +785,10 @@ void ggml_vec_dot_q5_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddq_s32(
ggml_vdotq_s32(vdupq_n_s32(0), v0_0lf, v1_0l),
ggml_vdotq_s32(vdupq_n_s32(0), v0_0hf, v1_0h))), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
ggml_vdotq_s32(vdupq_n_s32(0), v0_0hf, v1_0h))), GGML_CPU_FP16_TO_FP32(x0->d)*GGML_CPU_FP16_TO_FP32(y0->d));
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddq_s32(
ggml_vdotq_s32(vdupq_n_s32(0), v0_1lf, v1_1l),
ggml_vdotq_s32(vdupq_n_s32(0), v0_1hf, v1_1h))), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
ggml_vdotq_s32(vdupq_n_s32(0), v0_1hf, v1_1h))), GGML_CPU_FP16_TO_FP32(x1->d)*GGML_CPU_FP16_TO_FP32(y1->d));
}
sumf = vaddvq_f32(sumv0) + vaddvq_f32(sumv1) + summs0 + summs1;
@ -812,7 +813,7 @@ void ggml_vec_dot_q5_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
}
int sumi = sumi0 + sumi1;
sumf += (GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d))*sumi + GGML_FP16_TO_FP32(x[ib].m)*GGML_FP16_TO_FP32(y[ib].s);
sumf += (GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d))*sumi + GGML_CPU_FP16_TO_FP32(x[ib].m)*GGML_CPU_FP16_TO_FP32(y[ib].s);
}
*s = sumf;
@ -864,10 +865,10 @@ void ggml_vec_dot_q8_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
const int8x16_t y1_h = vld1q_s8(b_y1->qs + 16);
float32_t _scale[4] = {
GGML_FP16_TO_FP32(b_x0->d)*GGML_FP16_TO_FP32(b_y0->d),
GGML_FP16_TO_FP32(b_x0->d)*GGML_FP16_TO_FP32(b_y1->d),
GGML_FP16_TO_FP32(b_x1->d)*GGML_FP16_TO_FP32(b_y0->d),
GGML_FP16_TO_FP32(b_x1->d)*GGML_FP16_TO_FP32(b_y1->d)
GGML_CPU_FP16_TO_FP32(b_x0->d)*GGML_CPU_FP16_TO_FP32(b_y0->d),
GGML_CPU_FP16_TO_FP32(b_x0->d)*GGML_CPU_FP16_TO_FP32(b_y1->d),
GGML_CPU_FP16_TO_FP32(b_x1->d)*GGML_CPU_FP16_TO_FP32(b_y0->d),
GGML_CPU_FP16_TO_FP32(b_x1->d)*GGML_CPU_FP16_TO_FP32(b_y1->d)
};
float32x4_t scale = vld1q_f32(_scale);
@ -934,10 +935,10 @@ void ggml_vec_dot_q8_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
sumv0 = svmla_n_f32_x(pl16, sumv0, svcvt_f32_s32_x(pl16, svadd_x(pl16,
svdot_s32(svdup_n_s32(0), qx0_0, qy0_0),
svdot_s32(svdup_n_s32(0), qx0_1, qy0_1))), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
svdot_s32(svdup_n_s32(0), qx0_1, qy0_1))), GGML_CPU_FP16_TO_FP32(x0->d)*GGML_CPU_FP16_TO_FP32(y0->d));
sumv1 = svmla_n_f32_x(pl16, sumv1, svcvt_f32_s32_x(pl16, svadd_x(pl16,
svdot_s32(svdup_n_s32(0), qx1_0, qy1_0),
svdot_s32(svdup_n_s32(0), qx1_1, qy1_1))), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
svdot_s32(svdup_n_s32(0), qx1_1, qy1_1))), GGML_CPU_FP16_TO_FP32(x1->d)*GGML_CPU_FP16_TO_FP32(y1->d));
}
sumf = svaddv_f32(pl16, svadd_f32_x(pl16, sumv0, sumv1));
@ -960,9 +961,9 @@ void ggml_vec_dot_q8_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
const svint8_t qy1 = svld1_s8(svptrue_b8(), y1->qs);
sumv0 = svmla_n_f32_x(svptrue_b32(), sumv0, svcvt_f32_s32_x(svptrue_b32(),
svdot_s32(svdup_n_s32(0), qx0, qy0)), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
svdot_s32(svdup_n_s32(0), qx0, qy0)), GGML_CPU_FP16_TO_FP32(x0->d)*GGML_CPU_FP16_TO_FP32(y0->d));
sumv1 = svmla_n_f32_x(svptrue_b32(), sumv1, svcvt_f32_s32_x(svptrue_b32(),
svdot_s32(svdup_n_s32(0), qx1, qy1)), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
svdot_s32(svdup_n_s32(0), qx1, qy1)), GGML_CPU_FP16_TO_FP32(x1->d)*GGML_CPU_FP16_TO_FP32(y1->d));
}
sumf = svaddv_f32(svptrue_b32(), svadd_f32_x(svptrue_b32(), sumv0, sumv1));
@ -1002,8 +1003,8 @@ void ggml_vec_dot_q8_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
qy_64 = svadd_s8_x(svptrue_b8(), qy_32, qy_64);
// scale creation
const float32_t deq1 = GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d);
const float32_t deq2 = GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d);
const float32_t deq1 = GGML_CPU_FP16_TO_FP32(x0->d)*GGML_CPU_FP16_TO_FP32(y0->d);
const float32_t deq2 = GGML_CPU_FP16_TO_FP32(x1->d)*GGML_CPU_FP16_TO_FP32(y1->d);
// duplicate deq1 in first half of vector and deq2 in second half of vector
const svfloat32_t temp = svdup_f32_m(svdup_f32_z(ph8, deq1), pl8, deq2);
@ -1043,11 +1044,11 @@ void ggml_vec_dot_q8_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
sumv0 = vmlaq_n_f32(sumv0, vcvtq_f32_s32(vaddq_s32(
ggml_vdotq_s32(vdupq_n_s32(0), x0_0, y0_0),
ggml_vdotq_s32(vdupq_n_s32(0), x0_1, y0_1))), GGML_FP16_TO_FP32(x0->d)*GGML_FP16_TO_FP32(y0->d));
ggml_vdotq_s32(vdupq_n_s32(0), x0_1, y0_1))), GGML_CPU_FP16_TO_FP32(x0->d)*GGML_CPU_FP16_TO_FP32(y0->d));
sumv1 = vmlaq_n_f32(sumv1, vcvtq_f32_s32(vaddq_s32(
ggml_vdotq_s32(vdupq_n_s32(0), x1_0, y1_0),
ggml_vdotq_s32(vdupq_n_s32(0), x1_1, y1_1))), GGML_FP16_TO_FP32(x1->d)*GGML_FP16_TO_FP32(y1->d));
ggml_vdotq_s32(vdupq_n_s32(0), x1_1, y1_1))), GGML_CPU_FP16_TO_FP32(x1->d)*GGML_CPU_FP16_TO_FP32(y1->d));
}
sumf = vaddvq_f32(sumv0) + vaddvq_f32(sumv1);
@ -1059,7 +1060,7 @@ void ggml_vec_dot_q8_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
sumi += x[ib].qs[j]*y[ib].qs[j];
}
sumf += sumi*(GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d));
sumf += sumi*(GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d));
}
*s = sumf;
@ -1217,7 +1218,7 @@ void ggml_vec_dot_tq1_0_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
const int16x8_t ysum0 = vld1q_s16(y[i].bsums);
const int16x8_t ysum1 = vld1q_s16(y[i].bsums + 8);
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
#if defined(__ARM_FEATURE_DOTPROD)
sumi0 = vaddq_s32(sumi0, sumi1);
@ -1269,7 +1270,7 @@ void ggml_vec_dot_tq1_0_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
}
}
sumf += (float) sum * (GGML_FP16_TO_FP32(x[i].d) * y[i].d);
sumf += (float) sum * (GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d);
}
*s = sumf;
@ -1362,7 +1363,7 @@ void ggml_vec_dot_tq2_0_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
const int16x8_t ysum0 = vld1q_s16(y[i].bsums);
const int16x8_t ysum1 = vld1q_s16(y[i].bsums + 8);
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
#if defined(__ARM_FEATURE_DOTPROD)
sumi0 = vaddq_s32(sumi0, sumi1);
@ -1393,7 +1394,7 @@ void ggml_vec_dot_tq2_0_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
}
}
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
sumf += (float) sumi * d;
}
@ -1425,9 +1426,9 @@ void ggml_vec_dot_q2_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
switch (vector_length) {
case 128:
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
svfloat32_t d_broad = svdup_n_f32((float32_t)d);
const float dmin = -y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float dmin = -y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
svfloat32_t dmin_broad = svdup_n_f32((float32_t)dmin);
const uint8_t * GGML_RESTRICT q2 = x[i].qs;
@ -1570,9 +1571,9 @@ void ggml_vec_dot_q2_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
case 256:
case 512:
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
svfloat32_t d_broad = svdup_n_f32((float32_t)d);
const float dmin = -y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float dmin = -y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
svfloat32_t dmin_broad = svdup_n_f32((float32_t)dmin);
const uint8_t * GGML_RESTRICT q2 = x[i].qs;
@ -1671,8 +1672,8 @@ void ggml_vec_dot_q2_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
float sum = 0;
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = -y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = -y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
const uint8_t * GGML_RESTRICT q2 = x[i].qs;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
@ -1742,8 +1743,8 @@ void ggml_vec_dot_q2_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
summs += y[i].bsums[j] * (sc[j] >> 4);
}
const float dall = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float dall = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
int isum = 0;
int is = 0;
@ -1805,7 +1806,7 @@ void ggml_vec_dot_q3_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const uint8_t * GGML_RESTRICT q3_sv = x[i].qs;
const uint8_t * GGML_RESTRICT qh_sv = x[i].hmask;
@ -1981,7 +1982,7 @@ void ggml_vec_dot_q3_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const uint8_t * GGML_RESTRICT q3 = x[i].qs;
const uint8_t * GGML_RESTRICT qh = x[i].hmask;
@ -2112,7 +2113,7 @@ void ggml_vec_dot_q3_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += (scales[j] - 32) * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -2258,18 +2259,18 @@ void ggml_vec_dot_q4_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
bias[3] = vaddvq_s32(vaddq_s32(vmull_s16(vget_low_s16(y1_sums), vget_low_s16(x1_mins)),
vmull_s16(vget_high_s16(y1_sums), vget_high_s16(x1_mins))));
const float32x4_t dmins = {
GGML_FP16_TO_FP32(x0->dmin) * y0->d,
GGML_FP16_TO_FP32(x0->dmin) * y1->d,
GGML_FP16_TO_FP32(x1->dmin) * y0->d,
GGML_FP16_TO_FP32(x1->dmin) * y1->d,
GGML_CPU_FP16_TO_FP32(x0->dmin) * y0->d,
GGML_CPU_FP16_TO_FP32(x0->dmin) * y1->d,
GGML_CPU_FP16_TO_FP32(x1->dmin) * y0->d,
GGML_CPU_FP16_TO_FP32(x1->dmin) * y1->d,
};
vfsum = vmlsq_f32(vfsum, vcvtq_f32_s32(vld1q_s32(bias)), dmins);
const float32x4_t superblock_scale = {
GGML_FP16_TO_FP32(x0->d) * y0->d,
GGML_FP16_TO_FP32(x0->d) * y1->d,
GGML_FP16_TO_FP32(x1->d) * y0->d,
GGML_FP16_TO_FP32(x1->d) * y1->d,
GGML_CPU_FP16_TO_FP32(x0->d) * y0->d,
GGML_CPU_FP16_TO_FP32(x0->d) * y1->d,
GGML_CPU_FP16_TO_FP32(x1->d) * y0->d,
GGML_CPU_FP16_TO_FP32(x1->d) * y1->d,
};
vfsum = vmlaq_f32(vfsum, vcvtq_f32_s32(visum), superblock_scale);
}
@ -2289,8 +2290,8 @@ void ggml_vec_dot_q4_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
float sumf = 0;
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
const int16x8_t q8sums = vpaddq_s16(vld1q_s16(y[i].bsums), vld1q_s16(y[i].bsums + 8));
@ -2377,8 +2378,8 @@ void ggml_vec_dot_q4_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
const int16x8_t q8sums = vpaddq_s16(vld1q_s16(y[i].bsums), vld1q_s16(y[i].bsums + 8));
@ -2478,9 +2479,9 @@ void ggml_vec_dot_q4_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
const float dmin = GGML_FP16_TO_FP32(x[i].dmin) * y[i].d;
const float dmin = GGML_CPU_FP16_TO_FP32(x[i].dmin) * y[i].d;
sumf -= dmin * sumi;
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -2520,8 +2521,8 @@ void ggml_vec_dot_q5_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
const int16x8_t q8sums = vpaddq_s16(vld1q_s16(y[i].bsums), vld1q_s16(y[i].bsums + 8));
@ -2630,9 +2631,9 @@ void ggml_vec_dot_q5_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
const float dmin = GGML_FP16_TO_FP32(x[i].dmin) * y[i].d;
const float dmin = GGML_CPU_FP16_TO_FP32(x[i].dmin) * y[i].d;
sumf -= dmin * sumi;
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -2827,10 +2828,10 @@ void ggml_vec_dot_q6_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
const int32x4_t vibias = vmulq_n_s32(vld1q_s32(bias), 32);
const float32x4_t superblock_scale = {
GGML_FP16_TO_FP32(x0->d) * y0->d,
GGML_FP16_TO_FP32(x0->d) * y1->d,
GGML_FP16_TO_FP32(x1->d) * y0->d,
GGML_FP16_TO_FP32(x1->d) * y1->d,
GGML_CPU_FP16_TO_FP32(x0->d) * y0->d,
GGML_CPU_FP16_TO_FP32(x0->d) * y1->d,
GGML_CPU_FP16_TO_FP32(x1->d) * y0->d,
GGML_CPU_FP16_TO_FP32(x1->d) * y1->d,
};
visum = vsubq_s32(visum, vibias);
@ -2858,7 +2859,7 @@ void ggml_vec_dot_q6_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
svuint8_t q6h_1, q6h_2, q6h_3, q6h_4;
for (int i = 0; i < nb; ++i) {
const float d_all = GGML_FP16_TO_FP32(x[i].d);
const float d_all = GGML_CPU_FP16_TO_FP32(x[i].d);
const uint8_t * GGML_RESTRICT q6 = x[i].ql;
const uint8_t * GGML_RESTRICT qh = x[i].qh;
@ -3011,7 +3012,7 @@ void ggml_vec_dot_q6_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int i = 0; i < nb; ++i) {
const float d_all = GGML_FP16_TO_FP32(x[i].d);
const float d_all = GGML_CPU_FP16_TO_FP32(x[i].d);
const uint8_t * GGML_RESTRICT q6 = x[i].ql;
const uint8_t * GGML_RESTRICT qh = x[i].qh;
@ -3128,7 +3129,7 @@ void ggml_vec_dot_q6_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -3199,7 +3200,7 @@ void ggml_vec_dot_iq2_xxs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const
float sumf = 0;
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint16_t * GGML_RESTRICT q2 = x[i].qs;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
float sumf1 = 0, sumf2 = 0;
@ -3234,7 +3235,7 @@ void ggml_vec_dot_iq2_xxs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const
float sumf = 0.f;
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint16_t * GGML_RESTRICT q2 = x[i].qs;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
int32_t bsum = 0;
@ -3284,7 +3285,7 @@ void ggml_vec_dot_iq2_xs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const v
float sumf = 0;
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint16_t * GGML_RESTRICT q2 = x[i].qs;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
const uint8x8_t scales8 = vld1_u8(x[i].scales);
@ -3329,7 +3330,7 @@ void ggml_vec_dot_iq2_xs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const v
float sumf = 0.f;
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint16_t * GGML_RESTRICT q2 = x[i].qs;
const uint8_t * GGML_RESTRICT sc = x[i].scales;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
@ -3398,7 +3399,7 @@ void ggml_vec_dot_iq2_s_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
float sumf = 0;
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint8_t * GGML_RESTRICT qs = x[i].qs;
const uint8_t * GGML_RESTRICT qh = x[i].qh;
@ -3458,7 +3459,7 @@ void ggml_vec_dot_iq2_s_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
float sumf = 0;
for (int i = 0; i < nb; i++) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const int8_t * q8 = y[i].qs;
const uint8_t * qs = x[i].qs;
const uint8_t * qh = x[i].qh;
@ -3521,7 +3522,7 @@ void ggml_vec_dot_iq3_xxs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const
float sumf = 0;
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint8_t * GGML_RESTRICT q3 = x[i].qs;
const uint8_t * GGML_RESTRICT gas = x[i].qs + QK_K/4;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
@ -3557,7 +3558,7 @@ void ggml_vec_dot_iq3_xxs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const
float sumf = 0.f;
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint8_t * GGML_RESTRICT q3 = x[i].qs;
const uint8_t * GGML_RESTRICT gas = x[i].qs + QK_K/4;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
@ -3630,7 +3631,7 @@ void ggml_vec_dot_iq3_s_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
float sumf = 0;
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint8_t * GGML_RESTRICT qs = x[i].qs;
const uint8_t * GGML_RESTRICT qh = x[i].qh;
const uint16_t * GGML_RESTRICT signs = (const uint16_t *)x[i].signs;
@ -3691,7 +3692,7 @@ void ggml_vec_dot_iq3_s_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
float sumf = 0.f;
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint8_t * GGML_RESTRICT qs = x[i].qs;
const uint8_t * GGML_RESTRICT qh = x[i].qh;
const uint8_t * GGML_RESTRICT signs = x[i].signs;
@ -3786,7 +3787,7 @@ void ggml_vec_dot_iq1_s_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
}
sumf += y[i].d * GGML_FP16_TO_FP32(x[i].d) * (sumi1 + sumi2 + IQ1S_DELTA * sumi3);
sumf += y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d) * (sumi1 + sumi2 + IQ1S_DELTA * sumi3);
}
*s = sumf;
@ -3817,7 +3818,7 @@ void ggml_vec_dot_iq1_s_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
qs += 4;
}
sumf += GGML_FP16_TO_FP32(x[i].d) * y[i].d * (sumi + IQ1S_DELTA * sumi1);
sumf += GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d * (sumi + IQ1S_DELTA * sumi1);
}
*s = sumf;
@ -3905,7 +3906,7 @@ void ggml_vec_dot_iq1_m_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
}
sumf += y[i].d * GGML_FP16_TO_FP32(scale.f16) * (vaddvq_s32(sumi1) + IQ1M_DELTA * vaddvq_s32(sumi2));
sumf += y[i].d * GGML_CPU_FP16_TO_FP32(scale.f16) * (vaddvq_s32(sumi1) + IQ1M_DELTA * vaddvq_s32(sumi2));
}
*s = sumf;
@ -3952,7 +3953,7 @@ void ggml_vec_dot_iq1_m_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
qh += 2;
}
sumf += GGML_FP16_TO_FP32(scale.f16) * y[i].d * (sumi1 + IQ1M_DELTA * sumi2);
sumf += GGML_CPU_FP16_TO_FP32(scale.f16) * y[i].d * (sumi1 + IQ1M_DELTA * sumi2);
}
*s = sumf;
@ -4003,13 +4004,13 @@ void ggml_vec_dot_iq4_nl_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const v
prod_2 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), q4b.val[2], q8b.val[2]), q4b.val[3], q8b.val[3]);
sumf +=
GGML_FP16_TO_FP32(x[ib+0].d) * GGML_FP16_TO_FP32(y[ib + 0].d) * vaddvq_s32(prod_1) +
GGML_FP16_TO_FP32(x[ib+1].d) * GGML_FP16_TO_FP32(y[ib + 1].d) * vaddvq_s32(prod_2);
GGML_CPU_FP16_TO_FP32(x[ib+0].d) * GGML_CPU_FP16_TO_FP32(y[ib + 0].d) * vaddvq_s32(prod_1) +
GGML_CPU_FP16_TO_FP32(x[ib+1].d) * GGML_CPU_FP16_TO_FP32(y[ib + 1].d) * vaddvq_s32(prod_2);
}
#endif
for (; ib < nb; ++ib) {
const float d = GGML_FP16_TO_FP32(y[ib].d)*GGML_FP16_TO_FP32(x[ib].d);
const float d = GGML_CPU_FP16_TO_FP32(y[ib].d)*GGML_CPU_FP16_TO_FP32(x[ib].d);
int sumi1 = 0, sumi2 = 0;
for (int j = 0; j < QK4_NL/2; ++j) {
sumi1 += y[ib].qs[j+ 0] * kvalues_iq4nl[x[ib].qs[j] & 0xf];
@ -4071,7 +4072,7 @@ void ggml_vec_dot_iq4_xs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const v
}
sumf += GGML_FP16_TO_FP32(x[ibl].d) * y[ibl].d * (sumi1 + sumi2);
sumf += GGML_CPU_FP16_TO_FP32(x[ibl].d) * y[ibl].d * (sumi1 + sumi2);
}
*s = sumf;
@ -4079,7 +4080,7 @@ void ggml_vec_dot_iq4_xs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const v
#else
float sumf = 0;
for (int ibl = 0; ibl < nb; ++ibl) {
const float d4d8 = GGML_FP16_TO_FP32(x[ibl].d) * y[ibl].d;
const float d4d8 = GGML_CPU_FP16_TO_FP32(x[ibl].d) * y[ibl].d;
uint16_t h = x[ibl].scales_h;
const uint8_t * qs = x[ibl].qs;
const int8_t * q8 = y[ibl].qs;

25
ggml/src/ggml-cpu/arch/arm/repack.cpp
View File

@ -6,6 +6,7 @@
#include "ggml-impl.h"
#include "ggml-cpu.h"
#include "ggml-cpu-impl.h"
#include "simd-mappings.h"
#include "traits.h"
#include <cmath>
@ -51,7 +52,7 @@ void ggml_quantize_mat_q8_0_4x4(const float * GGML_RESTRICT x, void * GGML_RESTR
const float d = amax / ((1 << 7) - 1);
id[row_iter] = d ? 1.0f / d : 0.0f;
y[i].d[row_iter] = GGML_FP32_TO_FP16(d);
y[i].d[row_iter] = GGML_CPU_FP32_TO_FP16(d);
}
for (int j = 0; j < 8; j++) {
@ -102,7 +103,7 @@ void ggml_quantize_mat_q8_0_4x4(const float * GGML_RESTRICT x, void * GGML_RESTR
const float d = amax / ((1 << 7) - 1);
id[row_iter] = d ? 1.0f / d : 0.0f;
y[i].d[row_iter] = GGML_FP32_TO_FP16(d);
y[i].d[row_iter] = GGML_CPU_FP32_TO_FP16(d);
}
for (int j = 0; j < QK8_0 * 4; j++) {
@ -145,7 +146,7 @@ void ggml_quantize_mat_q8_0_4x8(const float * GGML_RESTRICT x, void * GGML_RESTR
const float d = amax / ((1 << 7) - 1);
id[row_iter] = d ? 1.0f / d : 0.0f;
y[i].d[row_iter] = GGML_FP32_TO_FP16(d);
y[i].d[row_iter] = GGML_CPU_FP32_TO_FP16(d);
}
for (int j = 0; j < 4; j++) {
@ -221,7 +222,7 @@ void ggml_quantize_mat_q8_0_4x8(const float * GGML_RESTRICT x, void * GGML_RESTR
const float d = amax / ((1 << 7) - 1);
id[row_iter] = d ? 1.0f / d : 0.0f;
y[i].d[row_iter] = GGML_FP32_TO_FP16(d);
y[i].d[row_iter] = GGML_CPU_FP32_TO_FP16(d);
}
for (int j = 0; j < QK8_0 * 4; j++) {
@ -311,7 +312,7 @@ void ggml_gemv_q4_0_4x4_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const vo
const int v1 = (int8_t) (b_ptr[l].qs[k * ncols_interleaved * blocklen + j * blocklen + i] & 0xF0);
sumi += ((v0 * a_ptr[l].qs[k * blocklen + i]) + (v1 * a_ptr[l].qs[k * blocklen + i + qk / 2])) >> 4;
}
sumf[j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_FP16_TO_FP32(a_ptr[l].d);
sumf[j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_CPU_FP16_TO_FP32(a_ptr[l].d);
}
}
}
@ -399,7 +400,7 @@ void ggml_gemv_q4_0_4x8_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const vo
const int v1 = (int8_t) (b_ptr[l].qs[k * ncols_interleaved * blocklen + j * blocklen + i] & 0xF0);
sumi += ((v0 * a_ptr[l].qs[k * blocklen + i]) + (v1 * a_ptr[l].qs[k * blocklen + i + qk / 2])) >> 4;
}
sumf[j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_FP16_TO_FP32(a_ptr[l].d);
sumf[j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_CPU_FP16_TO_FP32(a_ptr[l].d);
}
}
}
@ -514,7 +515,7 @@ void ggml_gemv_q4_0_8x8_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const vo
const int v1 = (int8_t) (b_ptr[l].qs[k * ncols_interleaved * blocklen + j * blocklen + i] & 0xF0);
sumi += ((v0 * a_ptr[l].qs[k * blocklen + i]) + (v1 * a_ptr[l].qs[k * blocklen + i + qk / 2])) >> 4;
}
sumf[j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_FP16_TO_FP32(a_ptr[l].d);
sumf[j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_CPU_FP16_TO_FP32(a_ptr[l].d);
}
}
}
@ -608,7 +609,7 @@ void ggml_gemv_iq4_nl_4x4_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const
const int v1 = kvalues_iq4nl[b_ptr[l].qs[k * ncols_interleaved * blocklen + j * blocklen + i] >> 4];
sumi += ((v0 * a_ptr[l].qs[k * blocklen + i]) + (v1 * a_ptr[l].qs[k * blocklen + i + qk / 2]));
}
sumf[j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_FP16_TO_FP32(a_ptr[l].d);
sumf[j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_CPU_FP16_TO_FP32(a_ptr[l].d);
}
}
}
@ -1117,7 +1118,7 @@ void ggml_gemm_q4_0_4x4_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const vo
sumi += ((v0 * a_ptr[l].qs[k * 4 * blocklen + m * blocklen + i]) +
(v1 * a_ptr[l].qs[k * 4 * blocklen + m * blocklen + i + qk / 2 * 4])) >> 4;
}
sumf[m][j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_FP16_TO_FP32(a_ptr[l].d[m]);
sumf[m][j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_CPU_FP16_TO_FP32(a_ptr[l].d[m]);
}
}
}
@ -1570,7 +1571,7 @@ void ggml_gemm_q4_0_4x8_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const vo
sumi += ((v0 * a_ptr[l].qs[k * 4 * blocklen + m * blocklen + i]) +
(v1 * a_ptr[l].qs[k * 4 * blocklen + m * blocklen + i + qk / 2 * 4])) >> 4;
}
sumf[m][j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_FP16_TO_FP32(a_ptr[l].d[m]);
sumf[m][j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_CPU_FP16_TO_FP32(a_ptr[l].d[m]);
}
}
}
@ -2039,7 +2040,7 @@ void ggml_gemm_q4_0_8x8_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const vo
sumi += ((v0 * a_ptr[l].qs[k * 4 * blocklen + m * blocklen + i]) +
(v1 * a_ptr[l].qs[k * 4 * blocklen + m * blocklen + i + qk / 2 * 4])) >> 4;
}
sumf[m][j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_FP16_TO_FP32(a_ptr[l].d[m]);
sumf[m][j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_CPU_FP16_TO_FP32(a_ptr[l].d[m]);
}
}
}
@ -2147,7 +2148,7 @@ void ggml_gemm_iq4_nl_4x4_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const
sumi += ((v0 * a_ptr[l].qs[k * 4 * blocklen + m * blocklen + i]) +
(v1 * a_ptr[l].qs[k * 4 * blocklen + m * blocklen + i + qk / 2 * 4]));
}
sumf[m][j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_FP16_TO_FP32(a_ptr[l].d[m]);
sumf[m][j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_CPU_FP16_TO_FP32(a_ptr[l].d[m]);
}
}
}

105
ggml/src/ggml-cpu/arch/loongarch/quants.c
View File

@ -3,6 +3,7 @@
#include "ggml-quants.h"
#include "ggml-impl.h"
#include "ggml-cpu.h"
#include "simd-mappings.h"
#include "../../quants.h"
#include "../../ggml-cpu-impl.h"
@ -474,7 +475,7 @@ void quantize_row_q8_0(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, i
// Quantize these floats
const float d = max_scalar / 127.f;
y[i].d = GGML_FP32_TO_FP16(d);
y[i].d = GGML_CPU_FP32_TO_FP16(d);
const float id = ( max_scalar != 0.0f ) ? 127.f / max_scalar : 0.0f;
const __m256 mul = (__m256)__lasx_xvreplfr2vr_s( id );
@ -548,7 +549,7 @@ void quantize_row_q8_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, i
// Quantize these floats
const float d = max_scalar / 127.f;
y[i].d = GGML_FP32_TO_FP16(d);
y[i].d = GGML_CPU_FP32_TO_FP16(d);
const float id = ( max_scalar != 0.0f ) ? 127.f / max_scalar : 0.0f;
const __m256 mul = __lasx_xvreplfr2vr_s( id );
@ -576,7 +577,7 @@ void quantize_row_q8_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, i
// Compute the sum of the quants and set y[i].s
const __m128i s0 = __lsx_vadd_w(__lsx_vadd_w(ni0, ni1), __lsx_vadd_w(ni2, ni3));
const __m128i s1 = __lsx_vadd_w(__lsx_vadd_w(ni4, ni5), __lsx_vadd_w(ni6, ni7));
y[i].s = GGML_FP32_TO_FP16(d * hsum_i32_4(__lsx_vadd_w(s0, s1)));
y[i].s = GGML_CPU_FP32_TO_FP16(d * hsum_i32_4(__lsx_vadd_w(s0, s1)));
// Convert int32 to int16
ni0 = lsx_packs_w( ni0, ni1 );
@ -667,7 +668,7 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
// Main loop
for (; ib < nb; ++ib) {
/* Compute combined scale for the block */
const __m256 d = __lasx_xvreplfr2vr_s( GGML_FP16_TO_FP32(x[ib].d) * GGML_FP16_TO_FP32(y[ib].d) );
const __m256 d = __lasx_xvreplfr2vr_s( GGML_CPU_FP16_TO_FP32(x[ib].d) * GGML_CPU_FP16_TO_FP32(y[ib].d) );
__m256i qx = bytes_from_nibbles_32(x[ib].qs);
@ -699,7 +700,7 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (; ib + 1 < nb; ib += 2) {
// Compute combined scale for the block 0 and 1
const __m128 d_0_1 = (__m128)__lsx_vreplgr2vr_w( GGML_FP16_TO_FP32(x[ib].d) * GGML_FP16_TO_FP32(y[ib].d) );
const __m128 d_0_1 = (__m128)__lsx_vreplgr2vr_w( GGML_CPU_FP16_TO_FP32(x[ib].d) * GGML_CPU_FP16_TO_FP32(y[ib].d) );
const __m128i tmp_0_1 = __lsx_vld((const __m128i *)x[ib].qs, 0);
@ -717,7 +718,7 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
//_mm_prefetch(&y[ib] + 2 * sizeof(block_q8_0), _MM_HINT_T0);
// Compute combined scale for the block 2 and 3
const __m128 d_2_3 = (__m128)__lsx_vreplgr2vr_w( GGML_FP16_TO_FP32(x[ib + 1].d) * GGML_FP16_TO_FP32(y[ib + 1].d) );
const __m128 d_2_3 = (__m128)__lsx_vreplgr2vr_w( GGML_CPU_FP16_TO_FP32(x[ib + 1].d) * GGML_CPU_FP16_TO_FP32(y[ib + 1].d) );
const __m128i tmp_2_3 = __lsx_vld((const __m128i *)x[ib + 1].qs, 0);
@ -766,7 +767,7 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
}
int sumi = sumi0 + sumi1;
sumf += sumi*GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d);
sumf += sumi*GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d);
}
*s = sumf;
@ -797,10 +798,10 @@ void ggml_vec_dot_q4_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
// Main loop
for (; ib < nb; ++ib) {
const float d0 = GGML_FP16_TO_FP32(x[ib].d);
const float d1 = GGML_FP16_TO_FP32(y[ib].d);
const float d0 = GGML_CPU_FP16_TO_FP32(x[ib].d);
const float d1 = GGML_CPU_FP16_TO_FP32(y[ib].d);
summs += GGML_FP16_TO_FP32(x[ib].m) * GGML_FP16_TO_FP32(y[ib].s);
summs += GGML_CPU_FP16_TO_FP32(x[ib].m) * GGML_CPU_FP16_TO_FP32(y[ib].s);
const __m256 d0v = __lasx_xvreplfr2vr_s( d0 );
const __m256 d1v = __lasx_xvreplfr2vr_s( d1 );
@ -834,7 +835,7 @@ void ggml_vec_dot_q4_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
}
int sumi = sumi0 + sumi1;
sumf += (GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d))*sumi + GGML_FP16_TO_FP32(x[ib].m)*GGML_FP16_TO_FP32(y[ib].s);
sumf += (GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d))*sumi + GGML_CPU_FP16_TO_FP32(x[ib].m)*GGML_CPU_FP16_TO_FP32(y[ib].s);
}
*s = sumf;
@ -865,7 +866,7 @@ void ggml_vec_dot_q5_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
// Main loop
for (; ib < nb; ++ib) {
/* Compute combined scale for the block */
const __m256 d = __lasx_xvreplfr2vr_s(GGML_FP16_TO_FP32(x[ib].d) * GGML_FP16_TO_FP32(y[ib].d)); //FIXME
const __m256 d = __lasx_xvreplfr2vr_s(GGML_CPU_FP16_TO_FP32(x[ib].d) * GGML_CPU_FP16_TO_FP32(y[ib].d)); //FIXME
__m256i qx = bytes_from_nibbles_32(x[ib].qs);
__m256i bxhi = bytes_from_bits_32(x[ib].qh);
@ -902,7 +903,7 @@ void ggml_vec_dot_q5_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
}
int sumi = sumi0 + sumi1;
sumf += (GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d)) * sumi;
sumf += (GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d)) * sumi;
}
*s = sumf;
@ -934,16 +935,16 @@ void ggml_vec_dot_q5_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
// Main loop
for (; ib < nb; ++ib) {
const __m256 dx = __lasx_xvreplfr2vr_s(GGML_FP16_TO_FP32(x[ib].d));
const __m256 dx = __lasx_xvreplfr2vr_s(GGML_CPU_FP16_TO_FP32(x[ib].d));
summs += GGML_FP16_TO_FP32(x[ib].m) * GGML_FP16_TO_FP32(y[ib].s);
summs += GGML_CPU_FP16_TO_FP32(x[ib].m) * GGML_CPU_FP16_TO_FP32(y[ib].s);
__m256i qx = bytes_from_nibbles_32(x[ib].qs);
__m256i bxhi = bytes_from_bits_32(x[ib].qh);
bxhi = __lasx_xvand_v(bxhi, __lasx_xvreplgr2vr_b(0x10));
qx = __lasx_xvor_v(qx, bxhi);
const __m256 dy = __lasx_xvreplfr2vr_s(GGML_FP16_TO_FP32(y[ib].d));
const __m256 dy = __lasx_xvreplfr2vr_s(GGML_CPU_FP16_TO_FP32(y[ib].d));
const __m256i qy = __lasx_xvld((const __m256i *)y[ib].qs, 0);
const __m256 q = mul_sum_us8_pairs_float(qx, qy);
@ -973,7 +974,7 @@ void ggml_vec_dot_q5_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
}
int sumi = sumi0 + sumi1;
sumf += (GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d))*sumi + GGML_FP16_TO_FP32(x[ib].m)*GGML_FP16_TO_FP32(y[ib].s);
sumf += (GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d))*sumi + GGML_CPU_FP16_TO_FP32(x[ib].m)*GGML_CPU_FP16_TO_FP32(y[ib].s);
}
*s = sumf;
@ -1003,7 +1004,7 @@ void ggml_vec_dot_q8_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
// Main loop
for (; ib < nb; ++ib) {
// Compute combined scale for the block
const __m256 d = __lasx_xvreplfr2vr_s(GGML_FP16_TO_FP32(x[ib].d) * GGML_FP16_TO_FP32(y[ib].d));
const __m256 d = __lasx_xvreplfr2vr_s(GGML_CPU_FP16_TO_FP32(x[ib].d) * GGML_CPU_FP16_TO_FP32(y[ib].d));
__m256i qx = __lasx_xvld((const __m256i *)x[ib].qs, 0);
__m256i qy = __lasx_xvld((const __m256i *)y[ib].qs, 0);
@ -1023,7 +1024,7 @@ void ggml_vec_dot_q8_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
sumi += x[ib].qs[j]*y[ib].qs[j];
}
sumf += sumi*(GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d));
sumf += sumi*(GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d));
}
*s = sumf;
@ -1047,8 +1048,8 @@ void ggml_vec_dot_q2_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = -y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = -y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
const uint8_t * GGML_RESTRICT q2 = x[i].qs;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
@ -1116,8 +1117,8 @@ void ggml_vec_dot_q2_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
summs += y[i].bsums[j] * (sc[j] >> 4);
}
const float dall = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float dall = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
int isum = 0;
int is = 0;
@ -1170,7 +1171,7 @@ void ggml_vec_dot_q3_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const uint8_t * GGML_RESTRICT q3 = x[i].qs;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
// Set up scales
@ -1294,7 +1295,7 @@ void ggml_vec_dot_q3_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += (scales[j] - 32) * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -1330,8 +1331,8 @@ void ggml_vec_dot_q4_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = -y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = -y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
memcpy(utmp, x[i].scales, 12);
utmp[3] = ((utmp[2] >> 4) & kmask2) | (((utmp[1] >> 6) & kmask3) << 4);
@ -1438,9 +1439,9 @@ void ggml_vec_dot_q4_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
const float dmin = GGML_FP16_TO_FP32(x[i].dmin) * y[i].d;
const float dmin = GGML_CPU_FP16_TO_FP32(x[i].dmin) * y[i].d;
sumf -= dmin * sumi;
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -1477,8 +1478,8 @@ void ggml_vec_dot_q5_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
const uint8_t * GGML_RESTRICT q5 = x[i].qs;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = -y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = -y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
memcpy(utmp, x[i].scales, 12);
utmp[3] = ((utmp[2] >> 4) & kmask2) | (((utmp[1] >> 6) & kmask3) << 4);
@ -1593,9 +1594,9 @@ void ggml_vec_dot_q5_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
const float dmin = GGML_FP16_TO_FP32(x[i].dmin) * y[i].d;
const float dmin = GGML_CPU_FP16_TO_FP32(x[i].dmin) * y[i].d;
sumf -= dmin * sumi;
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -1624,7 +1625,7 @@ void ggml_vec_dot_q6_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const uint8_t * GGML_RESTRICT q4 = x[i].ql;
const uint8_t * GGML_RESTRICT qh = x[i].qh;
@ -1713,7 +1714,7 @@ void ggml_vec_dot_q6_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -1780,7 +1781,7 @@ void ggml_vec_dot_iq2_xxs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const
__m256 accumf = (__m256)__lasx_xvldi(0);
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint16_t * GGML_RESTRICT q2 = x[i].qs;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
__m256i sumi1 = __lasx_xvldi(0);
@ -1820,7 +1821,7 @@ void ggml_vec_dot_iq2_xxs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const
float sumf = 0.f;
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint16_t * GGML_RESTRICT q2 = x[i].qs;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
int32_t bsum = 0;
@ -1895,7 +1896,7 @@ void ggml_vec_dot_iq2_xs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const v
__m256 accumf = (__m256)__lasx_xvldi(0);
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint16_t * GGML_RESTRICT q2 = x[i].qs;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
@ -1980,7 +1981,7 @@ void ggml_vec_dot_iq2_xs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const v
float sumf = 0.f;
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint16_t * GGML_RESTRICT q2 = x[i].qs;
const uint8_t * GGML_RESTRICT sc = x[i].scales;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
@ -2049,7 +2050,7 @@ void ggml_vec_dot_iq2_s_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
__m256 accumf = (__m256)__lasx_xvldi(0);
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint8_t * GGML_RESTRICT qs = x[i].qs;
const uint8_t * GGML_RESTRICT qh = x[i].qh;
const uint16_t * GGML_RESTRICT signs = (const uint16_t *)(x[i].qs + QK_K/8);
@ -2108,7 +2109,7 @@ void ggml_vec_dot_iq2_s_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
float sumf = 0;
for (int i = 0; i < nb; i++) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const int8_t * q8 = y[i].qs;
const uint8_t * qs = x[i].qs;
const uint8_t * qh = x[i].qh;
@ -2168,7 +2169,7 @@ void ggml_vec_dot_iq3_xxs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const
__m256 accumf = (__m256)__lasx_xvldi(0);
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint8_t * GGML_RESTRICT q3 = x[i].qs;
const uint8_t * GGML_RESTRICT gas = x[i].qs + QK_K/4;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
@ -2213,7 +2214,7 @@ void ggml_vec_dot_iq3_xxs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const
float sumf = 0.f;
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint8_t * GGML_RESTRICT q3 = x[i].qs;
const uint8_t * GGML_RESTRICT gas = x[i].qs + QK_K/4;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
@ -2279,7 +2280,7 @@ void ggml_vec_dot_iq3_s_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
__m256 accumf = (__m256)__lasx_xvldi(0);
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint8_t * GGML_RESTRICT qs = x[i].qs;
const uint8_t * GGML_RESTRICT qh = x[i].qh;
const uint16_t * GGML_RESTRICT signs = (const uint16_t *)x[i].signs;
@ -2340,7 +2341,7 @@ void ggml_vec_dot_iq3_s_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
float sumf = 0.f;
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint8_t * GGML_RESTRICT qs = x[i].qs;
const uint8_t * GGML_RESTRICT qh = x[i].qh;
const uint8_t * GGML_RESTRICT signs = x[i].signs;
@ -2451,7 +2452,7 @@ void ggml_vec_dot_iq1_s_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
+ (y[i].bsums[2*ib+2] + y[i].bsums[2*ib+3]) * (qh[ib+1] & 0x8000 ? -1 : 1) * ls2;
}
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
accum = __lasx_xvfmadd_s(__lasx_xvreplfr2vr_s(d), __lasx_xvffint_s_w(sumi), accum);
accum1 += d * sumi1;
}
@ -2484,7 +2485,7 @@ void ggml_vec_dot_iq1_s_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
qs += 4;
}
sumf += GGML_FP16_TO_FP32(x[i].d) * y[i].d * (sumi + IQ1S_DELTA * sumi1);
sumf += GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d * (sumi + IQ1S_DELTA * sumi1);
}
*s = sumf;
@ -2530,9 +2531,9 @@ void ggml_vec_dot_iq4_nl_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const v
const __m256i p16_2 = mul_add_epi8(q4b_2, q8b_2);
const __m256i p_1 = lasx_madd_h(p16_1, mone);
const __m256i p_2 = lasx_madd_h(p16_2, mone);
accum1 = __lasx_xvfmadd_s(__lasx_xvreplfr2vr_s(GGML_FP16_TO_FP32(y[ib + 0].d)*GGML_FP16_TO_FP32(x[ib + 0].d)),
accum1 = __lasx_xvfmadd_s(__lasx_xvreplfr2vr_s(GGML_CPU_FP16_TO_FP32(y[ib + 0].d)*GGML_CPU_FP16_TO_FP32(x[ib + 0].d)),
__lasx_xvffint_s_w(p_1), accum1);
accum2 = __lasx_xvfmadd_s(__lasx_xvreplfr2vr_s(GGML_FP16_TO_FP32(y[ib + 1].d)*GGML_FP16_TO_FP32(x[ib + 1].d)),
accum2 = __lasx_xvfmadd_s(__lasx_xvreplfr2vr_s(GGML_CPU_FP16_TO_FP32(y[ib + 1].d)*GGML_CPU_FP16_TO_FP32(x[ib + 1].d)),
__lasx_xvffint_s_w(p_2), accum2);
}
@ -2540,7 +2541,7 @@ void ggml_vec_dot_iq4_nl_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const v
#endif
for (; ib < nb; ++ib) {
const float d = GGML_FP16_TO_FP32(y[ib].d)*GGML_FP16_TO_FP32(x[ib].d);
const float d = GGML_CPU_FP16_TO_FP32(y[ib].d)*GGML_CPU_FP16_TO_FP32(x[ib].d);
int sumi1 = 0, sumi2 = 0;
for (int j = 0; j < QK4_NL/2; ++j) {
sumi1 += y[ib].qs[j+ 0] * kvalues_iq4nl[x[ib].qs[j] & 0xf];
@ -2595,7 +2596,7 @@ void ggml_vec_dot_iq4_xs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const v
sumi1 = __lasx_xvadd_w(p_1, sumi1);
sumi2 = __lasx_xvadd_w(p_2, sumi2);
}
accum = __lasx_xvfmadd_s(__lasx_xvreplfr2vr_s(GGML_FP16_TO_FP32(x[ibl].d)*y[ibl].d),
accum = __lasx_xvfmadd_s(__lasx_xvreplfr2vr_s(GGML_CPU_FP16_TO_FP32(x[ibl].d)*y[ibl].d),
__lasx_xvffint_s_w(__lasx_xvadd_w(sumi1, sumi2)), accum);
}
@ -2604,7 +2605,7 @@ void ggml_vec_dot_iq4_xs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const v
#else
float sumf = 0;
for (int ibl = 0; ibl < nb; ++ibl) {
const float d4d8 = GGML_FP16_TO_FP32(x[ibl].d) * y[ibl].d;
const float d4d8 = GGML_CPU_FP16_TO_FP32(x[ibl].d) * y[ibl].d;
uint16_t h = x[ibl].scales_h;
const uint8_t * qs = x[ibl].qs;
const int8_t * q8 = y[ibl].qs;

111
ggml/src/ggml-cpu/arch/powerpc/quants.c
View File

@ -3,6 +3,7 @@
#include "ggml-quants.h"
#include "ggml-impl.h"
#include "ggml-cpu.h"
#include "simd-mappings.h"
#include "../../quants.h"
#include "../../ggml-cpu-impl.h"
@ -67,7 +68,7 @@ void quantize_row_q8_0(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, i
const float id = d ? 1.0f/d : 0.0f;
const vector float vid = vec_splats(id);
y[i].d = GGML_FP32_TO_FP16(d);
y[i].d = GGML_CPU_FP32_TO_FP16(d);
for (int j = 0; j < 8; j++) {
const vector float v = vec_round(vec_mul(srcv[j], vid));
@ -112,7 +113,7 @@ void quantize_row_q8_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, i
const float id = d ? 1.0f/d : 0.0f;
const vector float vid = vec_splats(id);
y[i].d = GGML_FP32_TO_FP16(d);
y[i].d = GGML_CPU_FP32_TO_FP16(d);
vector int accv = vec_splats(0);
@ -127,7 +128,7 @@ void quantize_row_q8_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, i
accv = vec_add(accv, vec_sld(accv, accv, 4));
accv = vec_add(accv, vec_sld(accv, accv, 8));
y[i].s = GGML_FP32_TO_FP16(d * vec_extract(accv, 0));
y[i].s = GGML_CPU_FP32_TO_FP16(d * vec_extract(accv, 0));
}
#else
@ -170,8 +171,8 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
__builtin_prefetch(x[ib].qs, 0, 1);
__builtin_prefetch(y[ib].qs, 0, 1);
vector float vxd = vec_splats(GGML_FP16_TO_FP32(x[ib].d));
vector float vyd = vec_splats(GGML_FP16_TO_FP32(y[ib].d));
vector float vxd = vec_splats(GGML_CPU_FP16_TO_FP32(x[ib].d));
vector float vyd = vec_splats(GGML_CPU_FP16_TO_FP32(y[ib].d));
vector float vd = vec_mul(vxd, vyd);
vector signed char qxs = (vector signed char)vec_xl( 0, x[ib].qs);
@ -214,7 +215,7 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
}
int sumi = sumi0 + sumi1;
sumf += sumi*GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d);
sumf += sumi*GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d);
}
*s = sumf;
@ -249,12 +250,12 @@ void ggml_vec_dot_q4_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
__builtin_prefetch(x[ib].qs, 0, 1);
__builtin_prefetch(y[ib].qs, 0, 1);
vector float vxd = vec_splats(GGML_FP16_TO_FP32(x[ib].d));
vector float vyd = vec_splats(GGML_FP16_TO_FP32(y[ib].d));
vector float vxd = vec_splats(GGML_CPU_FP16_TO_FP32(x[ib].d));
vector float vyd = vec_splats(GGML_CPU_FP16_TO_FP32(y[ib].d));
vector float vd = vec_mul(vxd, vyd);
vector float vxmin = vec_splats(GGML_FP16_TO_FP32(x[ib].m));
vector float vys = {GGML_FP16_TO_FP32(y[ib].s), 0.0f, 0.0f, 0.0f};
vector float vxmin = vec_splats(GGML_CPU_FP16_TO_FP32(x[ib].m));
vector float vys = {GGML_CPU_FP16_TO_FP32(y[ib].s), 0.0f, 0.0f, 0.0f};
vsumf0 = vec_madd(vxmin, vys, vsumf0);
vector signed char qxs = (vector signed char)vec_xl( 0, x[ib].qs);
@ -291,7 +292,7 @@ void ggml_vec_dot_q4_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
}
int sumi = sumi0 + sumi1;
sumf += (GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d))*sumi + GGML_FP16_TO_FP32(x[ib].m)*GGML_FP16_TO_FP32(y[ib].s);
sumf += (GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d))*sumi + GGML_CPU_FP16_TO_FP32(x[ib].m)*GGML_CPU_FP16_TO_FP32(y[ib].s);
}
*s = sumf;
@ -326,8 +327,8 @@ void ggml_vec_dot_q5_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
__builtin_prefetch(x[ib].qs, 0, 1);
__builtin_prefetch(y[ib].qs, 0, 1);
vector float vxd = vec_splats(GGML_FP16_TO_FP32(x[ib].d));
vector float vyd = vec_splats(GGML_FP16_TO_FP32(y[ib].d));
vector float vxd = vec_splats(GGML_CPU_FP16_TO_FP32(x[ib].d));
vector float vyd = vec_splats(GGML_CPU_FP16_TO_FP32(y[ib].d));
vector float vd = vec_mul(vxd, vyd);
vector signed long long aux64x2_0 = {(uint64_t)(table_b2b_1[x[ib].qh[0]]), (uint64_t)(table_b2b_1[x[ib].qh[1]])};
@ -379,7 +380,7 @@ void ggml_vec_dot_q5_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
}
int sumi = sumi0 + sumi1;
sumf += (GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d)) * sumi;
sumf += (GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d)) * sumi;
}
*s = sumf;
@ -415,12 +416,12 @@ void ggml_vec_dot_q5_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
__builtin_prefetch(x[ib].qs, 0, 1);
__builtin_prefetch(y[ib].qs, 0, 1);
vector float vxd = vec_splats(GGML_FP16_TO_FP32(x[ib].d));
vector float vyd = vec_splats(GGML_FP16_TO_FP32(y[ib].d));
vector float vxd = vec_splats(GGML_CPU_FP16_TO_FP32(x[ib].d));
vector float vyd = vec_splats(GGML_CPU_FP16_TO_FP32(y[ib].d));
vector float vd = vec_mul(vxd, vyd);
vector float vxmin = vec_splats(GGML_FP16_TO_FP32(x[ib].m));
vector float vys = {GGML_FP16_TO_FP32(y[ib].s), 0.f, 0.f, 0.f};
vector float vxmin = vec_splats(GGML_CPU_FP16_TO_FP32(x[ib].m));
vector float vys = {GGML_CPU_FP16_TO_FP32(y[ib].s), 0.f, 0.f, 0.f};
vsumf0 = vec_madd(vxmin, vys, vsumf0);
vector unsigned long long aux64x2_0 = {(uint64_t)(table_b2b_0[x[ib].qh[0]]), (uint64_t)(table_b2b_0[x[ib].qh[1]])};
@ -470,7 +471,7 @@ void ggml_vec_dot_q5_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
}
int sumi = sumi0 + sumi1;
sumf += (GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d))*sumi + GGML_FP16_TO_FP32(x[ib].m)*GGML_FP16_TO_FP32(y[ib].s);
sumf += (GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d))*sumi + GGML_CPU_FP16_TO_FP32(x[ib].m)*GGML_CPU_FP16_TO_FP32(y[ib].s);
}
*s = sumf;
@ -502,8 +503,8 @@ void ggml_vec_dot_q8_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
__builtin_prefetch(x[ib].qs, 0, 1);
__builtin_prefetch(y[ib].qs, 0, 1);
vector float vxd = vec_splats(GGML_FP16_TO_FP32(x[ib].d));
vector float vyd = vec_splats(GGML_FP16_TO_FP32(y[ib].d));
vector float vxd = vec_splats(GGML_CPU_FP16_TO_FP32(x[ib].d));
vector float vyd = vec_splats(GGML_CPU_FP16_TO_FP32(y[ib].d));
vector float vd = vec_mul(vxd, vyd);
vector signed char q8x0 = vec_xl( 0, x[ib].qs);
@ -542,7 +543,7 @@ void ggml_vec_dot_q8_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
sumi += x[ib].qs[j]*y[ib].qs[j];
}
sumf += sumi*(GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d));
sumf += sumi*(GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d));
}
*s = sumf;
@ -574,11 +575,11 @@ void ggml_vec_dot_q2_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
vector float vsumf3 = vec_splats(0.0f);
for (int i = 0; i < nb; ++i) {
vector float vxd = vec_splats(GGML_FP16_TO_FP32(x[i].d));
vector float vxd = vec_splats(GGML_CPU_FP16_TO_FP32(x[i].d));
vector float vyd = vec_splats(y[i].d);
vector float vd = vec_mul(vxd, vyd);
vector float vxmin = vec_splats(GGML_FP16_TO_FP32(x[i].dmin));
vector float vxmin = vec_splats(GGML_CPU_FP16_TO_FP32(x[i].dmin));
vector float vdmin = vec_mul(vxmin, vyd);
vector signed short q8ysums0 = vec_xl( 0, y[i].bsums);
@ -708,8 +709,8 @@ void ggml_vec_dot_q2_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
summs += y[i].bsums[j] * (sc[j] >> 4);
}
const float dall = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float dall = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
int isum = 0;
int is = 0;
@ -770,7 +771,7 @@ void ggml_vec_dot_q3_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
vector float vsumf3 = vec_splats(0.0f);
for (int i = 0; i < nb; ++i) {
vector float vxd = vec_splats(GGML_FP16_TO_FP32(x[i].d));
vector float vxd = vec_splats(GGML_CPU_FP16_TO_FP32(x[i].d));
vector float vyd = vec_splats(y[i].d);
vector float vd = vec_mul(vxd, vyd);
@ -962,7 +963,7 @@ void ggml_vec_dot_q3_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += (scales[j] - 32) * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -1005,11 +1006,11 @@ void ggml_vec_dot_q4_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
vector float vsumf3 = vec_splats(0.0f);
for (int i = 0; i < nb; ++i) {
vector float vxd = vec_splats(GGML_FP16_TO_FP32(x[i].d));
vector float vxd = vec_splats(GGML_CPU_FP16_TO_FP32(x[i].d));
vector float vyd = vec_splats(y[i].d);
vector float vd = vec_mul(vxd, vyd);
vector float vxmin = vec_splats(GGML_FP16_TO_FP32(x[i].dmin));
vector float vxmin = vec_splats(GGML_CPU_FP16_TO_FP32(x[i].dmin));
vector float vdmin = vec_mul(vxmin, vyd);
vector signed short q8ysums0 = vec_xl( 0, y[i].bsums);
@ -1177,9 +1178,9 @@ void ggml_vec_dot_q4_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
const float dmin = GGML_FP16_TO_FP32(x[i].dmin) * y[i].d;
const float dmin = GGML_CPU_FP16_TO_FP32(x[i].dmin) * y[i].d;
sumf -= dmin * sumi;
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -1222,11 +1223,11 @@ void ggml_vec_dot_q5_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
vector float vsumf3 = vec_splats(0.0f);
for (int i = 0; i < nb; ++i) {
vector float vxd = vec_splats(GGML_FP16_TO_FP32(x[i].d));
vector float vxd = vec_splats(GGML_CPU_FP16_TO_FP32(x[i].d));
vector float vyd = vec_splats(y[i].d);
vector float vd = vec_mul(vxd, vyd);
vector float vxmin = vec_splats(GGML_FP16_TO_FP32(x[i].dmin));
vector float vxmin = vec_splats(GGML_CPU_FP16_TO_FP32(x[i].dmin));
vector float vdmin = vec_mul(vxmin, vyd);
UNUSED(kmask1);
@ -1394,9 +1395,9 @@ void ggml_vec_dot_q5_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
const float dmin = GGML_FP16_TO_FP32(x[i].dmin) * y[i].d;
const float dmin = GGML_CPU_FP16_TO_FP32(x[i].dmin) * y[i].d;
sumf -= dmin * sumi;
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -1432,7 +1433,7 @@ void ggml_vec_dot_q6_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
vector float vsumf3 = vec_splats(0.0f);
for (int i = 0; i < nb; ++i) {
vector float vxd = vec_splats(GGML_FP16_TO_FP32(x[i].d));
vector float vxd = vec_splats(GGML_CPU_FP16_TO_FP32(x[i].d));
vector float vyd = vec_splats(y[i].d);
vector float vd = vec_mul(vxd, vyd);
@ -1591,7 +1592,7 @@ void ggml_vec_dot_q6_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -1659,7 +1660,7 @@ void ggml_vec_dot_iq2_xxs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const
const uint64_t * signs64 = (const uint64_t *)keven_signs_q2xs;
for (int i = 0; i < nb; ++i) {
vector float vxd = vec_splats(GGML_FP16_TO_FP32(x[i].d));
vector float vxd = vec_splats(GGML_CPU_FP16_TO_FP32(x[i].d));
vector float vyd = vec_splats(y[i].d);
vector float vd = vec_mul(vxd, vyd);
@ -1742,7 +1743,7 @@ void ggml_vec_dot_iq2_xxs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const
float sumf = 0.f;
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint16_t * GGML_RESTRICT q2 = x[i].qs;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
int32_t bsum = 0;
@ -1790,7 +1791,7 @@ void ggml_vec_dot_iq2_xs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const v
const uint64_t * signs64 = (const uint64_t *)keven_signs_q2xs;
for (int i = 0; i < nb; ++i) {
vector float vxd = vec_splats(GGML_FP16_TO_FP32(x[i].d));
vector float vxd = vec_splats(GGML_CPU_FP16_TO_FP32(x[i].d));
vector float vyd = vec_splats(y[i].d);
vector float vd = vec_mul(vxd, vyd);
@ -1871,7 +1872,7 @@ void ggml_vec_dot_iq2_xs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const v
float sumf = 0.f;
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint16_t * GGML_RESTRICT q2 = x[i].qs;
const uint8_t * GGML_RESTRICT sc = x[i].scales;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
@ -1939,7 +1940,7 @@ void ggml_vec_dot_iq2_s_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
const vector signed char mask2 = (vector signed char)vec_xl( 0, k_mask2);
for (int i = 0; i < nb; ++i) {
vector float vxd = vec_splats(GGML_FP16_TO_FP32(x[i].d));
vector float vxd = vec_splats(GGML_CPU_FP16_TO_FP32(x[i].d));
vector float vyd = vec_splats(y[i].d);
vector float vd = vec_mul(vxd, vyd);
@ -2033,7 +2034,7 @@ void ggml_vec_dot_iq2_s_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
float sumf = 0;
for (int i = 0; i < nb; i++) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const int8_t * q8 = y[i].qs;
const uint8_t * qs = x[i].qs;
const uint8_t * qh = x[i].qh;
@ -2096,7 +2097,7 @@ void ggml_vec_dot_iq3_xxs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const
vector float vsumf3 = vec_splats(0.0f);
for (int i = 0; i < nb; ++i) {
vector float vxd = vec_splats(GGML_FP16_TO_FP32(x[i].d));
vector float vxd = vec_splats(GGML_CPU_FP16_TO_FP32(x[i].d));
vector float vyd = vec_splats(y[i].d);
vector float vd = vec_mul(vxd, vyd);
@ -2176,7 +2177,7 @@ void ggml_vec_dot_iq3_xxs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const
float sumf = 0.f;
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint8_t * GGML_RESTRICT q3 = x[i].qs;
const uint8_t * GGML_RESTRICT gas = x[i].qs + QK_K/4;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
@ -2236,7 +2237,7 @@ void ggml_vec_dot_iq3_s_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
const vector signed char mask2 = (vector signed char)vec_xl( 0, k_mask2);
for (int i = 0; i < nb; ++i) {
vector float vxd = vec_splats(GGML_FP16_TO_FP32(x[i].d));
vector float vxd = vec_splats(GGML_CPU_FP16_TO_FP32(x[i].d));
vector float vyd = vec_splats(y[i].d);
vector float vd = vec_mul(vxd, vyd);
@ -2329,7 +2330,7 @@ void ggml_vec_dot_iq3_s_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
float sumf = 0.f;
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint8_t * GGML_RESTRICT qs = x[i].qs;
const uint8_t * GGML_RESTRICT qh = x[i].qh;
const uint8_t * GGML_RESTRICT signs = x[i].signs;
@ -2394,7 +2395,7 @@ void ggml_vec_dot_iq1_s_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
vector float vsumf3 = vec_splats(0.0f);
for (int i = 0; i < nb; ++i) {
vector float vxd = vec_splats(GGML_FP16_TO_FP32(x[i].d));
vector float vxd = vec_splats(GGML_CPU_FP16_TO_FP32(x[i].d));
vector float vyd = vec_splats(y[i].d);
vector float vd = vec_mul(vxd, vyd);
@ -2505,7 +2506,7 @@ void ggml_vec_dot_iq1_s_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
qs += 4;
}
sumf += GGML_FP16_TO_FP32(x[i].d) * y[i].d * (sumi + IQ1S_DELTA * sumi1);
sumf += GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d * (sumi + IQ1S_DELTA * sumi1);
}
*s = sumf;
@ -2546,8 +2547,8 @@ void ggml_vec_dot_iq4_nl_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const v
__builtin_prefetch(y[ib].qs, 0, 1);
vector float vxd = vec_splats(GGML_FP16_TO_FP32(x[ib].d));
vector float vyd = vec_splats(GGML_FP16_TO_FP32(y[ib].d));
vector float vxd = vec_splats(GGML_CPU_FP16_TO_FP32(x[ib].d));
vector float vyd = vec_splats(GGML_CPU_FP16_TO_FP32(y[ib].d));
vector float vd = vec_mul(vxd, vyd);
vector signed char qxs = (vector signed char)vec_xl( 0, x[ib].qs);
@ -2582,7 +2583,7 @@ void ggml_vec_dot_iq4_nl_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const v
#endif
for (; ib < nb; ++ib) {
const float d = GGML_FP16_TO_FP32(y[ib].d)*GGML_FP16_TO_FP32(x[ib].d);
const float d = GGML_CPU_FP16_TO_FP32(y[ib].d)*GGML_CPU_FP16_TO_FP32(x[ib].d);
int sumi1 = 0, sumi2 = 0;
for (int j = 0; j < QK4_NL/2; ++j) {
sumi1 += y[ib].qs[j+ 0] * kvalues_iq4nl[x[ib].qs[j] & 0xf];
@ -2620,7 +2621,7 @@ void ggml_vec_dot_iq4_xs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const v
for (int ibl = 0; ibl < nb; ++ibl) {
vector float vxd = vec_splats(GGML_FP16_TO_FP32(x[ibl].d));
vector float vxd = vec_splats(GGML_CPU_FP16_TO_FP32(x[ibl].d));
vector float vyd = vec_splats(y[ibl].d);
vector float vd = vec_mul(vxd, vyd);
@ -2697,7 +2698,7 @@ void ggml_vec_dot_iq4_xs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const v
#else
float sumf = 0;
for (int ibl = 0; ibl < nb; ++ibl) {
const float d4d8 = GGML_FP16_TO_FP32(x[ibl].d) * y[ibl].d;
const float d4d8 = GGML_CPU_FP16_TO_FP32(x[ibl].d) * y[ibl].d;
uint16_t h = x[ibl].scales_h;
const uint8_t * qs = x[ibl].qs;
const int8_t * q8 = y[ibl].qs;

83
ggml/src/ggml-cpu/arch/riscv/quants.c
View File

@ -3,6 +3,7 @@
#include "ggml-quants.h"
#include "ggml-impl.h"
#include "ggml-cpu.h"
#include "simd-mappings.h"
#include "../../quants.h"
#include "../../ggml-cpu-impl.h"
@ -45,7 +46,7 @@ void quantize_row_q8_0(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, i
const float d = amax / ((1 << 7) - 1);
const float id = d ? 1.0f/d : 0.0f;
y[i].d = GGML_FP32_TO_FP16(d);
y[i].d = GGML_CPU_FP32_TO_FP16(d);
vfloat32m8_t x0 = __riscv_vfmul_vf_f32m8(v_x, id, vl);
@ -85,7 +86,7 @@ void quantize_row_q8_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, i
const float d = amax / ((1 << 7) - 1);
const float id = d ? 1.0f/d : 0.0f;
y[i].d = GGML_FP32_TO_FP16(d);
y[i].d = GGML_CPU_FP32_TO_FP16(d);
vfloat32m8_t x0 = __riscv_vfmul_vf_f32m8(v_x, id, vl);
@ -102,7 +103,7 @@ void quantize_row_q8_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, i
// set y[i].s
int sum = __riscv_vmv_x_s_i16m1_i16(vwrs);
y[i].s = GGML_FP32_TO_FP16(sum*d);
y[i].s = GGML_CPU_FP32_TO_FP16(sum*d);
}
#else
@ -160,7 +161,7 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
int sumi = __riscv_vmv_x_s_i32m1_i32(vs2);
sumf += sumi*GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d);
sumf += sumi*GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d);
}
#endif
@ -177,7 +178,7 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
}
int sumi = sumi0 + sumi1;
sumf += sumi*GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d);
sumf += sumi*GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d);
}
*s = sumf;
@ -225,7 +226,7 @@ void ggml_vec_dot_q4_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
int sumi = __riscv_vmv_x_s_i32m1_i32(vs2);
sumf += (GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d))*sumi + GGML_FP16_TO_FP32(x[ib].m)*GGML_FP16_TO_FP32(y[ib].s);
sumf += (GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d))*sumi + GGML_CPU_FP16_TO_FP32(x[ib].m)*GGML_CPU_FP16_TO_FP32(y[ib].s);
}
#endif
@ -242,7 +243,7 @@ void ggml_vec_dot_q4_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
}
int sumi = sumi0 + sumi1;
sumf += (GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d))*sumi + GGML_FP16_TO_FP32(x[ib].m)*GGML_FP16_TO_FP32(y[ib].s);
sumf += (GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d))*sumi + GGML_CPU_FP16_TO_FP32(x[ib].m)*GGML_CPU_FP16_TO_FP32(y[ib].s);
}
*s = sumf;
@ -293,7 +294,7 @@ void ggml_vec_dot_q5_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
vint32m1_t sum = __riscv_vwredsum_vs_i16m4_i32m1(mul, zero, vl);
int32_t sumi = __riscv_vmv_x_s_i32m1_i32(sum);
sumf += (GGML_FP16_TO_FP32(x[ib].d) * GGML_FP16_TO_FP32(y[ib].d)) * sumi;
sumf += (GGML_CPU_FP16_TO_FP32(x[ib].d) * GGML_CPU_FP16_TO_FP32(y[ib].d)) * sumi;
}
#endif
@ -316,7 +317,7 @@ void ggml_vec_dot_q5_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
}
int sumi = sumi0 + sumi1;
sumf += (GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d)) * sumi;
sumf += (GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d)) * sumi;
}
*s = sumf;
@ -366,7 +367,7 @@ void ggml_vec_dot_q5_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
vint32m1_t sum = __riscv_vwredsum_vs_i16m4_i32m1(mul, zero, vl);
int32_t sumi = __riscv_vmv_x_s_i32m1_i32(sum);
sumf += (GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d))*sumi + GGML_FP16_TO_FP32(x[ib].m)*GGML_FP16_TO_FP32(y[ib].s);
sumf += (GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d))*sumi + GGML_CPU_FP16_TO_FP32(x[ib].m)*GGML_CPU_FP16_TO_FP32(y[ib].s);
}
#endif
@ -389,7 +390,7 @@ void ggml_vec_dot_q5_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
}
int sumi = sumi0 + sumi1;
sumf += (GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d))*sumi + GGML_FP16_TO_FP32(x[ib].m)*GGML_FP16_TO_FP32(y[ib].s);
sumf += (GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d))*sumi + GGML_CPU_FP16_TO_FP32(x[ib].m)*GGML_CPU_FP16_TO_FP32(y[ib].s);
}
*s = sumf;
@ -427,7 +428,7 @@ void ggml_vec_dot_q8_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
int sumi = __riscv_vmv_x_s_i32m1_i32(v_sum);
sumf += sumi*(GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d));
sumf += sumi*(GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d));
}
#endif
@ -438,7 +439,7 @@ void ggml_vec_dot_q8_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
sumi += x[ib].qs[j]*y[ib].qs[j];
}
sumf += sumi*(GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d));
sumf += sumi*(GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d));
}
*s = sumf;
@ -465,8 +466,8 @@ void ggml_vec_dot_q2_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
const uint8_t * q2 = x[i].qs;
const int8_t * q8 = y[i].qs;
const uint8_t * sc = x[i].scales;
const float dall = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = -y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float dall = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = -y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
uint8_t *patmp = atmp;
int vsums;
int tmp;
@ -569,8 +570,8 @@ void ggml_vec_dot_q2_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
const int8_t * q8 = y[i].qs;
const uint8_t * sc = x[i].scales;
const float dall = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = -y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float dall = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = -y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
size_t vl = 16;
@ -644,8 +645,8 @@ void ggml_vec_dot_q2_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
const uint8_t * q2 = x[i].qs;
const int8_t * q8 = y[i].qs;
const uint8_t * sc = x[i].scales;
const float dall = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = -y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float dall = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = -y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
uint8_t *patmp = atmp;
int vsums;
int tmp;
@ -750,8 +751,8 @@ void ggml_vec_dot_q2_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
summs += y[i].bsums[j] * (sc[j] >> 4);
}
const float dall = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float dall = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
int isum = 0;
int is = 0;
@ -916,7 +917,7 @@ void ggml_vec_dot_q3_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
q3 += 32; q8 += 128; scale += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
sumf += d * isum;
}
@ -1017,7 +1018,7 @@ void ggml_vec_dot_q3_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
sumf += d*sum_t;
@ -1134,7 +1135,7 @@ void ggml_vec_dot_q3_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
q3 += 32; q8 += 128; scale += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
sumf += d * isum;
}
break;
@ -1202,7 +1203,7 @@ void ggml_vec_dot_q3_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += (scales[j] - 32) * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -1239,8 +1240,8 @@ void ggml_vec_dot_q4_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
float sumf = 0;
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
int tmp, tmp2, sumi;
__asm__ __volatile__(
@ -1361,8 +1362,8 @@ void ggml_vec_dot_q4_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
size_t vl = 8;
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
vint16mf2_t q8sums_0 = __riscv_vlse16_v_i16mf2(y[i].bsums, 4, vl);
vint16mf2_t q8sums_1 = __riscv_vlse16_v_i16mf2(y[i].bsums+1, 4, vl);
@ -1422,8 +1423,8 @@ void ggml_vec_dot_q4_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
break;
case 128:
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
int tmp, tmp2, sumi;
__asm__ __volatile__(
@ -1580,9 +1581,9 @@ void ggml_vec_dot_q4_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
const float dmin = GGML_FP16_TO_FP32(x[i].dmin) * y[i].d;
const float dmin = GGML_CPU_FP16_TO_FP32(x[i].dmin) * y[i].d;
sumf -= dmin * sumi;
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -1627,8 +1628,8 @@ void ggml_vec_dot_q5_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
const uint8_t * GGML_RESTRICT hm = x[i].qh;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float dmin = GGML_FP16_TO_FP32(x[i].dmin) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const float dmin = GGML_CPU_FP16_TO_FP32(x[i].dmin) * y[i].d;
vint16m1_t q8sums_0 = __riscv_vlse16_v_i16m1(y[i].bsums, 4, vl);
vint16m1_t q8sums_1 = __riscv_vlse16_v_i16m1(y[i].bsums+1, 4, vl);
@ -1749,9 +1750,9 @@ void ggml_vec_dot_q5_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
const float dmin = GGML_FP16_TO_FP32(x[i].dmin) * y[i].d;
const float dmin = GGML_CPU_FP16_TO_FP32(x[i].dmin) * y[i].d;
sumf -= dmin * sumi;
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -1778,7 +1779,7 @@ void ggml_vec_dot_q6_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint8_t * restrict q6 = x[i].ql;
const uint8_t * restrict qh = x[i].qh;
@ -1862,7 +1863,7 @@ void ggml_vec_dot_q6_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
case 256:
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint8_t * GGML_RESTRICT q6 = x[i].ql;
const uint8_t * GGML_RESTRICT qh = x[i].qh;
@ -1943,7 +1944,7 @@ void ggml_vec_dot_q6_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
case 128:
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint8_t * restrict q6 = x[i].ql;
const uint8_t * restrict qh = x[i].qh;
@ -2058,7 +2059,7 @@ void ggml_vec_dot_q6_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
}
for (int l = 0; l < 8; ++l) sumf += sums[l];

47
ggml/src/ggml-cpu/arch/riscv/repack.cpp
View File

@ -6,6 +6,7 @@
#include "ggml-impl.h"
#include "ggml-cpu.h"
#include "ggml-cpu-impl.h"
#include "simd-mappings.h"
#include "traits.h"
#include <cmath>
@ -90,16 +91,16 @@ void ggml_gemv_q4_0_8x8_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const vo
const vfloat32m1_t facc = __riscv_vfcvt_f_x_v_f32m1(sumi_h8, vl / 4);
// vector version needs Zvfhmin extension
const float a_scale = GGML_FP16_TO_FP32(a_ptr[l].d);
const float a_scale = GGML_CPU_FP16_TO_FP32(a_ptr[l].d);
const float b_scales[8] = {
GGML_FP16_TO_FP32(b_ptr[l].d[0]),
GGML_FP16_TO_FP32(b_ptr[l].d[1]),
GGML_FP16_TO_FP32(b_ptr[l].d[2]),
GGML_FP16_TO_FP32(b_ptr[l].d[3]),
GGML_FP16_TO_FP32(b_ptr[l].d[4]),
GGML_FP16_TO_FP32(b_ptr[l].d[5]),
GGML_FP16_TO_FP32(b_ptr[l].d[6]),
GGML_FP16_TO_FP32(b_ptr[l].d[7])
GGML_CPU_FP16_TO_FP32(b_ptr[l].d[0]),
GGML_CPU_FP16_TO_FP32(b_ptr[l].d[1]),
GGML_CPU_FP16_TO_FP32(b_ptr[l].d[2]),
GGML_CPU_FP16_TO_FP32(b_ptr[l].d[3]),
GGML_CPU_FP16_TO_FP32(b_ptr[l].d[4]),
GGML_CPU_FP16_TO_FP32(b_ptr[l].d[5]),
GGML_CPU_FP16_TO_FP32(b_ptr[l].d[6]),
GGML_CPU_FP16_TO_FP32(b_ptr[l].d[7])
};
const vfloat32m1_t b_scales_vec = __riscv_vle32_v_f32m1(b_scales, vl / 4);
const vfloat32m1_t tmp1 = __riscv_vfmul_vf_f32m1(facc, a_scale, vl / 4);
@ -129,7 +130,7 @@ void ggml_gemv_q4_0_8x8_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const vo
const int v1 = (int8_t) (b_ptr[l].qs[k * ncols_interleaved * blocklen + j * blocklen + i] & 0xF0);
sumi += ((v0 * a_ptr[l].qs[k * blocklen + i]) + (v1 * a_ptr[l].qs[k * blocklen + i + qk / 2])) >> 4;
}
sumf[j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_FP16_TO_FP32(a_ptr[l].d);
sumf[j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_CPU_FP16_TO_FP32(a_ptr[l].d);
}
}
}
@ -181,20 +182,20 @@ void ggml_gemm_q4_0_8x8_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const vo
// vector version needs Zvfhmin extension
const float a_scales[4] = {
GGML_FP16_TO_FP32(a_ptr[l].d[0]),
GGML_FP16_TO_FP32(a_ptr[l].d[1]),
GGML_FP16_TO_FP32(a_ptr[l].d[2]),
GGML_FP16_TO_FP32(a_ptr[l].d[3])
GGML_CPU_FP16_TO_FP32(a_ptr[l].d[0]),
GGML_CPU_FP16_TO_FP32(a_ptr[l].d[1]),
GGML_CPU_FP16_TO_FP32(a_ptr[l].d[2]),
GGML_CPU_FP16_TO_FP32(a_ptr[l].d[3])
};
const float b_scales[8] = {
GGML_FP16_TO_FP32(b_ptr[l].d[0]),
GGML_FP16_TO_FP32(b_ptr[l].d[1]),
GGML_FP16_TO_FP32(b_ptr[l].d[2]),
GGML_FP16_TO_FP32(b_ptr[l].d[3]),
GGML_FP16_TO_FP32(b_ptr[l].d[4]),
GGML_FP16_TO_FP32(b_ptr[l].d[5]),
GGML_FP16_TO_FP32(b_ptr[l].d[6]),
GGML_FP16_TO_FP32(b_ptr[l].d[7])
GGML_CPU_FP16_TO_FP32(b_ptr[l].d[0]),
GGML_CPU_FP16_TO_FP32(b_ptr[l].d[1]),
GGML_CPU_FP16_TO_FP32(b_ptr[l].d[2]),
GGML_CPU_FP16_TO_FP32(b_ptr[l].d[3]),
GGML_CPU_FP16_TO_FP32(b_ptr[l].d[4]),
GGML_CPU_FP16_TO_FP32(b_ptr[l].d[5]),
GGML_CPU_FP16_TO_FP32(b_ptr[l].d[6]),
GGML_CPU_FP16_TO_FP32(b_ptr[l].d[7])
};
const vfloat32m1_t b_scales_vec = __riscv_vle32_v_f32m1(b_scales, vl / 4);
@ -382,7 +383,7 @@ void ggml_gemm_q4_0_8x8_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const vo
sumi += ((v0 * a_ptr[l].qs[k * 4 * blocklen + m * blocklen + i]) +
(v1 * a_ptr[l].qs[k * 4 * blocklen + m * blocklen + i + qk / 2 * 4])) >> 4;
}
sumf[m][j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_FP16_TO_FP32(a_ptr[l].d[m]);
sumf[m][j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_CPU_FP16_TO_FP32(a_ptr[l].d[m]);
}
}
}

57
ggml/src/ggml-cpu/arch/s390/quants.c
View File

@ -3,6 +3,7 @@
#include "ggml-quants.h"
#include "ggml-impl.h"
#include "ggml-cpu.h"
#include "simd-mappings.h"
#include "../../quants.h"
#include "../../ggml-cpu-impl.h"
@ -49,7 +50,7 @@ void quantize_row_q8_0(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, i
const float d = amax / ((1 << 7) - 1);
const float id = d ? 1.0f / d : 0.0f;
y[i].d = GGML_FP32_TO_FP16(d);
y[i].d = GGML_CPU_FP32_TO_FP16(d);
for (int j = 0; j < 8; j++) {
const __vector float v = vec_mul(srcv[j], vec_splats(id));
@ -94,7 +95,7 @@ void quantize_row_q8_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, i
const float d = amax / ((1 << 7) - 1);
const float id = d ? 1.0f / d : 0.0f;
y[i].d = GGML_FP32_TO_FP16(d);
y[i].d = GGML_CPU_FP32_TO_FP16(d);
__vector int32_t acc = vec_splats(0);
@ -110,7 +111,7 @@ void quantize_row_q8_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, i
acc = vec_add(acc, vi);
}
y[i].s = GGML_FP32_TO_FP16(d * (acc[0] + acc[1] + acc[2] + acc[3]));
y[i].s = GGML_CPU_FP32_TO_FP16(d * (acc[0] + acc[1] + acc[2] + acc[3]));
}
#else
GGML_UNUSED(nb);
@ -164,7 +165,7 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
__vector int16_t v_xy_ = v_xylso + v_xylse + v_xyhso + v_xyhse; v_xy_ += vec_reve(v_xy_);
const __vector float v_xy = vec_float(vec_unpackh(v_xy_));
const __vector float v_d = vec_splats(GGML_FP16_TO_FP32(x[ib].d) * GGML_FP16_TO_FP32(y[ib].d));
const __vector float v_d = vec_splats(GGML_CPU_FP16_TO_FP32(x[ib].d) * GGML_CPU_FP16_TO_FP32(y[ib].d));
acc = vec_madd(v_xy, v_d, acc);
}
@ -185,7 +186,7 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
}
int sumi = sumi0 + sumi1;
sumf += sumi*GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d);
sumf += sumi*GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d);
}
*s = sumf;
@ -219,7 +220,7 @@ void ggml_vec_dot_q4_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
__builtin_prefetch(x[ib].qs, 0, 1);
__builtin_prefetch(y[ib].qs, 0, 1);
summs += GGML_FP16_TO_FP32(x[ib].m) * GGML_FP16_TO_FP32(y[ib].s);
summs += GGML_CPU_FP16_TO_FP32(x[ib].m) * GGML_CPU_FP16_TO_FP32(y[ib].s);
const uint8x16_t v_x = vec_xl(0, x[ib].qs);
const int8x16_t v_xl = (const int8x16_t)(v_x & v_m);
@ -231,7 +232,7 @@ void ggml_vec_dot_q4_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
const int32x4_t v_xy_ = ggml_vec_dot(ggml_vec_dot(vec_splats(0), v_xl, v_yl), v_xh, v_yh);
const float32x4_t v_xy = vec_float(v_xy_);
const float32x4_t v_d = vec_splats(GGML_FP16_TO_FP32(x[ib].d) * GGML_FP16_TO_FP32(y[ib].d));
const float32x4_t v_d = vec_splats(GGML_CPU_FP16_TO_FP32(x[ib].d) * GGML_CPU_FP16_TO_FP32(y[ib].d));
acc = vec_madd(v_xy, v_d, acc);
}
@ -252,7 +253,7 @@ void ggml_vec_dot_q4_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
}
int sumi = sumi0 + sumi1;
sumf += (GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d))*sumi + GGML_FP16_TO_FP32(x[ib].m)*GGML_FP16_TO_FP32(y[ib].s);
sumf += (GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d))*sumi + GGML_CPU_FP16_TO_FP32(x[ib].m)*GGML_CPU_FP16_TO_FP32(y[ib].s);
}
*s = sumf;
@ -290,7 +291,7 @@ void ggml_vec_dot_q8_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
const int32x4_t v_xy_ = ggml_vec_dot(ggml_vec_dot(vec_splats(0), v_xl, v_yl), v_xh, v_yh);
const float32x4_t v_xy = vec_float(v_xy_);
const float32x4_t v_d = vec_splats(GGML_FP16_TO_FP32(x[ib].d) * GGML_FP16_TO_FP32(y[ib].d));
const float32x4_t v_d = vec_splats(GGML_CPU_FP16_TO_FP32(x[ib].d) * GGML_CPU_FP16_TO_FP32(y[ib].d));
acc = vec_madd(v_xy, v_d, acc);
}
@ -305,7 +306,7 @@ void ggml_vec_dot_q8_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
sumi += x[ib].qs[j]*y[ib].qs[j];
}
sumf += sumi*(GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d));
sumf += sumi*(GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d));
}
*s = sumf;
@ -348,7 +349,7 @@ void ggml_vec_dot_q3_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
float sum = 0;
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const uint8_t * restrict x0l = x[i].qs;
const uint8_t * restrict x0h = x[i].hmask;
@ -497,7 +498,7 @@ void ggml_vec_dot_q3_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += (scales[j] - 32) * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -537,8 +538,8 @@ void ggml_vec_dot_q4_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
float sumf = 0;
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
const int16x8_t v_ysumsl = vec_xl(0 , y[i].bsums);
const int16x8_t v_ysumsh = vec_xl(16, y[i].bsums);
@ -647,9 +648,9 @@ void ggml_vec_dot_q4_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
const float dmin = GGML_FP16_TO_FP32(x[i].dmin) * y[i].d;
const float dmin = GGML_CPU_FP16_TO_FP32(x[i].dmin) * y[i].d;
sumf -= dmin * sumi;
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -698,8 +699,8 @@ void ggml_vec_dot_q5_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
float sumf = 0;
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
const int16x8_t v_ysumsl = vec_xl(0 , y[i].bsums);
const int16x8_t v_ysumsh = vec_xl(16, y[i].bsums);
@ -819,9 +820,9 @@ void ggml_vec_dot_q5_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
const float dmin = GGML_FP16_TO_FP32(x[i].dmin) * y[i].d;
const float dmin = GGML_CPU_FP16_TO_FP32(x[i].dmin) * y[i].d;
sumf -= dmin * sumi;
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -859,7 +860,7 @@ void ggml_vec_dot_q6_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
int8x16_t v_y[4];
for (int i = 0; i < nb; ++i) {
const float d_all = GGML_FP16_TO_FP32(x[i].d);
const float d_all = GGML_CPU_FP16_TO_FP32(x[i].d);
const uint8_t * GGML_RESTRICT x0l = x[i].ql;
const uint8_t * GGML_RESTRICT x0h = x[i].qh;
@ -1004,7 +1005,7 @@ void ggml_vec_dot_q6_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -1071,7 +1072,7 @@ void ggml_vec_dot_q6_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
// float sumf = 0;
// for (int i = 0; i < nb; ++i) {
// const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
// const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
// const uint16_t * GGML_RESTRICT q2 = x[i].qs;
// const int8_t * GGML_RESTRICT q8 = y[i].qs;
@ -1121,7 +1122,7 @@ void ggml_vec_dot_q6_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
// float sumf = 0.f;
// for (int i = 0; i < nb; ++i) {
// const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
// const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
// const uint16_t * GGML_RESTRICT q2 = x[i].qs;
// const int8_t * GGML_RESTRICT q8 = y[i].qs;
// int32_t bsum = 0;
@ -1182,12 +1183,12 @@ void ggml_vec_dot_iq4_nl_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const v
const int8x16_t v_yh = vec_xl(QK8_0/2, y0->qs);
const int32x4_t v_xy = ggml_vec_dot(ggml_vec_dot(vec_splats(0), v_xl, v_yl), v_xh, v_yh);
sumf += GGML_FP16_TO_FP32(x0->d) * GGML_FP16_TO_FP32(y0->d) * (v_xy[0] + v_xy[1] + v_xy[2] + v_xy[3]);
sumf += GGML_CPU_FP16_TO_FP32(x0->d) * GGML_CPU_FP16_TO_FP32(y0->d) * (v_xy[0] + v_xy[1] + v_xy[2] + v_xy[3]);
}
#endif
for (; ib < nb; ++ib) {
const float d = GGML_FP16_TO_FP32(y[ib].d)*GGML_FP16_TO_FP32(x[ib].d);
const float d = GGML_CPU_FP16_TO_FP32(y[ib].d)*GGML_CPU_FP16_TO_FP32(x[ib].d);
int sumi1 = 0, sumi2 = 0;
for (int j = 0; j < QK4_NL/2; ++j) {
sumi1 += y[ib].qs[j+ 0] * kvalues_iq4nl[x[ib].qs[j] & 0xf];
@ -1257,7 +1258,7 @@ void ggml_vec_dot_iq4_xs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const v
sumi2 += (vsumi1[0] + vsumi1[1] + vsumi1[2] + vsumi1[3]) * ls2;
}
sumf += GGML_FP16_TO_FP32(x[ibl].d) * y[ibl].d * (sumi1 + sumi2);
sumf += GGML_CPU_FP16_TO_FP32(x[ibl].d) * y[ibl].d * (sumi1 + sumi2);
}
*s = sumf;
@ -1265,7 +1266,7 @@ void ggml_vec_dot_iq4_xs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const v
#else
float sumf = 0;
for (int ibl = 0; ibl < nb; ++ibl) {
const float d4d8 = GGML_FP16_TO_FP32(x[ibl].d) * y[ibl].d;
const float d4d8 = GGML_CPU_FP16_TO_FP32(x[ibl].d) * y[ibl].d;
uint16_t h = x[ibl].scales_h;
const uint8_t * qs = x[ibl].qs;
const int8_t * q8 = y[ibl].qs;

59
ggml/src/ggml-cpu/arch/wasm/quants.c
View File

@ -3,6 +3,7 @@
#include "ggml-quants.h"
#include "ggml-impl.h"
#include "ggml-cpu.h"
#include "simd-mappings.h"
#include "../../quants.h"
#include "../../ggml-cpu-impl.h"
@ -65,7 +66,7 @@ void quantize_row_q8_0(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, i
const float d = amax / ((1 << 7) - 1);
const float id = d ? 1.0f/d : 0.0f;
y[i].d = GGML_FP32_TO_FP16(d);
y[i].d = GGML_CPU_FP32_TO_FP16(d);
for (int j = 0; j < 8; j++) {
const v128_t v = wasm_f32x4_mul(srcv[j], wasm_f32x4_splat(id));
@ -110,7 +111,7 @@ void quantize_row_q8_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, i
const float d = amax / ((1 << 7) - 1);
const float id = d ? 1.0f/d : 0.0f;
y[i].d = GGML_FP32_TO_FP16(d);
y[i].d = GGML_CPU_FP32_TO_FP16(d);
v128_t accv = wasm_i32x4_splat(0);
@ -126,7 +127,7 @@ void quantize_row_q8_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, i
accv = wasm_i32x4_add(accv, vi);
}
y[i].s = GGML_FP32_TO_FP16(
y[i].s = GGML_CPU_FP32_TO_FP16(
d * (wasm_i32x4_extract_lane(accv, 0) +
wasm_i32x4_extract_lane(accv, 1) +
wasm_i32x4_extract_lane(accv, 2) +
@ -324,8 +325,8 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
);
// Accumulate results with scaling
float scale0 = GGML_FP16_TO_FP32(x0->d) * GGML_FP16_TO_FP32(y0->d);
float scale1 = GGML_FP16_TO_FP32(x1->d) * GGML_FP16_TO_FP32(y1->d);
float scale0 = GGML_CPU_FP16_TO_FP32(x0->d) * GGML_CPU_FP16_TO_FP32(y0->d);
float scale1 = GGML_CPU_FP16_TO_FP32(x1->d) * GGML_CPU_FP16_TO_FP32(y1->d);
sumv = wasm_f32x4_add(sumv, wasm_f32x4_mul(wasm_f32x4_convert_i32x4(dp0), wasm_f32x4_splat(scale0)));
sumv = wasm_f32x4_add(sumv, wasm_f32x4_mul(wasm_f32x4_convert_i32x4(dp1), wasm_f32x4_splat(scale1)));
@ -348,7 +349,7 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
}
int sumi = sumi0 + sumi1;
sumf += sumi*GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d);
sumf += sumi*GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d);
}
*s = sumf;
@ -428,7 +429,7 @@ void ggml_vec_dot_q5_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
wasm_i32x4_dot_i16x8(v0lfh, v1lh)),
wasm_i32x4_add(wasm_i32x4_dot_i16x8(v0hfl, v1hl),
wasm_i32x4_dot_i16x8(v0hfh, v1hh)))),
wasm_f32x4_splat(GGML_FP16_TO_FP32(x0->d) * GGML_FP16_TO_FP32(y0->d))));
wasm_f32x4_splat(GGML_CPU_FP16_TO_FP32(x0->d) * GGML_CPU_FP16_TO_FP32(y0->d))));
}
sumf = wasm_f32x4_extract_lane(sumv, 0) + wasm_f32x4_extract_lane(sumv, 1) +
@ -454,7 +455,7 @@ void ggml_vec_dot_q5_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
}
int sumi = sumi0 + sumi1;
sumf += (GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d)) * sumi;
sumf += (GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d)) * sumi;
}
*s = sumf;
@ -491,7 +492,7 @@ void ggml_vec_dot_q5_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
const block_q5_1 * GGML_RESTRICT x0 = &x[ib];
const block_q8_1 * GGML_RESTRICT y0 = &y[ib];
summs += GGML_FP16_TO_FP32(x0->m) * GGML_FP16_TO_FP32(y0->s);
summs += GGML_CPU_FP16_TO_FP32(x0->m) * GGML_CPU_FP16_TO_FP32(y0->s);
const v128_t m4b = wasm_i8x16_splat(0x0F);
@ -538,7 +539,7 @@ void ggml_vec_dot_q5_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
wasm_i32x4_dot_i16x8(v0lfh, v1lh)),
wasm_i32x4_add(wasm_i32x4_dot_i16x8(v0hfl, v1hl),
wasm_i32x4_dot_i16x8(v0hfh, v1hh)))),
wasm_f32x4_splat(GGML_FP16_TO_FP32(x0->d) * GGML_FP16_TO_FP32(y0->d))));
wasm_f32x4_splat(GGML_CPU_FP16_TO_FP32(x0->d) * GGML_CPU_FP16_TO_FP32(y0->d))));
}
sumf = wasm_f32x4_extract_lane(sumv, 0) + wasm_f32x4_extract_lane(sumv, 1) +
@ -564,7 +565,7 @@ void ggml_vec_dot_q5_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
}
int sumi = sumi0 + sumi1;
sumf += (GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d))*sumi + GGML_FP16_TO_FP32(x[ib].m)*GGML_FP16_TO_FP32(y[ib].s);
sumf += (GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d))*sumi + GGML_CPU_FP16_TO_FP32(x[ib].m)*GGML_CPU_FP16_TO_FP32(y[ib].s);
}
*s = sumf;
@ -620,7 +621,7 @@ void ggml_vec_dot_q8_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
const v128_t sum_dots = wasm_i32x4_add(wasm_i32x4_add(dx0_0, dx0_1), wasm_i32x4_add(dx1_0, dx1_1));
// Convert to float and accumulate
const float scale = GGML_FP16_TO_FP32(x0->d) * GGML_FP16_TO_FP32(y0->d);
const float scale = GGML_CPU_FP16_TO_FP32(x0->d) * GGML_CPU_FP16_TO_FP32(y0->d);
sumv = wasm_f32x4_add(sumv, wasm_f32x4_mul(wasm_f32x4_convert_i32x4(sum_dots), wasm_f32x4_splat(scale)));
}
@ -635,7 +636,7 @@ void ggml_vec_dot_q8_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
sumi += x[ib].qs[j]*y[ib].qs[j];
}
sumf += sumi*(GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d));
sumf += sumi*(GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d));
}
*s = sumf;
@ -746,8 +747,8 @@ void ggml_vec_dot_q2_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
isum += wasm_i32x4_extract_lane(isum_vec, 0);
}
const float dall = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float dmin = GGML_FP16_TO_FP32(x[i].dmin) * y[i].d;
const float dall = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const float dmin = GGML_CPU_FP16_TO_FP32(x[i].dmin) * y[i].d;
sumf += dall * isum - dmin * summs;
}
@ -768,8 +769,8 @@ void ggml_vec_dot_q2_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
summs += y[i].bsums[j] * (sc[j] >> 4);
}
const float dall = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float dall = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
int isum = 0;
int is = 0;
@ -880,7 +881,7 @@ void ggml_vec_dot_q3_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
}
// Accumulate results
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const v128_t v_d = wasm_f32x4_splat(d);
v128_t v_sum = wasm_f32x4_add(
wasm_f32x4_mul(wasm_f32x4_convert_i32x4(v_acc0), v_d),
@ -957,7 +958,7 @@ void ggml_vec_dot_q3_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += (scales[j] - 32) * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -991,8 +992,8 @@ void ggml_vec_dot_q4_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
float sumf = 0;
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_FP16_TO_FP32(x[i].dmin); // Corrected sign
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin); // Corrected sign
const uint8_t * GGML_RESTRICT q4 = x[i].qs;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
@ -1136,9 +1137,9 @@ void ggml_vec_dot_q4_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
const float dmin = GGML_FP16_TO_FP32(x[i].dmin) * y[i].d;
const float dmin = GGML_CPU_FP16_TO_FP32(x[i].dmin) * y[i].d;
sumf -= dmin * sumi;
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -1170,8 +1171,8 @@ void ggml_vec_dot_q5_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
float sumf = 0;
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_FP16_TO_FP32(x[i].dmin); // Fixed sign
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin); // Fixed sign
const uint8_t * GGML_RESTRICT q5 = x[i].qs;
const uint8_t * GGML_RESTRICT qh = x[i].qh;
@ -1331,9 +1332,9 @@ void ggml_vec_dot_q5_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
const float dmin = GGML_FP16_TO_FP32(x[i].dmin) * y[i].d;
const float dmin = GGML_CPU_FP16_TO_FP32(x[i].dmin) * y[i].d;
sumf -= dmin * sumi;
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -1420,7 +1421,7 @@ void ggml_vec_dot_q6_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
wasm_v128_store(&aux32[0], acc0);
wasm_v128_store(&aux32[4], acc1);
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) {
sums[l] += d * aux32[l];
}
@ -1470,7 +1471,7 @@ void ggml_vec_dot_q6_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
}
for (int l = 0; l < 8; ++l) sumf += sums[l];

165
ggml/src/ggml-cpu/arch/x86/quants.c
View File

@ -3,6 +3,7 @@
#include "ggml-quants.h"
#include "ggml-impl.h"
#include "ggml-cpu.h"
#include "simd-mappings.h"
#include "../../quants.h"
#include "../../ggml-cpu-impl.h"
@ -256,9 +257,9 @@ static inline __m256 mul_sum_i8_quad_float(const __m128i x_1_0, const __m128i x_
// quad fp16 delta calculation
static inline __m256 quad_fp16_delta_float(const float x0, const float y0, const float x1, const float y1) {
// GGML_FP16_TO_FP32 is faster than Intel F16C
return _mm256_set_m128(_mm_set1_ps(GGML_FP16_TO_FP32(x1) * GGML_FP16_TO_FP32(y1)),
_mm_set1_ps(GGML_FP16_TO_FP32(x0) * GGML_FP16_TO_FP32(y0)));
// GGML_CPU_FP16_TO_FP32 is faster than Intel F16C
return _mm256_set_m128(_mm_set1_ps(GGML_CPU_FP16_TO_FP32(x1) * GGML_CPU_FP16_TO_FP32(y1)),
_mm_set1_ps(GGML_CPU_FP16_TO_FP32(x0) * GGML_CPU_FP16_TO_FP32(y0)));
}
#endif
#elif defined(__SSSE3__)
@ -305,7 +306,7 @@ void quantize_row_q8_0(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, i
// Quantize these floats
const float d = maxScalar / 127.f;
y[i].d = GGML_FP32_TO_FP16(d);
y[i].d = GGML_CPU_FP32_TO_FP16(d);
const float id = ( maxScalar != 0.0f ) ? 127.f / maxScalar : 0.0f;
const __m256 mul = _mm256_set1_ps( id );
@ -401,7 +402,7 @@ void quantize_row_q8_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, i
// Quantize these floats
const float d = max_scalar / 127.f;
y[i].d = GGML_FP32_TO_FP16(d);
y[i].d = GGML_CPU_FP32_TO_FP16(d);
const float id = ( max_scalar != 0.0f ) ? 127.f / max_scalar : 0.0f;
const __m256 mul = _mm256_set1_ps( id );
@ -425,7 +426,7 @@ void quantize_row_q8_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, i
#if defined(__AVX2__)
// Compute the sum of the quants and set y[i].s
y[i].s = GGML_FP32_TO_FP16(d * hsum_i32_8(_mm256_add_epi32(_mm256_add_epi32(i0, i1), _mm256_add_epi32(i2, i3))));
y[i].s = GGML_CPU_FP32_TO_FP16(d * hsum_i32_8(_mm256_add_epi32(_mm256_add_epi32(i0, i1), _mm256_add_epi32(i2, i3))));
// Convert int32 to int16
i0 = _mm256_packs_epi32( i0, i1 ); // 0, 1, 2, 3, 8, 9, 10, 11, 4, 5, 6, 7, 12, 13, 14, 15
@ -455,7 +456,7 @@ void quantize_row_q8_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, i
// Compute the sum of the quants and set y[i].s
const __m128i s0 = _mm_add_epi32(_mm_add_epi32(ni0, ni1), _mm_add_epi32(ni2, ni3));
const __m128i s1 = _mm_add_epi32(_mm_add_epi32(ni4, ni5), _mm_add_epi32(ni6, ni7));
y[i].s = GGML_FP32_TO_FP16(d * hsum_i32_4(_mm_add_epi32(s0, s1)));
y[i].s = GGML_CPU_FP32_TO_FP16(d * hsum_i32_4(_mm_add_epi32(s0, s1)));
// Convert int32 to int16
ni0 = _mm_packs_epi32( ni0, ni1 );
@ -552,7 +553,7 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
// Main loop
for (; ib < nb; ++ib) {
/* Compute combined scale for the block */
const __m256 d = _mm256_set1_ps( GGML_FP16_TO_FP32(x[ib].d) * GGML_FP16_TO_FP32(y[ib].d) );
const __m256 d = _mm256_set1_ps( GGML_CPU_FP16_TO_FP32(x[ib].d) * GGML_CPU_FP16_TO_FP32(y[ib].d) );
__m256i qx = bytes_from_nibbles_32(x[ib].qs);
@ -613,7 +614,7 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
_mm_prefetch(&y[ib] + sizeof(block_q8_0), _MM_HINT_T0);
// Compute combined scale for the block 0 and 1
const __m128 d_0_1 = _mm_set1_ps( GGML_FP16_TO_FP32(x[ib].d) * GGML_FP16_TO_FP32(y[ib].d) );
const __m128 d_0_1 = _mm_set1_ps( GGML_CPU_FP16_TO_FP32(x[ib].d) * GGML_CPU_FP16_TO_FP32(y[ib].d) );
const __m128i tmp_0_1 = _mm_loadu_si128((const __m128i *)x[ib].qs);
@ -631,7 +632,7 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
_mm_prefetch(&y[ib] + 2 * sizeof(block_q8_0), _MM_HINT_T0);
// Compute combined scale for the block 2 and 3
const __m128 d_2_3 = _mm_set1_ps( GGML_FP16_TO_FP32(x[ib + 1].d) * GGML_FP16_TO_FP32(y[ib + 1].d) );
const __m128 d_2_3 = _mm_set1_ps( GGML_CPU_FP16_TO_FP32(x[ib + 1].d) * GGML_CPU_FP16_TO_FP32(y[ib + 1].d) );
const __m128i tmp_2_3 = _mm_loadu_si128((const __m128i *)x[ib + 1].qs);
@ -680,7 +681,7 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
}
int sumi = sumi0 + sumi1;
sumf += sumi*GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d);
sumf += sumi*GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d);
}
*s = sumf;
@ -711,10 +712,10 @@ void ggml_vec_dot_q4_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
// Main loop
for (; ib < nb; ++ib) {
const float d0 = GGML_FP16_TO_FP32(x[ib].d);
const float d1 = GGML_FP16_TO_FP32(y[ib].d);
const float d0 = GGML_CPU_FP16_TO_FP32(x[ib].d);
const float d1 = GGML_CPU_FP16_TO_FP32(y[ib].d);
summs += GGML_FP16_TO_FP32(x[ib].m) * GGML_FP16_TO_FP32(y[ib].s);
summs += GGML_CPU_FP16_TO_FP32(x[ib].m) * GGML_CPU_FP16_TO_FP32(y[ib].s);
const __m256 d0v = _mm256_set1_ps( d0 );
const __m256 d1v = _mm256_set1_ps( d1 );
@ -752,7 +753,7 @@ void ggml_vec_dot_q4_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
}
int sumi = sumi0 + sumi1;
sumf += (GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d))*sumi + GGML_FP16_TO_FP32(x[ib].m)*GGML_FP16_TO_FP32(y[ib].s);
sumf += (GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d))*sumi + GGML_CPU_FP16_TO_FP32(x[ib].m)*GGML_CPU_FP16_TO_FP32(y[ib].s);
}
*s = sumf;
@ -783,7 +784,7 @@ void ggml_vec_dot_q5_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
// Main loop
for (; ib < nb; ++ib) {
/* Compute combined scale for the block */
const __m256 d = _mm256_set1_ps(GGML_FP16_TO_FP32(x[ib].d) * GGML_FP16_TO_FP32(y[ib].d));
const __m256 d = _mm256_set1_ps(GGML_CPU_FP16_TO_FP32(x[ib].d) * GGML_CPU_FP16_TO_FP32(y[ib].d));
__m256i qx = bytes_from_nibbles_32(x[ib].qs);
__m256i bxhi = bytes_from_bits_32(x[ib].qh);
@ -807,7 +808,7 @@ void ggml_vec_dot_q5_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
// Main loop
for (; ib < nb; ++ib) {
/* Compute combined scale for the block */
const __m256 d = _mm256_set1_ps(GGML_FP16_TO_FP32(x[ib].d) * GGML_FP16_TO_FP32(y[ib].d));
const __m256 d = _mm256_set1_ps(GGML_CPU_FP16_TO_FP32(x[ib].d) * GGML_CPU_FP16_TO_FP32(y[ib].d));
__m256i bx_0 = bytes_from_nibbles_32(x[ib].qs);
const __m256i bxhi = bytes_from_bits_32(x[ib].qh);
@ -851,7 +852,7 @@ void ggml_vec_dot_q5_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
}
int sumi = sumi0 + sumi1;
sumf += (GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d)) * sumi;
sumf += (GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d)) * sumi;
}
*s = sumf;
@ -883,16 +884,16 @@ void ggml_vec_dot_q5_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
// Main loop
for (; ib < nb; ++ib) {
const __m256 dx = _mm256_set1_ps(GGML_FP16_TO_FP32(x[ib].d));
const __m256 dx = _mm256_set1_ps(GGML_CPU_FP16_TO_FP32(x[ib].d));
summs += GGML_FP16_TO_FP32(x[ib].m) * GGML_FP16_TO_FP32(y[ib].s);
summs += GGML_CPU_FP16_TO_FP32(x[ib].m) * GGML_CPU_FP16_TO_FP32(y[ib].s);
__m256i qx = bytes_from_nibbles_32(x[ib].qs);
__m256i bxhi = bytes_from_bits_32(x[ib].qh);
bxhi = _mm256_and_si256(bxhi, _mm256_set1_epi8(0x10));
qx = _mm256_or_si256(qx, bxhi);
const __m256 dy = _mm256_set1_ps(GGML_FP16_TO_FP32(y[ib].d));
const __m256 dy = _mm256_set1_ps(GGML_CPU_FP16_TO_FP32(y[ib].d));
const __m256i qy = _mm256_loadu_si256((const __m256i *)y[ib].qs);
const __m256 q = mul_sum_us8_pairs_float(qx, qy);
@ -910,9 +911,9 @@ void ggml_vec_dot_q5_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
// Main loop
for (; ib < nb; ++ib) {
const __m256 dx = _mm256_set1_ps(GGML_FP16_TO_FP32(x[ib].d));
const __m256 dx = _mm256_set1_ps(GGML_CPU_FP16_TO_FP32(x[ib].d));
summs += GGML_FP16_TO_FP32(x[ib].m) * GGML_FP16_TO_FP32(y[ib].s);
summs += GGML_CPU_FP16_TO_FP32(x[ib].m) * GGML_CPU_FP16_TO_FP32(y[ib].s);
__m256i bx_0 = bytes_from_nibbles_32(x[ib].qs);
const __m256i bxhi = bytes_from_bits_32(x[ib].qh);
@ -926,7 +927,7 @@ void ggml_vec_dot_q5_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
bxh = _mm_or_si128(bxh, bxhih);
bx_0 = MM256_SET_M128I(bxh, bxl);
const __m256 dy = _mm256_set1_ps(GGML_FP16_TO_FP32(y[ib].d));
const __m256 dy = _mm256_set1_ps(GGML_CPU_FP16_TO_FP32(y[ib].d));
const __m256i by_0 = _mm256_loadu_si256((const __m256i *)y[ib].qs);
const __m256 q = mul_sum_us8_pairs_float(bx_0, by_0);
@ -956,7 +957,7 @@ void ggml_vec_dot_q5_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const voi
}
int sumi = sumi0 + sumi1;
sumf += (GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d))*sumi + GGML_FP16_TO_FP32(x[ib].m)*GGML_FP16_TO_FP32(y[ib].s);
sumf += (GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d))*sumi + GGML_CPU_FP16_TO_FP32(x[ib].m)*GGML_CPU_FP16_TO_FP32(y[ib].s);
}
*s = sumf;
@ -986,7 +987,7 @@ void ggml_vec_dot_q8_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
// Main loop
for (; ib < nb; ++ib) {
// Compute combined scale for the block
const __m256 d = _mm256_set1_ps(GGML_FP16_TO_FP32(x[ib].d) * GGML_FP16_TO_FP32(y[ib].d));
const __m256 d = _mm256_set1_ps(GGML_CPU_FP16_TO_FP32(x[ib].d) * GGML_CPU_FP16_TO_FP32(y[ib].d));
__m256i qx = _mm256_loadu_si256((const __m256i *)x[ib].qs);
__m256i qy = _mm256_loadu_si256((const __m256i *)y[ib].qs);
@ -1025,7 +1026,7 @@ void ggml_vec_dot_q8_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const voi
sumi += x[ib].qs[j]*y[ib].qs[j];
}
sumf += sumi*(GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d));
sumf += sumi*(GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d));
}
*s = sumf;
@ -1144,7 +1145,7 @@ void ggml_vec_dot_tq1_0_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
}
const __m256i ysum = _mm256_loadu_si256((const __m256i *) y[i].bsums);
const __m256 d = _mm256_set1_ps(y[i].d * GGML_FP16_TO_FP32(x[i].d));
const __m256 d = _mm256_set1_ps(y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d));
sumi0 = _mm256_sub_epi16(sumi0, ysum);
sumi0 = _mm256_add_epi16(sumi0, _mm256_add_epi16(sumi1, sumi2));
@ -1190,7 +1191,7 @@ void ggml_vec_dot_tq1_0_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
}
}
sumf += (float) sum * (GGML_FP16_TO_FP32(x[i].d) * y[i].d);
sumf += (float) sum * (GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d);
}
*s = sumf;
@ -1244,7 +1245,7 @@ void ggml_vec_dot_tq2_0_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
}
const __m256i ysum = _mm256_loadu_si256((const __m256i *) y[i].bsums);
const __m256 d = _mm256_set1_ps(y[i].d * GGML_FP16_TO_FP32(x[i].d));
const __m256 d = _mm256_set1_ps(y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d));
sumi0 = _mm256_add_epi16(sumi0, sumi1);
sumi0 = _mm256_sub_epi16(sumi0, ysum);
@ -1269,7 +1270,7 @@ void ggml_vec_dot_tq2_0_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
}
}
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
sumf += (float) sumi * d;
}
@ -1299,8 +1300,8 @@ void ggml_vec_dot_q2_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = -y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = -y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
const uint8_t * GGML_RESTRICT q2 = x[i].qs;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
@ -1366,8 +1367,8 @@ void ggml_vec_dot_q2_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int i = 0; i < nb; ++i) {
const float dall = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = -y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float dall = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = -y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
const uint8_t * GGML_RESTRICT q2 = x[i].qs;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
@ -1477,8 +1478,8 @@ void ggml_vec_dot_q2_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
summs += y[i].bsums[j] * (sc[j] >> 4);
}
const float dall = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float dall = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
int isum = 0;
int is = 0;
@ -1533,7 +1534,7 @@ void ggml_vec_dot_q3_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const uint8_t * GGML_RESTRICT q3 = x[i].qs;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
@ -1638,7 +1639,7 @@ void ggml_vec_dot_q3_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const uint8_t * GGML_RESTRICT q3 = x[i].qs;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
@ -1824,7 +1825,7 @@ void ggml_vec_dot_q3_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += (scales[j] - 32) * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -1862,8 +1863,8 @@ void ggml_vec_dot_q4_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = -y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = -y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
memcpy(utmp, x[i].scales, 12);
utmp[3] = ((utmp[2] >> 4) & kmask2) | (((utmp[1] >> 6) & kmask3) << 4);
@ -1928,8 +1929,8 @@ void ggml_vec_dot_q4_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = -y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = -y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
const uint8_t * GGML_RESTRICT q4 = x[i].qs;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
@ -2049,9 +2050,9 @@ void ggml_vec_dot_q4_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
const float dmin = GGML_FP16_TO_FP32(x[i].dmin) * y[i].d;
const float dmin = GGML_CPU_FP16_TO_FP32(x[i].dmin) * y[i].d;
sumf -= dmin * sumi;
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -2092,8 +2093,8 @@ void ggml_vec_dot_q5_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
const uint8_t * GGML_RESTRICT q5 = x[i].qs;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = -y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = -y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
memcpy(utmp, x[i].scales, 12);
utmp[3] = ((utmp[2] >> 4) & kmask2) | (((utmp[1] >> 6) & kmask3) << 4);
@ -2170,8 +2171,8 @@ void ggml_vec_dot_q5_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = -y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = -y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
const uint8_t * GGML_RESTRICT q5 = x[i].qs;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
@ -2311,9 +2312,9 @@ void ggml_vec_dot_q5_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
const float dmin = GGML_FP16_TO_FP32(x[i].dmin) * y[i].d;
const float dmin = GGML_CPU_FP16_TO_FP32(x[i].dmin) * y[i].d;
sumf -= dmin * sumi;
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -2344,7 +2345,7 @@ void ggml_vec_dot_q6_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const uint8_t * GGML_RESTRICT q4 = x[i].ql;
const uint8_t * GGML_RESTRICT qh = x[i].qh;
@ -2422,7 +2423,7 @@ void ggml_vec_dot_q6_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const uint8_t * GGML_RESTRICT q4 = x[i].ql;
const uint8_t * GGML_RESTRICT qh = x[i].qh;
@ -2555,7 +2556,7 @@ void ggml_vec_dot_q6_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const voi
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -2622,7 +2623,7 @@ void ggml_vec_dot_iq2_xxs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const
__m256 accumf = _mm256_setzero_ps();
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint16_t * GGML_RESTRICT q2 = x[i].qs;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
__m256i sumi1 = _mm256_setzero_si256();
@ -2663,7 +2664,7 @@ void ggml_vec_dot_iq2_xxs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const
__m256 accumf = _mm256_setzero_ps();
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint16_t * GGML_RESTRICT q2 = x[i].qs;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
__m128i sumi1_0 = _mm_setzero_si128();
@ -2717,7 +2718,7 @@ void ggml_vec_dot_iq2_xxs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const
float sumf = 0.f;
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint16_t * GGML_RESTRICT q2 = x[i].qs;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
int32_t bsum = 0;
@ -2792,7 +2793,7 @@ void ggml_vec_dot_iq2_xs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const v
__m256 accumf = _mm256_setzero_ps();
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint16_t * GGML_RESTRICT q2 = x[i].qs;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
@ -2913,7 +2914,7 @@ void ggml_vec_dot_iq2_xs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const v
__m256 accumf = _mm256_setzero_ps();
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint16_t * GGML_RESTRICT q2 = x[i].qs;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
@ -3035,7 +3036,7 @@ void ggml_vec_dot_iq2_xs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const v
float sumf = 0.f;
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint16_t * GGML_RESTRICT q2 = x[i].qs;
const uint8_t * GGML_RESTRICT sc = x[i].scales;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
@ -3104,7 +3105,7 @@ void ggml_vec_dot_iq2_s_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
__m256 accumf = _mm256_setzero_ps();
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint8_t * GGML_RESTRICT qs = x[i].qs;
const uint8_t * GGML_RESTRICT qh = x[i].qh;
const uint16_t * GGML_RESTRICT signs = (const uint16_t *)(x[i].qs + QK_K/8);
@ -3177,7 +3178,7 @@ void ggml_vec_dot_iq2_s_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
__m256 accumf = _mm256_setzero_ps();
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint8_t * GGML_RESTRICT qs = x[i].qs;
const uint8_t * GGML_RESTRICT qh = x[i].qh;
const uint16_t * GGML_RESTRICT signs = (const uint16_t *)(x[i].qs + QK_K/8);
@ -3253,7 +3254,7 @@ void ggml_vec_dot_iq2_s_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
float sumf = 0;
for (int i = 0; i < nb; i++) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const int8_t * q8 = y[i].qs;
const uint8_t * qs = x[i].qs;
const uint8_t * qh = x[i].qh;
@ -3313,7 +3314,7 @@ void ggml_vec_dot_iq3_xxs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const
__m256 accumf = _mm256_setzero_ps();
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint8_t * GGML_RESTRICT q3 = x[i].qs;
const uint8_t * GGML_RESTRICT gas = x[i].qs + QK_K/4;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
@ -3358,7 +3359,7 @@ void ggml_vec_dot_iq3_xxs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const
__m256 accumf = _mm256_setzero_ps();
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint8_t * GGML_RESTRICT q3 = x[i].qs;
const uint8_t * GGML_RESTRICT gas = x[i].qs + QK_K/4;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
@ -3414,7 +3415,7 @@ void ggml_vec_dot_iq3_xxs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const
float sumf = 0.f;
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint8_t * GGML_RESTRICT q3 = x[i].qs;
const uint8_t * GGML_RESTRICT gas = x[i].qs + QK_K/4;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
@ -3480,7 +3481,7 @@ void ggml_vec_dot_iq3_s_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
__m256 accumf = _mm256_setzero_ps();
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint8_t * GGML_RESTRICT qs = x[i].qs;
const uint8_t * GGML_RESTRICT qh = x[i].qh;
const uint16_t * GGML_RESTRICT signs = (const uint16_t *)x[i].signs;
@ -3565,7 +3566,7 @@ void ggml_vec_dot_iq3_s_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
__m256 accumf = _mm256_setzero_ps();
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint8_t * GGML_RESTRICT qs = x[i].qs;
const uint8_t * GGML_RESTRICT qh = x[i].qh;
const uint16_t * GGML_RESTRICT signs = (const uint16_t *)x[i].signs;
@ -3648,7 +3649,7 @@ void ggml_vec_dot_iq3_s_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
float sumf = 0.f;
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint8_t * GGML_RESTRICT qs = x[i].qs;
const uint8_t * GGML_RESTRICT qh = x[i].qh;
const uint8_t * GGML_RESTRICT signs = x[i].signs;
@ -3753,7 +3754,7 @@ void ggml_vec_dot_iq1_s_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
+ (y[i].bsums[2*ib+2] + y[i].bsums[2*ib+3]) * (qh[ib+1] & 0x8000 ? -1 : 1) * ls2;
}
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
accum = _mm256_fmadd_ps(_mm256_set1_ps(d), _mm256_cvtepi32_ps(sumi), accum);
accum1 += d * sumi1;
@ -3801,7 +3802,7 @@ void ggml_vec_dot_iq1_s_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
+ (y[i].bsums[2*ib+2] + y[i].bsums[2*ib+3]) * (qh[ib+1] & 0x8000 ? -1 : 1) * ls2;
}
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
accum = _mm256_add_ps(_mm256_mul_ps(_mm256_set1_ps(d), _mm256_cvtepi32_ps(MM256_SET_M128I(sumi1_1, sumi1_0))), accum);
accum1 += d * sumi1;
@ -3835,7 +3836,7 @@ void ggml_vec_dot_iq1_s_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
qs += 4;
}
sumf += GGML_FP16_TO_FP32(x[i].d) * y[i].d * (sumi + IQ1S_DELTA * sumi1);
sumf += GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d * (sumi + IQ1S_DELTA * sumi1);
}
*s = sumf;
@ -3947,7 +3948,7 @@ void ggml_vec_dot_iq1_m_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
qs += 8; qh += 4;
}
const __m256 d = _mm256_set1_ps(y[i].d * GGML_FP16_TO_FP32(scale.f16));
const __m256 d = _mm256_set1_ps(y[i].d * GGML_CPU_FP16_TO_FP32(scale.f16));
accum1 = _mm256_fmadd_ps(d, _mm256_cvtepi32_ps(sumi1), accum1);
accum2 = _mm256_fmadd_ps(d, _mm256_cvtepi32_ps(sumi2), accum2);
@ -4033,7 +4034,7 @@ void ggml_vec_dot_iq1_m_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
qs += 8; qh += 4;
}
const __m256 d = _mm256_set1_ps(y[i].d * GGML_FP16_TO_FP32(scale.f16));
const __m256 d = _mm256_set1_ps(y[i].d * GGML_CPU_FP16_TO_FP32(scale.f16));
accum1 = _mm256_add_ps(_mm256_mul_ps(d, _mm256_cvtepi32_ps(MM256_SET_M128I(sumi1_1, sumi1_0))), accum1);
accum2 = _mm256_add_ps(_mm256_mul_ps(d, _mm256_cvtepi32_ps(MM256_SET_M128I(sumi2_1, sumi2_0))), accum2);
@ -4083,7 +4084,7 @@ void ggml_vec_dot_iq1_m_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
qh += 2;
}
sumf += GGML_FP16_TO_FP32(scale.f16) * y[i].d * (sumi1 + IQ1M_DELTA * sumi2);
sumf += GGML_CPU_FP16_TO_FP32(scale.f16) * y[i].d * (sumi1 + IQ1M_DELTA * sumi2);
}
*s = sumf;
@ -4129,9 +4130,9 @@ void ggml_vec_dot_iq4_nl_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const v
const __m256i p16_2 = mul_add_epi8(q4b_2, q8b_2);
const __m256i p_1 = _mm256_madd_epi16(p16_1, mone);
const __m256i p_2 = _mm256_madd_epi16(p16_2, mone);
accum1 = _mm256_fmadd_ps(_mm256_set1_ps(GGML_FP16_TO_FP32(y[ib + 0].d)*GGML_FP16_TO_FP32(x[ib + 0].d)),
accum1 = _mm256_fmadd_ps(_mm256_set1_ps(GGML_CPU_FP16_TO_FP32(y[ib + 0].d)*GGML_CPU_FP16_TO_FP32(x[ib + 0].d)),
_mm256_cvtepi32_ps(p_1), accum1);
accum2 = _mm256_fmadd_ps(_mm256_set1_ps(GGML_FP16_TO_FP32(y[ib + 1].d)*GGML_FP16_TO_FP32(x[ib + 1].d)),
accum2 = _mm256_fmadd_ps(_mm256_set1_ps(GGML_CPU_FP16_TO_FP32(y[ib + 1].d)*GGML_CPU_FP16_TO_FP32(x[ib + 1].d)),
_mm256_cvtepi32_ps(p_2), accum2);
}
@ -4164,7 +4165,7 @@ void ggml_vec_dot_iq4_nl_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const v
#endif
for (; ib < nb; ++ib) {
const float d = GGML_FP16_TO_FP32(y[ib].d)*GGML_FP16_TO_FP32(x[ib].d);
const float d = GGML_CPU_FP16_TO_FP32(y[ib].d)*GGML_CPU_FP16_TO_FP32(x[ib].d);
int sumi1 = 0, sumi2 = 0;
for (int j = 0; j < QK4_NL/2; ++j) {
sumi1 += y[ib].qs[j+ 0] * kvalues_iq4nl[x[ib].qs[j] & 0xf];
@ -4219,7 +4220,7 @@ void ggml_vec_dot_iq4_xs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const v
sumi1 = _mm256_add_epi32(p_1, sumi1);
sumi2 = _mm256_add_epi32(p_2, sumi2);
}
accum = _mm256_fmadd_ps(_mm256_set1_ps(GGML_FP16_TO_FP32(x[ibl].d)*y[ibl].d),
accum = _mm256_fmadd_ps(_mm256_set1_ps(GGML_CPU_FP16_TO_FP32(x[ibl].d)*y[ibl].d),
_mm256_cvtepi32_ps(_mm256_add_epi32(sumi1, sumi2)), accum);
}
@ -4267,7 +4268,7 @@ void ggml_vec_dot_iq4_xs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const v
}
__m128i sumi12_0 = _mm_add_epi32(sumi1_0, sumi2_0);
__m128i sumi12_1 = _mm_add_epi32(sumi1_1, sumi2_1);
accum = _mm256_add_ps(_mm256_mul_ps(_mm256_set1_ps(GGML_FP16_TO_FP32(x[ibl].d)*y[ibl].d),
accum = _mm256_add_ps(_mm256_mul_ps(_mm256_set1_ps(GGML_CPU_FP16_TO_FP32(x[ibl].d)*y[ibl].d),
_mm256_cvtepi32_ps(MM256_SET_M128I(sumi12_1, sumi12_0))), accum);
}
@ -4276,7 +4277,7 @@ void ggml_vec_dot_iq4_xs_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const v
#else
float sumf = 0;
for (int ibl = 0; ibl < nb; ++ibl) {
const float d4d8 = GGML_FP16_TO_FP32(x[ibl].d) * y[ibl].d;
const float d4d8 = GGML_CPU_FP16_TO_FP32(x[ibl].d) * y[ibl].d;
uint16_t h = x[ibl].scales_h;
const uint8_t * qs = x[ibl].qs;
const int8_t * q8 = y[ibl].qs;

39
ggml/src/ggml-cpu/arch/x86/repack.cpp
View File

@ -6,6 +6,7 @@
#include "ggml-impl.h"
#include "ggml-cpu.h"
#include "ggml-cpu-impl.h"
#include "simd-mappings.h"
#include "traits.h"
#include <cmath>
@ -39,11 +40,11 @@ static inline __m512 __avx512_f32cx8x2_load(ggml_fp16_t *x, ggml_fp16_t *y) {
float tmp[16];
for (int i = 0; i < 8; i++) {
tmp[i] = GGML_FP16_TO_FP32(x[i]);
tmp[i] = GGML_CPU_FP16_TO_FP32(x[i]);
}
for (int i = 0; i < 8; i++) {
tmp[i + 8] = GGML_FP16_TO_FP32(y[i]);
tmp[i + 8] = GGML_CPU_FP16_TO_FP32(y[i]);
}
return _mm512_loadu_ps(tmp);
@ -54,10 +55,10 @@ static inline __m512 __avx512_repeat_f32cx16_load(__m128i x) {
_mm_storeu_si128((__m128i*)tmphalf, x);
for (int i = 0; i < 4; i++) {
tmp[i] = GGML_FP16_TO_FP32(tmphalf[i]);
tmp[i + 4] = GGML_FP16_TO_FP32(tmphalf[i]);
tmp[i + 8] = GGML_FP16_TO_FP32(tmphalf[i]);
tmp[i + 12] = GGML_FP16_TO_FP32(tmphalf[i]);
tmp[i] = GGML_CPU_FP16_TO_FP32(tmphalf[i]);
tmp[i + 4] = GGML_CPU_FP16_TO_FP32(tmphalf[i]);
tmp[i + 8] = GGML_CPU_FP16_TO_FP32(tmphalf[i]);
tmp[i + 12] = GGML_CPU_FP16_TO_FP32(tmphalf[i]);
}
return _mm512_loadu_ps(tmp);
@ -67,7 +68,7 @@ static inline __m256 __avx_f32cx8_load(ggml_fp16_t *x) {
float tmp[8];
for (int i = 0; i < 8; i++) {
tmp[i] = GGML_FP16_TO_FP32(x[i]);
tmp[i] = GGML_CPU_FP16_TO_FP32(x[i]);
}
return _mm256_loadu_ps(tmp);
@ -76,8 +77,8 @@ static inline __m256 __avx_repeat_f32cx8_load(ggml_fp16_t *x) {
float tmp[8];
for (int i = 0; i < 4; i++) {
tmp[i] = GGML_FP16_TO_FP32(x[i]);
tmp[i + 4] = GGML_FP16_TO_FP32(x[i]);
tmp[i] = GGML_CPU_FP16_TO_FP32(x[i]);
tmp[i + 4] = GGML_CPU_FP16_TO_FP32(x[i]);
}
return _mm256_loadu_ps(tmp);
@ -88,7 +89,7 @@ static inline __m256 __avx_rearranged_f32cx8_load(ggml_fp16_t *x, __m128i arrang
_mm_storeu_si128((__m128i*)tmphalf, _mm_shuffle_epi8(_mm_loadu_si128((const __m128i *) x), arrangeMask));
for (int i = 0; i < 8; i++) {
tmp[i] = GGML_FP16_TO_FP32(tmphalf[i]);
tmp[i] = GGML_CPU_FP16_TO_FP32(tmphalf[i]);
}
return _mm256_loadu_ps(tmp);
@ -211,7 +212,7 @@ void ggml_quantize_mat_q8_0_4x8(const float * GGML_RESTRICT x, void * GGML_RESTR
id[row_iter] = ( maxScalar != 0.0f ) ? 127.f / maxScalar : 0.0f; //d ? 1.0f / d : 0.0f;
// Store the scale for the individual block
y[i].d[row_iter] = GGML_FP32_TO_FP16(d);
y[i].d[row_iter] = GGML_CPU_FP32_TO_FP16(d);
// Store the values in blocks of eight values - Aim is to use these later for block interleaving
srcv[row_iter][0] = v0;
@ -297,7 +298,7 @@ void ggml_quantize_mat_q8_0_4x8(const float * GGML_RESTRICT x, void * GGML_RESTR
const float d = amax / ((1 << 7) - 1);
id[row_iter] = d ? 1.0f / d : 0.0f;
y[i].d[row_iter] = GGML_FP32_TO_FP16(d);
y[i].d[row_iter] = GGML_CPU_FP32_TO_FP16(d);
}
for (int j = 0; j < QK8_0 * 4; j++) {
@ -647,7 +648,7 @@ void ggml_gemv_q4_0_8x8_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const vo
const __m256 col_scale_f32 = GGML_F32Cx8_REARRANGE_LOAD(b_ptr[b].d, changemask);
// Load and convert to FP32 scale from block_q8_0
const __m256 row_scale_f32 = _mm256_set1_ps(GGML_FP16_TO_FP32(a_ptr[b].d));
const __m256 row_scale_f32 = _mm256_set1_ps(GGML_CPU_FP16_TO_FP32(a_ptr[b].d));
// Load the block values in block_q8_0 in batches of 16 bytes and replicate the same across 256 bit vector
__m256i lhs_vec_0 = _mm256_castsi128_si256(_mm_loadu_si128((const __m128i *)a_ptr[b].qs));
@ -706,7 +707,7 @@ void ggml_gemv_q4_0_8x8_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const vo
const int v1 = (int8_t) (b_ptr[l].qs[k * ncols_interleaved * blocklen + j * blocklen + i] & 0xF0);
sumi += ((v0 * a_ptr[l].qs[k * blocklen + i]) + (v1 * a_ptr[l].qs[k * blocklen + i + qk / 2])) >> 4;
}
sumf[j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_FP16_TO_FP32(a_ptr[l].d);
sumf[j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_CPU_FP16_TO_FP32(a_ptr[l].d);
}
}
}
@ -972,13 +973,13 @@ void ggml_gemv_q4_K_8x8_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
sumi2 = sumi2 * scales_1[j];
sumi += sumi1 + sumi2;
}
sumf[j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * a_ptr[l].d;
sumf[j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * a_ptr[l].d;
}
}
for (int sb = 0; sb < 8; sb++) {
uint8_t *mins = (uint8_t*) utmp + 8 + sb * 16;
for (int j = 0; j < ncols_interleaved; j++) {
sum_minf[j] += mins[j] * (a_ptr[l].bsums[sb * 2] + a_ptr[l].bsums[sb * 2 + 1]) * GGML_FP16_TO_FP32(b_ptr[l].dmin[j]) * a_ptr[l].d;
sum_minf[j] += mins[j] * (a_ptr[l].bsums[sb * 2] + a_ptr[l].bsums[sb * 2 + 1]) * GGML_CPU_FP16_TO_FP32(b_ptr[l].dmin[j]) * a_ptr[l].d;
}
}
}
@ -1755,7 +1756,7 @@ void ggml_gemm_q4_0_8x8_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const vo
sumi += ((v0 * a_ptr[l].qs[k * 4 * blocklen + m * blocklen + i]) +
(v1 * a_ptr[l].qs[k * 4 * blocklen + m * blocklen + i + qk / 2 * 4])) >> 4;
}
sumf[m][j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_FP16_TO_FP32(a_ptr[l].d[m]);
sumf[m][j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_CPU_FP16_TO_FP32(a_ptr[l].d[m]);
}
}
}
@ -3259,7 +3260,7 @@ void ggml_gemm_q4_K_8x8_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
sumi2 = sumi2 * scales_1[j];
sumi += sumi1 + sumi2;
}
sumf[m][j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * a_ptr[l].d[m];
sumf[m][j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * a_ptr[l].d[m];
}
}
}
@ -3268,7 +3269,7 @@ void ggml_gemm_q4_K_8x8_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const vo
for(int m = 0; m < 4; m++) {
const int16_t *bsums = a_ptr[l].bsums + (sb * 8) + (m * 4) - ((sb % 2) * 6);
for(int j = 0; j < ncols_interleaved; j++) {
sum_minf[m][j] += mins[j] * (bsums[0] + bsums[1]) * GGML_FP16_TO_FP32(b_ptr[l].dmin[j]) * a_ptr[l].d[m];
sum_minf[m][j] += mins[j] * (bsums[0] + bsums[1]) * GGML_CPU_FP16_TO_FP32(b_ptr[l].dmin[j]) * a_ptr[l].d[m];
}
}
}

5
ggml/src/ggml-cpu/common.h
View File

@ -4,6 +4,7 @@
#include "traits.h"
#include "ggml-cpu-impl.h"
#include "ggml-impl.h"
#include "simd-mappings.h"
#ifdef __cplusplus
@ -12,11 +13,11 @@
// convenience functions/macros for use in template calls
// note: these won't be required after the 'traits' lookup table is used.
static inline ggml_fp16_t f32_to_f16(float x) {
return GGML_FP32_TO_FP16(x);
return GGML_CPU_FP32_TO_FP16(x);
}
static inline float f16_to_f32(ggml_fp16_t x) {
return GGML_FP16_TO_FP32(x);
return GGML_CPU_FP16_TO_FP32(x);
}
static inline ggml_bf16_t f32_to_bf16(float x) {

12
ggml/src/ggml-cpu/ggml-cpu-impl.h
View File

@ -62,11 +62,17 @@ struct ggml_compute_params {
#if defined(__s390x__) && defined(__VEC__)
#ifndef __VXE__
#define __VXE__
#endif
#endif // __VXE__
#ifndef __VXE2__
#define __VXE2__
#endif
#endif
#endif // __VXE2__
#endif // __s390x__ && __VEC__
#if defined(__s390x__) && defined(GGML_NNPA)
#ifndef __NNPA__
#define __NNPA__
#endif // __NNPA__
#endif // __s390x__ && GGML_NNPA
#if defined(__ARM_FEATURE_SVE)
#include <sys/prctl.h>

75
ggml/src/ggml-cpu/ggml-cpu.c
View File

@ -72,6 +72,9 @@
#define UNUSED GGML_UNUSED
#define SWAP(x, y, T) do { T SWAP = x; (x) = y; (y) = SWAP; } while (0)
// precomputed f32 table for f16 (256 KB) (simd-mappings.h)
float ggml_table_f32_f16[1 << 16];
#if defined(__ARM_ARCH)
struct ggml_arm_arch_features_type {
int sve_cnt;
@ -736,7 +739,7 @@ struct ggml_tensor * ggml_set_i32 (struct ggml_tensor * tensor, int32_t value) {
{
assert(tensor->nb[0] == sizeof(ggml_fp16_t));
for (int i = 0; i < n; i++) {
ggml_vec_set_f16(nc, (ggml_fp16_t *)(data + i*n1), GGML_FP32_TO_FP16(value));
ggml_vec_set_f16(nc, (ggml_fp16_t *)(data + i*n1), GGML_CPU_FP32_TO_FP16(value));
}
} break;
case GGML_TYPE_BF16:
@ -795,7 +798,7 @@ struct ggml_tensor * ggml_set_f32(struct ggml_tensor * tensor, float value) {
{
assert(tensor->nb[0] == sizeof(ggml_fp16_t));
for (int i = 0; i < n; i++) {
ggml_vec_set_f16(nc, (ggml_fp16_t *)(data + i*n1), GGML_FP32_TO_FP16(value));
ggml_vec_set_f16(nc, (ggml_fp16_t *)(data + i*n1), GGML_CPU_FP32_TO_FP16(value));
}
} break;
case GGML_TYPE_BF16:
@ -846,7 +849,7 @@ int32_t ggml_get_i32_1d(const struct ggml_tensor * tensor, int i) {
case GGML_TYPE_F16:
{
GGML_ASSERT(tensor->nb[0] == sizeof(ggml_fp16_t));
return GGML_FP16_TO_FP32(((ggml_fp16_t *)(tensor->data))[i]);
return GGML_CPU_FP16_TO_FP32(((ggml_fp16_t *)(tensor->data))[i]);
}
case GGML_TYPE_BF16:
{
@ -891,7 +894,7 @@ void ggml_set_i32_1d(const struct ggml_tensor * tensor, int i, int32_t value) {
case GGML_TYPE_F16:
{
GGML_ASSERT(tensor->nb[0] == sizeof(ggml_fp16_t));
((ggml_fp16_t *)(tensor->data))[i] = GGML_FP32_TO_FP16(value);
((ggml_fp16_t *)(tensor->data))[i] = GGML_CPU_FP32_TO_FP16(value);
} break;
case GGML_TYPE_BF16:
{
@ -920,7 +923,7 @@ int32_t ggml_get_i32_nd(const struct ggml_tensor * tensor, int i0, int i1, int i
case GGML_TYPE_I32:
return ((int32_t *) data)[0];
case GGML_TYPE_F16:
return GGML_FP16_TO_FP32(((ggml_fp16_t *) data)[0]);
return GGML_CPU_FP16_TO_FP32(((ggml_fp16_t *) data)[0]);
case GGML_TYPE_BF16:
return GGML_BF16_TO_FP32(((ggml_bf16_t *) data)[0]);
case GGML_TYPE_F32:
@ -947,7 +950,7 @@ void ggml_set_i32_nd(const struct ggml_tensor * tensor, int i0, int i1, int i2,
} break;
case GGML_TYPE_F16:
{
((ggml_fp16_t *)(data))[0] = GGML_FP32_TO_FP16(value);
((ggml_fp16_t *)(data))[0] = GGML_CPU_FP32_TO_FP16(value);
} break;
case GGML_TYPE_BF16:
{
@ -985,7 +988,7 @@ float ggml_get_f32_1d(const struct ggml_tensor * tensor, int i) {
}
case GGML_TYPE_F16:
{
return GGML_FP16_TO_FP32(((ggml_fp16_t *)(tensor->data))[i]);
return GGML_CPU_FP16_TO_FP32(((ggml_fp16_t *)(tensor->data))[i]);
}
case GGML_TYPE_BF16:
{
@ -1024,7 +1027,7 @@ void ggml_set_f32_1d(const struct ggml_tensor * tensor, int i, float value) {
} break;
case GGML_TYPE_F16:
{
((ggml_fp16_t *)(tensor->data))[i] = GGML_FP32_TO_FP16(value);
((ggml_fp16_t *)(tensor->data))[i] = GGML_CPU_FP32_TO_FP16(value);
} break;
case GGML_TYPE_BF16:
{
@ -1051,7 +1054,7 @@ float ggml_get_f32_nd(const struct ggml_tensor * tensor, int i0, int i1, int i2,
case GGML_TYPE_I32:
return ((int32_t *) data)[0];
case GGML_TYPE_F16:
return GGML_FP16_TO_FP32(((ggml_fp16_t *) data)[0]);
return GGML_CPU_FP16_TO_FP32(((ggml_fp16_t *) data)[0]);
case GGML_TYPE_BF16:
return GGML_BF16_TO_FP32(((ggml_bf16_t *) data)[0]);
case GGML_TYPE_F32:
@ -1078,7 +1081,7 @@ void ggml_set_f32_nd(const struct ggml_tensor * tensor, int i0, int i1, int i2,
} break;
case GGML_TYPE_F16:
{
((ggml_fp16_t *)(data))[0] = GGML_FP32_TO_FP16(value);
((ggml_fp16_t *)(data))[0] = GGML_CPU_FP32_TO_FP16(value);
} break;
case GGML_TYPE_BF16:
{
@ -3141,9 +3144,24 @@ void ggml_cpu_fp32_to_fp16(const float * x, ggml_fp16_t * y, int64_t n) {
__m128i y_vec = _mm_cvtps_ph(x_vec, _MM_FROUND_TO_NEAREST_INT);
_mm_storel_epi64((__m128i *)(y + i), y_vec);
}
#elif defined(__NNPA__)
for (; i + 7 < n; i += 8) {
float32x4_t v_xh = vec_xl(0, (const float *)(x + i + 0));
float32x4_t v_xl = vec_xl(0, (const float *)(x + i + 4));
uint16x8_t v_yd = vec_round_from_fp32(v_xh, v_xl, 0);
uint16x8_t v_y = vec_convert_to_fp16(v_yd, 0);
vec_xst(v_y, 0, (ggml_fp16_t *)(y + i));
}
for (; i + 3 < n; i += 4) {
float32x4_t v_x = vec_xl(0, (const float *)(x + i));
float32x4_t v_zero = vec_splats(0.0f);
uint16x8_t v_yd = vec_round_from_fp32(v_x, v_zero, 0);
uint16x8_t v_y = vec_convert_to_fp16(v_yd, 0);
vec_xst(v_y, 0, (ggml_fp16_t *)(y + i));
}
#endif
for (; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(x[i]);
y[i] = GGML_CPU_FP32_TO_FP16(x[i]);
}
}
@ -3167,9 +3185,25 @@ void ggml_cpu_fp16_to_fp32(const ggml_fp16_t * x, float * y, int64_t n) {
__m128 y_vec = _mm_cvtph_ps(x_vec);
_mm_storeu_ps(y + i, y_vec);
}
#elif defined(__NNPA__)
for (; i + 7 < n; i += 8) {
uint16x8_t v_x = vec_xl(0, (const ggml_fp16_t *)(x + i));
uint16x8_t v_yd = vec_convert_from_fp16(v_x, 0);
float32x4_t v_yh = vec_extend_to_fp32_hi(v_yd, 0);
float32x4_t v_yl = vec_extend_to_fp32_lo(v_yd, 0);
vec_xst(v_yh, 0, (float *)(y + i + 0));
vec_xst(v_yl, 0, (float *)(y + i + 4));
}
for (; i + 3 < n; i += 4) {
uint16x8_t v_x = vec_xl(0, (const ggml_fp16_t *)(x + i));
uint16x8_t v_yd = vec_convert_from_fp16(v_x, 0);
float32x4_t v_yh = vec_extend_to_fp32_hi(v_yd, 0);
vec_xst(v_yh, 0, (float *)(y + i));
}
#endif
for (; i < n; ++i) {
y[i] = GGML_FP16_TO_FP32(x[i]);
y[i] = GGML_CPU_FP16_TO_FP32(x[i]);
}
}
@ -3369,6 +3403,14 @@ int ggml_cpu_has_vxe(void) {
#endif
}
int ggml_cpu_has_nnpa(void) {
#if defined(GGML_NNPA)
return 1;
#else
return 0;
#endif
}
int ggml_cpu_has_neon(void) {
#if defined(__ARM_ARCH) && defined(__ARM_NEON)
return 1;
@ -3418,7 +3460,7 @@ int ggml_cpu_has_sme(void) {
}
void ggml_cpu_init(void) {
// needed to initialize f16 tables
// needed to initialize ggml_time
{
struct ggml_init_params params = { 0, NULL, false };
struct ggml_context * ctx = ggml_init(params);
@ -3439,9 +3481,10 @@ void ggml_cpu_init(void) {
uint16_t u16;
ggml_fp16_t fp16;
} u = {i};
float f = GGML_FP16_TO_FP32(u.fp16);
ggml_table_gelu_f16[i] = GGML_FP32_TO_FP16(ggml_gelu_f32(f));
ggml_table_gelu_quick_f16[i] = GGML_FP32_TO_FP16(ggml_gelu_quick_f32(f));
float f = GGML_COMPUTE_FP16_TO_FP32(u.fp16);
ggml_table_f32_f16[i] = f;
ggml_table_gelu_f16[i] = GGML_CPU_FP32_TO_FP16(ggml_gelu_f32(f));
ggml_table_gelu_quick_f16[i] = GGML_CPU_FP32_TO_FP16(ggml_gelu_quick_f32(f));
}
const uint64_t t_end = ggml_time_us(); UNUSED(t_end);

3
ggml/src/ggml-cpu/ggml-cpu.cpp
View File

@ -578,6 +578,9 @@ static ggml_backend_feature * ggml_backend_cpu_get_features(ggml_backend_reg_t r
if (ggml_cpu_has_vxe()) {
features.push_back({ "VXE", "1" });
}
if (ggml_cpu_has_nnpa()) {
features.push_back({ "NNPA", "1" });
}
if (ggml_cpu_has_wasm_simd()) {
features.push_back({ "WASM_SIMD", "1" });
}

5
ggml/src/ggml-cpu/llamafile/sgemm.cpp
View File

@ -52,6 +52,7 @@
#include "ggml-impl.h"
#include "ggml-cpu-impl.h"
#include "ggml-quants.h"
#include "simd-mappings.h"
#include <array>
#include <type_traits>
@ -73,7 +74,7 @@
namespace {
inline float unhalf(ggml_fp16_t d) {
return GGML_FP16_TO_FP32(d);
return GGML_CPU_FP16_TO_FP32(d);
}
////////////////////////////////////////////////////////////////////////////////////////////////////
@ -252,7 +253,7 @@ template <> inline float32x4_t load(const ggml_fp16_t * p) {
float tmp[4];
for (int i = 0; i < 4; i++) {
tmp[i] = GGML_FP16_TO_FP32(p[i]);
tmp[i] = GGML_CPU_FP16_TO_FP32(p[i]);
}
return vec_xl(0, (const float *)(tmp));

96
ggml/src/ggml-cpu/ops.cpp
View File

@ -108,7 +108,7 @@ static void ggml_compute_forward_dup_f16(
for (int i01 = ir0; i01 < ir1; i01++) {
const ggml_fp16_t * src0_ptr = (ggml_fp16_t *) ((char *) src0->data + i01*nb01 + i02*nb02 + i03*nb03);
for (int i00 = 0; i00 < ne00; i00++) {
dst_ptr[id] = GGML_FP16_TO_FP32(src0_ptr[i00]);
dst_ptr[id] = GGML_CPU_FP16_TO_FP32(src0_ptr[i00]);
id++;
}
}
@ -130,7 +130,7 @@ static void ggml_compute_forward_dup_f16(
const ggml_fp16_t * src0_ptr = (ggml_fp16_t *) ((char *) src0->data + i01*nb01 + i02*nb02 + i03*nb03);
for (int i00 = 0; i00 < ne00; i00++) {
src0_f32[i00] = GGML_FP16_TO_FP32(src0_ptr[i00]);
src0_f32[i00] = GGML_CPU_FP16_TO_FP32(src0_ptr[i00]);
}
quantize_row_q(src0_f32, dst_ptr + id, ne00);
@ -156,7 +156,7 @@ static void ggml_compute_forward_dup_f16(
for (int i00 = 0; i00 < ne00; i00++) {
const ggml_fp16_t * src0_ptr = (ggml_fp16_t *) ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03);
dst_ptr[id] = GGML_FP16_TO_FP32(*src0_ptr);
dst_ptr[id] = GGML_CPU_FP16_TO_FP32(*src0_ptr);
id++;
}
}
@ -267,7 +267,7 @@ static void ggml_compute_forward_dup_f16(
const char * src0_ptr = ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03);
char * dst_ptr = ((char *) dst->data + i10*nb0 + i11*nb1 + i12*nb2 + i13*nb3);
*(float *) dst_ptr = GGML_FP16_TO_FP32(*(const ggml_fp16_t *) src0_ptr);
*(float *) dst_ptr = GGML_CPU_FP16_TO_FP32(*(const ggml_fp16_t *) src0_ptr);
if (++i10 == ne0) {
i10 = 0;
@ -372,7 +372,7 @@ static void ggml_compute_forward_dup_bf16(
for (int i01 = ir0; i01 < ir1; i01++) {
const ggml_bf16_t * src0_ptr = (ggml_bf16_t *) ((char *) src0->data + i01*nb01 + i02*nb02 + i03*nb03);
for (int i00 = 0; i00 < ne00; i00++) {
dst_ptr[id] = GGML_FP32_TO_FP16(GGML_BF16_TO_FP32(src0_ptr[i00]));
dst_ptr[id] = GGML_CPU_FP32_TO_FP16(GGML_BF16_TO_FP32(src0_ptr[i00]));
id++;
}
}
@ -473,7 +473,7 @@ static void ggml_compute_forward_dup_bf16(
for (int i00 = 0; i00 < ne00; i00++) {
const ggml_bf16_t * src0_ptr = (ggml_bf16_t *) ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03);
dst_ptr[id] = GGML_FP32_TO_FP16(GGML_BF16_TO_FP32(*src0_ptr));
dst_ptr[id] = GGML_CPU_FP32_TO_FP16(GGML_BF16_TO_FP32(*src0_ptr));
id++;
}
}
@ -566,7 +566,7 @@ static void ggml_compute_forward_dup_bf16(
const char * src0_ptr = ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03);
char * dst_ptr = ((char *) dst->data + i10*nb0 + i11*nb1 + i12*nb2 + i13*nb3);
*(ggml_fp16_t *) dst_ptr = GGML_FP32_TO_FP16(GGML_BF16_TO_FP32(*(const ggml_bf16_t *) src0_ptr));
*(ggml_fp16_t *) dst_ptr = GGML_CPU_FP32_TO_FP16(GGML_BF16_TO_FP32(*(const ggml_bf16_t *) src0_ptr));
if (++i10 == ne0) {
i10 = 0;
@ -765,7 +765,7 @@ static void ggml_compute_forward_dup_f32(
for (int i00 = 0; i00 < ne00; i00++) {
const float * src0_ptr = (float *) ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03);
dst_ptr[id] = GGML_FP32_TO_FP16(*src0_ptr);
dst_ptr[id] = GGML_CPU_FP32_TO_FP16(*src0_ptr);
id++;
}
}
@ -878,7 +878,7 @@ static void ggml_compute_forward_dup_f32(
const char * src0_ptr = ((char *) src0->data + i00*nb00 + i01*nb01 + i02*nb02 + i03*nb03);
char * dst_ptr = ((char *) dst->data + i10*nb0 + i11*nb1 + i12*nb2 + i13*nb3);
*(ggml_fp16_t *) dst_ptr = GGML_FP32_TO_FP16(*(const float *) src0_ptr);
*(ggml_fp16_t *) dst_ptr = GGML_CPU_FP32_TO_FP16(*(const float *) src0_ptr);
if (++i10 == ne0) {
i10 = 0;
@ -1419,7 +1419,7 @@ static void ggml_compute_forward_add1_f16_f32(
ggml_fp16_t * dst_ptr = (ggml_fp16_t *) ((char *) dst->data + i3*nb3 + i2*nb2 + i1*nb1 );
ggml_fp16_t * src0_ptr = (ggml_fp16_t *) ((char *) src0->data + i3*nb03 + i2*nb02 + i1*nb01);
for (int i = 0; i < ne0; i++) {
dst_ptr[i] = GGML_FP32_TO_FP16(GGML_FP16_TO_FP32(src0_ptr[i]) + v);
dst_ptr[i] = GGML_CPU_FP32_TO_FP16(GGML_CPU_FP16_TO_FP32(src0_ptr[i]) + v);
}
}
}
@ -1435,7 +1435,7 @@ static void ggml_compute_forward_add1_f16_f16(
GGML_ASSERT(ggml_is_scalar(src1));
// scalar to add
const float v = GGML_FP16_TO_FP32(*(ggml_fp16_t *) src1->data);
const float v = GGML_CPU_FP16_TO_FP32(*(ggml_fp16_t *) src1->data);
const int ith = params->ith;
const int nth = params->nth;
@ -1467,7 +1467,7 @@ static void ggml_compute_forward_add1_f16_f16(
ggml_fp16_t * dst_ptr = (ggml_fp16_t *) ((char *) dst->data + i3*nb3 + i2*nb2 + i1*nb1 );
ggml_fp16_t * src0_ptr = (ggml_fp16_t *) ((char *) src0->data + i3*nb03 + i2*nb02 + i1*nb01);
for (int i = 0; i < ne0; i++) {
dst_ptr[i] = GGML_FP32_TO_FP16(GGML_FP16_TO_FP32(src0_ptr[i]) + v);
dst_ptr[i] = GGML_CPU_FP32_TO_FP16(GGML_CPU_FP16_TO_FP32(src0_ptr[i]) + v);
}
}
}
@ -1889,7 +1889,7 @@ static void ggml_compute_forward_sum_f16(
}
}
}
((ggml_fp16_t *) dst->data)[0] = GGML_FP32_TO_FP16(sum);
((ggml_fp16_t *) dst->data)[0] = GGML_CPU_FP32_TO_FP16(sum);
}
static void ggml_compute_forward_sum_bf16(
@ -2660,7 +2660,7 @@ static void ggml_compute_forward_gelu_f16(
#ifndef NDEBUG
for (int k = 0; k < nc; k++) {
const ggml_fp16_t x = ((ggml_fp16_t *) ((char *) dst->data + i1*( dst->nb[1])))[k];
const float v = GGML_FP16_TO_FP32(x);
const float v = GGML_CPU_FP16_TO_FP32(x);
GGML_UNUSED(v);
assert(!isnan(v));
assert(!isinf(v));
@ -2763,7 +2763,7 @@ static void ggml_compute_forward_gelu_erf_f16(
#ifndef NDEBUG
for (int k = 0; k < nc; k++) {
const ggml_fp16_t x = ((ggml_fp16_t *) ((char *) dst->data + i1*( dst->nb[1])))[k];
const float v = GGML_FP16_TO_FP32(x);
const float v = GGML_CPU_FP16_TO_FP32(x);
GGML_UNUSED(v);
assert(!isnan(v));
assert(!isinf(v));
@ -2866,7 +2866,7 @@ static void ggml_compute_forward_gelu_quick_f16(
#ifndef NDEBUG
for (int k = 0; k < nc; k++) {
const ggml_fp16_t x = ((ggml_fp16_t *) ((char *) dst->data + i1*( dst->nb[1])))[k];
const float v = GGML_FP16_TO_FP32(x);
const float v = GGML_CPU_FP16_TO_FP32(x);
GGML_UNUSED(v);
assert(!isnan(v));
assert(!isinf(v));
@ -2969,7 +2969,7 @@ static void ggml_compute_forward_silu_f16(
#ifndef NDEBUG
for (int k = 0; k < nc; k++) {
const ggml_fp16_t x = ((ggml_fp16_t *) ((char *) dst->data + i1*(dst->nb[1])))[k];
const float v = GGML_FP16_TO_FP32(x);
const float v = GGML_CPU_FP16_TO_FP32(x);
GGML_UNUSED(v);
assert(!isnan(v));
assert(!isinf(v));
@ -3163,7 +3163,7 @@ static void ggml_compute_forward_silu_back_f16(
#ifndef NDEBUG
for (int k = 0; k < nc; k++) {
const float x = ((ggml_fp16_t *) ((char *) dst->data + i1*( dst->nb[1])))[k];
const float v = GGML_FP16_TO_FP32(x);
const float v = GGML_CPU_FP16_TO_FP32(x);
GGML_UNUSED(v);
assert(!isnan(v));
assert(!isinf(v));
@ -4500,7 +4500,7 @@ static void ggml_compute_forward_get_rows_back_f32_f16(
for (int j = 0; j < nc; ++j) {
ggml_fp16_t v = ((ggml_fp16_t *) ((char *) src0->data + i*src0->nb[1]))[j];
((float *) ((char *) dst->data + r*dst->nb[1]))[j] += GGML_FP16_TO_FP32(v);
((float *) ((char *) dst->data + r*dst->nb[1]))[j] += GGML_CPU_FP16_TO_FP32(v);
}
}
}
@ -4792,7 +4792,7 @@ static void ggml_compute_forward_soft_max_f32(
if (mp_f32) {
if (use_f16) {
for (int i = 0; i < nc; ++i) {
wp[i] += slope*GGML_FP16_TO_FP32(mp_f16[i]);
wp[i] += slope*GGML_CPU_FP16_TO_FP32(mp_f16[i]);
}
} else {
for (int i = 0; i < nc; ++i) {
@ -5018,8 +5018,8 @@ static void ggml_compute_forward_clamp_f16(
ggml_fp16_t * src0_ptr = (ggml_fp16_t *) ((char *) src0->data + j*nb01);
for (int i = 0; i < nc; i++) {
float v = GGML_FP16_TO_FP32(src0_ptr[i]);
dst_ptr[i] = GGML_FP32_TO_FP16(MAX(MIN(v, max), min));
float v = GGML_CPU_FP16_TO_FP32(src0_ptr[i]);
dst_ptr[i] = GGML_CPU_FP32_TO_FP16(MAX(MIN(v, max), min));
}
}
}
@ -5476,11 +5476,11 @@ static void ggml_compute_forward_rope_f16(
const ggml_fp16_t * const src = (ggml_fp16_t *)((char *) src0->data + i3*nb03 + i2*nb02 + i1*nb01 + ic*nb00);
ggml_fp16_t * dst_data = (ggml_fp16_t *)((char *) dst->data + i3*nb3 + i2*nb2 + i1*nb1 + ic*nb0);
const float x0 = GGML_FP16_TO_FP32(src[0]);
const float x1 = GGML_FP16_TO_FP32(src[n_dims]);
const float x0 = GGML_CPU_FP16_TO_FP32(src[0]);
const float x1 = GGML_CPU_FP16_TO_FP32(src[n_dims]);
dst_data[0] = GGML_FP32_TO_FP16(x0*cos_theta - x1*sin_theta);
dst_data[n_dims] = GGML_FP32_TO_FP16(x0*sin_theta + x1*cos_theta);
dst_data[0] = GGML_CPU_FP32_TO_FP16(x0*cos_theta - x1*sin_theta);
dst_data[n_dims] = GGML_CPU_FP32_TO_FP16(x0*sin_theta + x1*cos_theta);
}
} else {
for (int64_t i0 = 0; i0 < n_dims; i0 += 2) {
@ -5492,11 +5492,11 @@ static void ggml_compute_forward_rope_f16(
const ggml_fp16_t * const src = (ggml_fp16_t *)((char *) src0->data + i3*nb03 + i2*nb02 + i1*nb01 + ic*nb00);
ggml_fp16_t * dst_data = (ggml_fp16_t *)((char *) dst->data + i3*nb3 + i2*nb2 + i1*nb1 + ic*nb0);
const float x0 = GGML_FP16_TO_FP32(src[0]);
const float x1 = GGML_FP16_TO_FP32(src[n_dims/2]);
const float x0 = GGML_CPU_FP16_TO_FP32(src[0]);
const float x1 = GGML_CPU_FP16_TO_FP32(src[n_dims/2]);
dst_data[0] = GGML_FP32_TO_FP16(x0*cos_theta - x1*sin_theta);
dst_data[n_dims/2] = GGML_FP32_TO_FP16(x0*sin_theta + x1*cos_theta);
dst_data[0] = GGML_CPU_FP32_TO_FP16(x0*cos_theta - x1*sin_theta);
dst_data[n_dims/2] = GGML_CPU_FP32_TO_FP16(x0*sin_theta + x1*cos_theta);
}
}
} else {
@ -5507,11 +5507,11 @@ static void ggml_compute_forward_rope_f16(
const ggml_fp16_t * const src = (ggml_fp16_t *)((char *) src0->data + i3*nb03 + i2*nb02 + i1*nb01 + i0*nb00);
ggml_fp16_t * dst_data = (ggml_fp16_t *)((char *) dst->data + i3*nb3 + i2*nb2 + i1*nb1 + i0*nb0);
const float x0 = GGML_FP16_TO_FP32(src[0]);
const float x1 = GGML_FP16_TO_FP32(src[1]);
const float x0 = GGML_CPU_FP16_TO_FP32(src[0]);
const float x1 = GGML_CPU_FP16_TO_FP32(src[1]);
dst_data[0] = GGML_FP32_TO_FP16(x0*cos_theta - x1*sin_theta);
dst_data[1] = GGML_FP32_TO_FP16(x0*sin_theta + x1*cos_theta);
dst_data[0] = GGML_CPU_FP32_TO_FP16(x0*cos_theta - x1*sin_theta);
dst_data[1] = GGML_CPU_FP32_TO_FP16(x0*sin_theta + x1*cos_theta);
}
}
@ -5525,11 +5525,11 @@ static void ggml_compute_forward_rope_f16(
const ggml_fp16_t * const src = (ggml_fp16_t *)((char *) src0->data + i3*nb03 + i2*nb02 + i1*nb01 + ic*nb00);
ggml_fp16_t * dst_data = (ggml_fp16_t *)((char *) dst->data + i3*nb3 + i2*nb2 + i1*nb1 + ic*nb0);
const float x0 = GGML_FP16_TO_FP32(src[0]);
const float x1 = GGML_FP16_TO_FP32(src[n_dims]);
const float x0 = GGML_CPU_FP16_TO_FP32(src[0]);
const float x1 = GGML_CPU_FP16_TO_FP32(src[n_dims]);
dst_data[0] = GGML_FP32_TO_FP16(x0*cos_theta - x1*sin_theta);
dst_data[n_dims] = GGML_FP32_TO_FP16(x0*sin_theta + x1*cos_theta);
dst_data[0] = GGML_CPU_FP32_TO_FP16(x0*cos_theta - x1*sin_theta);
dst_data[n_dims] = GGML_CPU_FP32_TO_FP16(x0*sin_theta + x1*cos_theta);
}
} else {
for (int64_t i0 = n_dims; i0 < ne0; i0 += 2) {
@ -5640,7 +5640,7 @@ static void ggml_compute_forward_conv_transpose_1d_f16_f32(
for (int64_t i11 = 0; i11 < ne11; i11++) {
const float * const src = (float *)((char *) src1->data + i11*nb11);
for (int64_t i10 = 0; i10 < ne10; i10++) {
dst_data[i10*ne11 + i11] = GGML_FP32_TO_FP16(src[i10]);
dst_data[i10*ne11 + i11] = GGML_CPU_FP32_TO_FP16(src[i10]);
}
}
}
@ -5933,7 +5933,7 @@ static void ggml_compute_forward_im2col_f16(
if (iih < 0 || iih >= IH || iiw < 0 || iiw >= IW) {
dst_data[iic*(KH*KW) + ikh*KW + ikw] = 0;
} else {
dst_data[iic*(KH*KW) + ikh*KW + ikw] = GGML_FP32_TO_FP16(src_data[iih*IW + iiw]);
dst_data[iic*(KH*KW) + ikh*KW + ikw] = GGML_CPU_FP32_TO_FP16(src_data[iih*IW + iiw]);
}
}
}
@ -6109,7 +6109,7 @@ void ggml_compute_forward_conv_transpose_2d(
const float * const src = (float *)((char *) src1->data + i12*nb12 + i11*nb11);
ggml_fp16_t * dst_data = wdata + i11*ne10*ne12;
for (int i10 = 0; i10 < ne10; i10++) {
dst_data[i10*ne12 + i12] = GGML_FP32_TO_FP16(src[i10]);
dst_data[i10*ne12 + i12] = GGML_CPU_FP32_TO_FP16(src[i10]);
}
}
}
@ -6358,7 +6358,7 @@ static void ggml_compute_forward_pool_1d_sk_p0(
case GGML_OP_POOL_COUNT: GGML_ABORT("fatal error");
}
for (int ki = 0; ki < k; ++ki) {
const float srow_j = (src->type == GGML_TYPE_F32) ? ((const float*)srow)[j] : GGML_FP16_TO_FP32(((const ggml_fp16_t*)srow)[j]);
const float srow_j = (src->type == GGML_TYPE_F32) ? ((const float*)srow)[j] : GGML_CPU_FP16_TO_FP32(((const ggml_fp16_t*)srow)[j]);
switch (op) {
case GGML_OP_POOL_AVG: drow[i] += srow_j; break;
case GGML_OP_POOL_MAX: if (srow_j > drow[i]) drow[i] = srow_j; break;
@ -6450,7 +6450,7 @@ void ggml_compute_forward_pool_2d(
for (int kx = 0; kx < k0; ++kx) {
int j = ix + kx;
if (j < 0 || j >= src->ne[0]) continue;
const float srow_j = (src->type == GGML_TYPE_F32) ? ((const float*)srow)[j] : GGML_FP16_TO_FP32(((const ggml_fp16_t*)srow)[j]);
const float srow_j = (src->type == GGML_TYPE_F32) ? ((const float*)srow)[j] : GGML_CPU_FP16_TO_FP32(((const ggml_fp16_t*)srow)[j]);
switch (op) {
case GGML_OP_POOL_AVG: *out += srow_j; break;
case GGML_OP_POOL_MAX: if (srow_j > *out) *out = srow_j; break;
@ -6538,7 +6538,7 @@ void ggml_compute_forward_pool_2d_back(
}
const float val = dst->type == GGML_TYPE_F32 ?
((const float *) drowf)[j] : GGML_FP16_TO_FP32(((const ggml_fp16_t *) drowf)[j]);
((const float *) drowf)[j] : GGML_CPU_FP16_TO_FP32(((const ggml_fp16_t *) drowf)[j]);
if (val <= maxval) {
continue;
}
@ -6558,7 +6558,7 @@ void ggml_compute_forward_pool_2d_back(
if (dst->type == GGML_TYPE_F32) {
((float *) drow)[j] += grad0;
} else {
((ggml_fp16_t *) drow)[j] = GGML_FP32_TO_FP16(grad0 + GGML_FP16_TO_FP32(((const ggml_fp16_t *) drow)[j]));
((ggml_fp16_t *) drow)[j] = GGML_CPU_FP32_TO_FP16(grad0 + GGML_CPU_FP16_TO_FP32(((const ggml_fp16_t *) drow)[j]));
}
} else if (op == GGML_OP_POOL_AVG) {
const float grad = grad0 / ka;
@ -6577,7 +6577,7 @@ void ggml_compute_forward_pool_2d_back(
if (dst->type == GGML_TYPE_F32) {
((float *) drow)[j] += grad;
} else {
((ggml_fp16_t *) drow)[j] += GGML_FP32_TO_FP16(grad);
((ggml_fp16_t *) drow)[j] += GGML_CPU_FP32_TO_FP16(grad);
}
}
}
@ -7142,7 +7142,7 @@ static void ggml_compute_forward_flash_attn_ext_f16(
// loop over n_kv and n_head_kv
// ref: https://arxiv.org/pdf/2112.05682.pdf
for (int64_t ic = 0; ic < nek1; ++ic) {
const float mv = mp ? slope*GGML_FP16_TO_FP32(mp[ic]) : 0.0f;
const float mv = mp ? slope*GGML_CPU_FP16_TO_FP32(mp[ic]) : 0.0f;
if (mv == -INFINITY) {
continue;
}
@ -7210,7 +7210,7 @@ static void ggml_compute_forward_flash_attn_ext_f16(
if (v->type == GGML_TYPE_F16) {
for (int64_t d = 0; d < DV; ++d) {
VKQ32[d] = GGML_FP16_TO_FP32(VKQ16[d]);
VKQ32[d] = GGML_CPU_FP16_TO_FP32(VKQ16[d]);
}
}

49
ggml/src/ggml-cpu/quants.c
View File

@ -2,6 +2,7 @@
#include "ggml-common.h"
#include "ggml-cpu-impl.h"
#include "simd-mappings.h"
#include "ggml-quants.h"
#include "quants.h"
@ -137,7 +138,7 @@ void ggml_vec_dot_q4_0_q8_0_generic(int n, float * GGML_RESTRICT s, size_t bs, c
}
int sumi = sumi0 + sumi1;
sumf += sumi*GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d);
sumf += sumi*GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d);
}
*s = sumf;
@ -174,7 +175,7 @@ void ggml_vec_dot_q4_1_q8_1_generic(int n, float * GGML_RESTRICT s, size_t bs, c
}
int sumi = sumi0 + sumi1;
sumf += (GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d))*sumi + GGML_FP16_TO_FP32(x[ib].m)*GGML_FP16_TO_FP32(y[ib].s);
sumf += (GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d))*sumi + GGML_CPU_FP16_TO_FP32(x[ib].m)*GGML_CPU_FP16_TO_FP32(y[ib].s);
}
*s = sumf;
@ -217,7 +218,7 @@ void ggml_vec_dot_q5_0_q8_0_generic(int n, float * GGML_RESTRICT s, size_t bs, c
}
int sumi = sumi0 + sumi1;
sumf += (GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d)) * sumi;
sumf += (GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d)) * sumi;
}
*s = sumf;
@ -260,7 +261,7 @@ void ggml_vec_dot_q5_1_q8_1_generic(int n, float * GGML_RESTRICT s, size_t bs, c
}
int sumi = sumi0 + sumi1;
sumf += (GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d))*sumi + GGML_FP16_TO_FP32(x[ib].m)*GGML_FP16_TO_FP32(y[ib].s);
sumf += (GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d))*sumi + GGML_CPU_FP16_TO_FP32(x[ib].m)*GGML_CPU_FP16_TO_FP32(y[ib].s);
}
*s = sumf;
@ -290,7 +291,7 @@ void ggml_vec_dot_q8_0_q8_0_generic(int n, float * GGML_RESTRICT s, size_t bs, c
sumi += x[ib].qs[j]*y[ib].qs[j];
}
sumf += sumi*(GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d));
sumf += sumi*(GGML_CPU_FP16_TO_FP32(x[ib].d)*GGML_CPU_FP16_TO_FP32(y[ib].d));
}
*s = sumf;
@ -342,7 +343,7 @@ void ggml_vec_dot_tq1_0_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs,
}
}
sumf += (float) sum * (GGML_FP16_TO_FP32(x[i].d) * y[i].d);
sumf += (float) sum * (GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d);
}
*s = sumf;
@ -372,7 +373,7 @@ void ggml_vec_dot_tq2_0_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs,
}
}
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float d = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
sumf += (float) sumi * d;
}
@ -405,8 +406,8 @@ void ggml_vec_dot_q2_K_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs, c
summs += y[i].bsums[j] * (sc[j] >> 4);
}
const float dall = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
const float dall = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_CPU_FP16_TO_FP32(x[i].dmin);
int isum = 0;
int is = 0;
@ -504,7 +505,7 @@ void ggml_vec_dot_q3_K_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs, c
for (int l = 0; l < 8; ++l) aux32[l] += (scales[j] - 32) * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -577,9 +578,9 @@ void ggml_vec_dot_q4_K_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs, c
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
const float dmin = GGML_FP16_TO_FP32(x[i].dmin) * y[i].d;
const float dmin = GGML_CPU_FP16_TO_FP32(x[i].dmin) * y[i].d;
sumf -= dmin * sumi;
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -657,9 +658,9 @@ void ggml_vec_dot_q5_K_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs, c
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
const float dmin = GGML_FP16_TO_FP32(x[i].dmin) * y[i].d;
const float dmin = GGML_CPU_FP16_TO_FP32(x[i].dmin) * y[i].d;
sumf -= dmin * sumi;
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -714,7 +715,7 @@ void ggml_vec_dot_q6_K_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs, c
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
@ -739,7 +740,7 @@ void ggml_vec_dot_iq2_xxs_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs
float sumf = 0.f;
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint16_t * GGML_RESTRICT q2 = x[i].qs;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
int32_t bsum = 0;
@ -778,7 +779,7 @@ void ggml_vec_dot_iq2_xs_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs,
float sumf = 0.f;
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint16_t * GGML_RESTRICT q2 = x[i].qs;
const uint8_t * GGML_RESTRICT sc = x[i].scales;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
@ -829,7 +830,7 @@ void ggml_vec_dot_iq2_s_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs,
float sumf = 0;
for (int i = 0; i < nb; i++) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const int8_t * q8 = y[i].qs;
const uint8_t * qs = x[i].qs;
const uint8_t * qh = x[i].qh;
@ -882,7 +883,7 @@ void ggml_vec_dot_iq3_xxs_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs
float sumf = 0.f;
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint8_t * GGML_RESTRICT q3 = x[i].qs;
const uint8_t * GGML_RESTRICT gas = x[i].qs + QK_K/4;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
@ -924,7 +925,7 @@ void ggml_vec_dot_iq3_s_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs,
float sumf = 0.f;
for (int i = 0; i < nb; ++i) {
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float d = GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d;
const uint8_t * GGML_RESTRICT qs = x[i].qs;
const uint8_t * GGML_RESTRICT qh = x[i].qh;
const uint8_t * GGML_RESTRICT signs = x[i].signs;
@ -1002,7 +1003,7 @@ void ggml_vec_dot_iq1_s_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs,
qs += 4;
}
sumf += GGML_FP16_TO_FP32(x[i].d) * y[i].d * (sumi + IQ1S_DELTA * sumi1);
sumf += GGML_CPU_FP16_TO_FP32(x[i].d) * y[i].d * (sumi + IQ1S_DELTA * sumi1);
}
*s = sumf;
@ -1063,7 +1064,7 @@ void ggml_vec_dot_iq1_m_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs,
qh += 2;
}
sumf += GGML_FP16_TO_FP32(scale.f16) * y[i].d * (sumi1 + IQ1M_DELTA * sumi2);
sumf += GGML_CPU_FP16_TO_FP32(scale.f16) * y[i].d * (sumi1 + IQ1M_DELTA * sumi2);
}
*s = sumf;
@ -1087,7 +1088,7 @@ void ggml_vec_dot_iq4_nl_q8_0_generic(int n, float * GGML_RESTRICT s, size_t bs,
float sumf = 0;
for (; ib < nb; ++ib) {
const float d = GGML_FP16_TO_FP32(y[ib].d)*GGML_FP16_TO_FP32(x[ib].d);
const float d = GGML_CPU_FP16_TO_FP32(y[ib].d)*GGML_CPU_FP16_TO_FP32(x[ib].d);
int sumi1 = 0, sumi2 = 0;
for (int j = 0; j < QK4_NL/2; ++j) {
sumi1 += y[ib].qs[j+ 0] * kvalues_iq4nl[x[ib].qs[j] & 0xf];
@ -1113,7 +1114,7 @@ void ggml_vec_dot_iq4_xs_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs,
float sumf = 0;
for (int ibl = 0; ibl < nb; ++ibl) {
const float d4d8 = GGML_FP16_TO_FP32(x[ibl].d) * y[ibl].d;
const float d4d8 = GGML_CPU_FP16_TO_FP32(x[ibl].d) * y[ibl].d;
uint16_t h = x[ibl].scales_h;
const uint8_t * qs = x[ibl].qs;
const int8_t * q8 = y[ibl].qs;

29
ggml/src/ggml-cpu/repack.cpp
View File

@ -6,6 +6,7 @@
#include "ggml-impl.h"
#include "ggml-cpu.h"
#include "ggml-cpu-impl.h"
#include "simd-mappings.h"
#include "traits.h"
#include "arch-fallback.h"
@ -72,7 +73,7 @@ void ggml_quantize_mat_q8_0_4x4_generic(const float * GGML_RESTRICT x, void * GG
const float d = amax / ((1 << 7) - 1);
id[row_iter] = d ? 1.0f / d : 0.0f;
y[i].d[row_iter] = GGML_FP32_TO_FP16(d);
y[i].d[row_iter] = GGML_CPU_FP32_TO_FP16(d);
}
for (int j = 0; j < QK8_0 * 4; j++) {
@ -110,7 +111,7 @@ void ggml_quantize_mat_q8_0_4x8_generic(const float * GGML_RESTRICT x, void * GG
const float d = amax / ((1 << 7) - 1);
id[row_iter] = d ? 1.0f / d : 0.0f;
y[i].d[row_iter] = GGML_FP32_TO_FP16(d);
y[i].d[row_iter] = GGML_CPU_FP32_TO_FP16(d);
}
for (int j = 0; j < QK8_0 * 4; j++) {
@ -236,7 +237,7 @@ void ggml_gemv_q4_0_4x4_q8_0_generic(int n, float * GGML_RESTRICT s, size_t bs,
const int v1 = (int8_t) (b_ptr[l].qs[k * ncols_interleaved * blocklen + j * blocklen + i] & 0xF0);
sumi += ((v0 * a_ptr[l].qs[k * blocklen + i]) + (v1 * a_ptr[l].qs[k * blocklen + i + qk / 2])) >> 4;
}
sumf[j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_FP16_TO_FP32(a_ptr[l].d);
sumf[j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_CPU_FP16_TO_FP32(a_ptr[l].d);
}
}
}
@ -280,7 +281,7 @@ void ggml_gemv_q4_0_4x8_q8_0_generic(int n, float * GGML_RESTRICT s, size_t bs,
const int v1 = (int8_t) (b_ptr[l].qs[k * ncols_interleaved * blocklen + j * blocklen + i] & 0xF0);
sumi += ((v0 * a_ptr[l].qs[k * blocklen + i]) + (v1 * a_ptr[l].qs[k * blocklen + i + qk / 2])) >> 4;
}
sumf[j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_FP16_TO_FP32(a_ptr[l].d);
sumf[j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_CPU_FP16_TO_FP32(a_ptr[l].d);
}
}
}
@ -325,7 +326,7 @@ void ggml_gemv_q4_0_8x8_q8_0_generic(int n, float * GGML_RESTRICT s, size_t bs,
const int v1 = (int8_t) (b_ptr[l].qs[k * ncols_interleaved * blocklen + j * blocklen + i] & 0xF0);
sumi += ((v0 * a_ptr[l].qs[k * blocklen + i]) + (v1 * a_ptr[l].qs[k * blocklen + i + qk / 2])) >> 4;
}
sumf[j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_FP16_TO_FP32(a_ptr[l].d);
sumf[j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_CPU_FP16_TO_FP32(a_ptr[l].d);
}
}
}
@ -396,13 +397,13 @@ void ggml_gemv_q4_K_8x8_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs,
sumi2 = sumi2 * scales_1[j];
sumi += sumi1 + sumi2;
}
sumf[j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * a_ptr[l].d;
sumf[j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * a_ptr[l].d;
}
}
for (int sb = 0; sb < 8; sb++) {
uint8_t *mins = (uint8_t*) utmp + 8 + sb * 16;
for (int j = 0; j < ncols_interleaved; j++) {
sum_minf[j] += mins[j] * (a_ptr[l].bsums[sb * 2] + a_ptr[l].bsums[sb * 2 + 1]) * GGML_FP16_TO_FP32(b_ptr[l].dmin[j]) * a_ptr[l].d;
sum_minf[j] += mins[j] * (a_ptr[l].bsums[sb * 2] + a_ptr[l].bsums[sb * 2 + 1]) * GGML_CPU_FP16_TO_FP32(b_ptr[l].dmin[j]) * a_ptr[l].d;
}
}
}
@ -449,7 +450,7 @@ void ggml_gemv_iq4_nl_4x4_q8_0_generic(int n, float * GGML_RESTRICT s, size_t bs
const int v1 = kvalues_iq4nl[b_ptr[l].qs[k * ncols_interleaved * blocklen + j * blocklen + i] >> 4];
sumi += ((v0 * a_ptr[l].qs[k * blocklen + i]) + (v1 * a_ptr[l].qs[k * blocklen + i + qk / 2]));
}
sumf[j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_FP16_TO_FP32(a_ptr[l].d);
sumf[j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_CPU_FP16_TO_FP32(a_ptr[l].d);
}
}
}
@ -500,7 +501,7 @@ void ggml_gemm_q4_0_4x4_q8_0_generic(int n, float * GGML_RESTRICT s, size_t bs,
sumi += ((v0 * a_ptr[l].qs[k * 4 * blocklen + m * blocklen + i]) +
(v1 * a_ptr[l].qs[k * 4 * blocklen + m * blocklen + i + qk / 2 * 4])) >> 4;
}
sumf[m][j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_FP16_TO_FP32(a_ptr[l].d[m]);
sumf[m][j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_CPU_FP16_TO_FP32(a_ptr[l].d[m]);
}
}
}
@ -555,7 +556,7 @@ void ggml_gemm_q4_0_4x8_q8_0_generic(int n, float * GGML_RESTRICT s, size_t bs,
sumi += ((v0 * a_ptr[l].qs[k * 4 * blocklen + m * blocklen + i]) +
(v1 * a_ptr[l].qs[k * 4 * blocklen + m * blocklen + i + qk / 2 * 4])) >> 4;
}
sumf[m][j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_FP16_TO_FP32(a_ptr[l].d[m]);
sumf[m][j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_CPU_FP16_TO_FP32(a_ptr[l].d[m]);
}
}
}
@ -609,7 +610,7 @@ void ggml_gemm_q4_0_8x8_q8_0_generic(int n, float * GGML_RESTRICT s, size_t bs,
sumi += ((v0 * a_ptr[l].qs[k * 4 * blocklen + m * blocklen + i]) +
(v1 * a_ptr[l].qs[k * 4 * blocklen + m * blocklen + i + qk / 2 * 4])) >> 4;
}
sumf[m][j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_FP16_TO_FP32(a_ptr[l].d[m]);
sumf[m][j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_CPU_FP16_TO_FP32(a_ptr[l].d[m]);
}
}
}
@ -688,7 +689,7 @@ void ggml_gemm_q4_K_8x8_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs,
sumi2 = sumi2 * scales_1[j];
sumi += sumi1 + sumi2;
}
sumf[m][j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * a_ptr[l].d[m];
sumf[m][j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * a_ptr[l].d[m];
}
}
}
@ -697,7 +698,7 @@ void ggml_gemm_q4_K_8x8_q8_K_generic(int n, float * GGML_RESTRICT s, size_t bs,
for(int m = 0; m < 4; m++) {
const int16_t *bsums = a_ptr[l].bsums + (sb * 8) + (m * 4) - ((sb % 2) * 6);
for(int j = 0; j < ncols_interleaved; j++) {
sum_minf[m][j] += mins[j] * (bsums[0] + bsums[1]) * GGML_FP16_TO_FP32(b_ptr[l].dmin[j]) * a_ptr[l].d[m];
sum_minf[m][j] += mins[j] * (bsums[0] + bsums[1]) * GGML_CPU_FP16_TO_FP32(b_ptr[l].dmin[j]) * a_ptr[l].d[m];
}
}
}
@ -753,7 +754,7 @@ void ggml_gemm_iq4_nl_4x4_q8_0_generic(int n, float * GGML_RESTRICT s, size_t bs
sumi += ((v0 * a_ptr[l].qs[k * 4 * blocklen + m * blocklen + i]) +
(v1 * a_ptr[l].qs[k * 4 * blocklen + m * blocklen + i + qk / 2 * 4]));
}
sumf[m][j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_FP16_TO_FP32(a_ptr[l].d[m]);
sumf[m][j] += sumi * GGML_CPU_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_CPU_FP16_TO_FP32(a_ptr[l].d[m]);
}
}
}

244
ggml/src/ggml-cpu/simd-mappings.h
View File

@ -2,10 +2,167 @@
#include "ggml-cpu-impl.h"
#ifdef __ARM_FEATURE_SVE
#include <arm_sve.h>
#endif // __ARM_FEATURE_SVE
#if defined(__ARM_NEON) && !defined(__CUDACC__) && !defined(__MUSACC__)
// if YCM cannot find <arm_neon.h>, make a symbolic link to it, for example:
//
// $ ln -sfn /Library/Developer/CommandLineTools/usr/lib/clang/13.1.6/include/arm_neon.h ./src/
//
#include <arm_neon.h>
#endif
#if defined(__F16C__)
#include <immintrin.h>
#endif
#ifdef __cplusplus
extern "C" {
#endif
//
// simd mappings
//
// FP16 to FP32 conversion
// 16-bit float
// on Arm, we use __fp16
// on x86, we use uint16_t
//
// for old CUDA compilers (<= 11), we use uint16_t: ref https://github.com/ggml-org/llama.cpp/pull/10616
// for MUSA compilers , we use uint16_t: ref https://github.com/ggml-org/llama.cpp/pull/11843
//
#if defined(__ARM_NEON) && !(defined(__CUDACC__) && __CUDACC_VER_MAJOR__ <= 11) && !defined(__MUSACC__)
#define GGML_CPU_COMPUTE_FP16_TO_FP32(x) neon_compute_fp16_to_fp32(x)
#define GGML_CPU_COMPUTE_FP32_TO_FP16(x) neon_compute_fp32_to_fp16(x)
#define GGML_CPU_FP16_TO_FP32(x) GGML_CPU_COMPUTE_FP16_TO_FP32(x)
static inline float neon_compute_fp16_to_fp32(ggml_fp16_t h) {
__fp16 tmp;
memcpy(&tmp, &h, sizeof(ggml_fp16_t));
return (float)tmp;
}
static inline ggml_fp16_t neon_compute_fp32_to_fp16(float f) {
ggml_fp16_t res;
__fp16 tmp = f;
memcpy(&res, &tmp, sizeof(ggml_fp16_t));
return res;
}
#elif defined(__F16C__)
#ifdef _MSC_VER
#define GGML_CPU_COMPUTE_FP16_TO_FP32(x) _mm_cvtss_f32(_mm_cvtph_ps(_mm_cvtsi32_si128(x)))
#define GGML_CPU_COMPUTE_FP32_TO_FP16(x) _mm_extract_epi16(_mm_cvtps_ph(_mm_set_ss(x), 0), 0)
#else
#define GGML_CPU_COMPUTE_FP16_TO_FP32(x) _cvtsh_ss(x)
#define GGML_CPU_COMPUTE_FP32_TO_FP16(x) _cvtss_sh(x, 0)
#endif
#elif defined(__POWER9_VECTOR__)
#define GGML_CPU_COMPUTE_FP16_TO_FP32(x) power_compute_fp16_to_fp32(x)
#define GGML_CPU_COMPUTE_FP32_TO_FP16(x) power_compute_fp32_to_fp16(x)
/* the inline asm below is about 12% faster than the lookup method */
#define GGML_CPU_FP16_TO_FP32(x) GGML_CPU_COMPUTE_FP16_TO_FP32(x)
#define GGML_CPU_FP32_TO_FP16(x) GGML_CPU_COMPUTE_FP32_TO_FP16(x)
static inline float power_compute_fp16_to_fp32(ggml_fp16_t h) {
float f;
double d;
__asm__(
"mtfprd %0,%2\n"
"xscvhpdp %0,%0\n"
"frsp %1,%0\n" :
/* temp */ "=d"(d),
/* out */ "=f"(f):
/* in */ "r"(h));
return f;
}
static inline ggml_fp16_t power_compute_fp32_to_fp16(float f) {
double d;
ggml_fp16_t r;
__asm__( /* xscvdphp can work on double or single precision */
"xscvdphp %0,%2\n"
"mffprd %1,%0\n" :
/* temp */ "=d"(d),
/* out */ "=r"(r):
/* in */ "f"(f));
return r;
}
#elif defined(__riscv) && defined(__riscv_zfhmin)
static inline float riscv_compute_fp16_to_fp32(ggml_fp16_t h) {
float f;
__asm__(
"fmv.h.x %[f], %[h]\n\t"
"fcvt.s.h %[f], %[f]"
: [f] "=&f" (f)
: [h] "r" (h)
);
return f;
}
static inline ggml_fp16_t riscv_compute_fp32_to_fp16(float f) {
ggml_fp16_t res;
__asm__(
"fcvt.h.s %[f], %[f]\n\t"
"fmv.x.h %[h], %[f]"
: [h] "=&r" (res)
: [f] "f" (f)
);
return res;
}
#define GGML_CPU_COMPUTE_FP16_TO_FP32(x) riscv_compute_fp16_to_fp32(x)
#define GGML_CPU_COMPUTE_FP32_TO_FP16(x) riscv_compute_fp32_to_fp16(x)
#define GGML_CPU_FP16_TO_FP32(x) GGML_CPU_COMPUTE_FP16_TO_FP32(x)
#define GGML_CPU_FP32_TO_FP16(x) GGML_CPU_COMPUTE_FP32_TO_FP16(x)
#elif defined(__NNPA__)
#define GGML_CPU_COMPUTE_FP16_TO_FP32(x) nnpa_compute_fp16_to_fp32(x)
#define GGML_CPU_COMPUTE_FP32_TO_FP16(x) nnpa_compute_fp32_to_fp16(x)
#define GGML_CPU_FP16_TO_FP32(x) GGML_CPU_COMPUTE_FP16_TO_FP32(x)
#define GGML_CPU_FP32_TO_FP16(x) GGML_CPU_COMPUTE_FP32_TO_FP16(x)
static inline float nnpa_compute_fp16_to_fp32(ggml_fp16_t h) {
uint16x8_t v_h = vec_splats(h);
uint16x8_t v_hd = vec_convert_from_fp16(v_h, 0);
return vec_extend_to_fp32_hi(v_hd, 0)[0];
}
static inline ggml_fp16_t nnpa_compute_fp32_to_fp16(float f) {
float32x4_t v_f = vec_splats(f);
float32x4_t v_zero = vec_splats(0.0f);
uint16x8_t v_hd = vec_round_from_fp32(v_f, v_zero, 0);
uint16x8_t v_h = vec_convert_to_fp16(v_hd, 0);
return vec_extract(v_h, 0);
}
#endif
// precomputed f32 table for f16 (256 KB)
// defined in ggml-cpu.c, initialized in ggml_cpu_init()
extern float ggml_table_f32_f16[1 << 16];
// On ARM NEON, it's quicker to directly convert x -> x instead of calling into ggml_lookup_fp16_to_fp32,
// so we define GGML_CPU_FP16_TO_FP32 and GGML_CPU_FP32_TO_FP16 elsewhere for NEON.
// This is also true for POWER9.
#if !defined(GGML_CPU_FP16_TO_FP32)
inline static float ggml_lookup_fp16_to_fp32(ggml_fp16_t f) {
uint16_t s;
memcpy(&s, &f, sizeof(uint16_t));
return ggml_table_f32_f16[s];
}
#define GGML_CPU_FP16_TO_FP32(x) ggml_lookup_fp16_to_fp32(x)
#endif
#if !defined(GGML_CPU_FP32_TO_FP16)
#define GGML_CPU_FP32_TO_FP16(x) GGML_COMPUTE_FP32_TO_FP16(x)
#endif
// we define a common set of C macros which map to specific intrinsics based on the current architecture
// we then implement the fundamental computation operations below using only these macros
// adding support for new architectures requires to define the corresponding SIMD macros
@ -415,7 +572,7 @@ static inline __m256 __avx_f32cx8_load(const ggml_fp16_t * x) {
float tmp[8];
for (int i = 0; i < 8; i++) {
tmp[i] = GGML_FP16_TO_FP32(x[i]);
tmp[i] = GGML_CPU_FP16_TO_FP32(x[i]);
}
return _mm256_loadu_ps(tmp);
@ -426,7 +583,7 @@ static inline void __avx_f32cx8_store(ggml_fp16_t *x, __m256 y) {
_mm256_storeu_ps(arr, y);
for (int i = 0; i < 8; i++)
x[i] = GGML_FP32_TO_FP16(arr[i]);
x[i] = GGML_CPU_FP32_TO_FP16(arr[i]);
}
#define GGML_F32Cx8_LOAD(x) __avx_f32cx8_load(x)
#define GGML_F32Cx8_STORE(x, y) __avx_f32cx8_store(x, y)
@ -574,10 +731,10 @@ static inline unsigned char ggml_endian_byte(int i) {
inline static v128_t __wasm_f16x4_load(const ggml_fp16_t * p) {
float tmp[4];
tmp[0] = GGML_FP16_TO_FP32(p[0]);
tmp[1] = GGML_FP16_TO_FP32(p[1]);
tmp[2] = GGML_FP16_TO_FP32(p[2]);
tmp[3] = GGML_FP16_TO_FP32(p[3]);
tmp[0] = GGML_CPU_FP16_TO_FP32(p[0]);
tmp[1] = GGML_CPU_FP16_TO_FP32(p[1]);
tmp[2] = GGML_CPU_FP16_TO_FP32(p[2]);
tmp[3] = GGML_CPU_FP16_TO_FP32(p[3]);
return wasm_v128_load(tmp);
}
@ -587,10 +744,10 @@ inline static void __wasm_f16x4_store(ggml_fp16_t * p, v128_t x) {
wasm_v128_store(tmp, x);
p[0] = GGML_FP32_TO_FP16(tmp[0]);
p[1] = GGML_FP32_TO_FP16(tmp[1]);
p[2] = GGML_FP32_TO_FP16(tmp[2]);
p[3] = GGML_FP32_TO_FP16(tmp[3]);
p[0] = GGML_CPU_FP32_TO_FP16(tmp[0]);
p[1] = GGML_CPU_FP32_TO_FP16(tmp[1]);
p[2] = GGML_CPU_FP32_TO_FP16(tmp[2]);
p[3] = GGML_CPU_FP32_TO_FP16(tmp[3]);
}
#define GGML_F16x4 v128_t
@ -690,10 +847,10 @@ inline static void __wasm_f16x4_store(ggml_fp16_t * p, v128_t x) {
static inline __m128 __sse_f16x4_load(const ggml_fp16_t * x) {
float tmp[4];
tmp[0] = GGML_FP16_TO_FP32(x[0]);
tmp[1] = GGML_FP16_TO_FP32(x[1]);
tmp[2] = GGML_FP16_TO_FP32(x[2]);
tmp[3] = GGML_FP16_TO_FP32(x[3]);
tmp[0] = GGML_CPU_FP16_TO_FP32(x[0]);
tmp[1] = GGML_CPU_FP16_TO_FP32(x[1]);
tmp[2] = GGML_CPU_FP16_TO_FP32(x[2]);
tmp[3] = GGML_CPU_FP16_TO_FP32(x[3]);
return _mm_loadu_ps(tmp);
}
@ -703,10 +860,10 @@ static inline void __sse_f16x4_store(ggml_fp16_t * x, __m128 y) {
_mm_storeu_ps(arr, y);
x[0] = GGML_FP32_TO_FP16(arr[0]);
x[1] = GGML_FP32_TO_FP16(arr[1]);
x[2] = GGML_FP32_TO_FP16(arr[2]);
x[3] = GGML_FP32_TO_FP16(arr[3]);
x[0] = GGML_CPU_FP32_TO_FP16(arr[0]);
x[1] = GGML_CPU_FP32_TO_FP16(arr[1]);
x[2] = GGML_CPU_FP32_TO_FP16(arr[2]);
x[3] = GGML_CPU_FP32_TO_FP16(arr[3]);
}
#define GGML_F32Cx4 __m128
@ -828,7 +985,7 @@ static inline void __lasx_f32cx8_store(ggml_fp16_t * x, __m256 y) {
#define GGML_F32x4_ZERO __lsx_vldi(0)
#define GGML_F32x4_SET1(x) __lsx_vinsgr2vr_w(__lsx_vldi(0),(x), 0)
#define GGML_F32x4_LOAD(x) __lsx_vld((x), 0)
#define GGML_F32x4_STORE((x),(y)) __lsx_vst((y), (x), 0)
#define GGML_F32x4_STORE(x, y) __lsx_vst(y, x, 0)
#define GGML_F32x4_FMA(a, b, c) __lsx_vfmadd_s(b, c, a)
#define GGML_F32x4_ADD __lsx_vfadd_s
#define GGML_F32x4_MUL __lsx_vfmul_s
@ -874,10 +1031,10 @@ static inline void __lasx_f32cx8_store(ggml_fp16_t * x, __m256 y) {
static inline __m128 __lsx_f16x4_load(const ggml_fp16_t * x) {
float tmp[4];
tmp[0] = GGML_FP16_TO_FP32(x[0]);
tmp[1] = GGML_FP16_TO_FP32(x[1]);
tmp[2] = GGML_FP16_TO_FP32(x[2]);
tmp[3] = GGML_FP16_TO_FP32(x[3]);
tmp[0] = GGML_CPU_FP16_TO_FP32(x[0]);
tmp[1] = GGML_CPU_FP16_TO_FP32(x[1]);
tmp[2] = GGML_CPU_FP16_TO_FP32(x[2]);
tmp[3] = GGML_CPU_FP16_TO_FP32(x[3]);
return __lsx_vld(tmp, 0);
}
@ -887,10 +1044,10 @@ static inline void __lsx_f16x4_store(ggml_fp16_t * x, __m128 y) {
__lsx_vst(y, arr, 0);
x[0] = GGML_FP32_TO_FP16(arr[0]);
x[1] = GGML_FP32_TO_FP16(arr[1]);
x[2] = GGML_FP32_TO_FP16(arr[2]);
x[3] = GGML_FP32_TO_FP16(arr[3]);
x[0] = GGML_CPU_FP32_TO_FP16(arr[0]);
x[1] = GGML_CPU_FP32_TO_FP16(arr[1]);
x[2] = GGML_CPU_FP32_TO_FP16(arr[2]);
x[3] = GGML_CPU_FP32_TO_FP16(arr[3]);
}
#define GGML_F32Cx4 __m128
@ -922,7 +1079,7 @@ static inline void __lsx_f16x4_store(ggml_fp16_t * x, __m128 y) {
#define GGML_F32_STEP 32
#define GGML_F32_EPR 4
#define GGML_F32x4 __vector float
#define GGML_F32x4 float32x4_t
#define GGML_F32x4_ZERO vec_splats(0.0f)
#define GGML_F32x4_SET1 vec_splats
#define GGML_F32x4_LOAD(p) vec_xl(0, p)
@ -962,28 +1119,45 @@ static inline void __lsx_f16x4_store(ggml_fp16_t * x, __m128 y) {
#define GGML_F16_STEP GGML_F32_STEP
#define GGML_F16_EPR GGML_F32_EPR
static inline __vector float __lzs_f16cx4_load(const ggml_fp16_t * x) {
static inline float32x4_t __lzs_f16cx4_load(const ggml_fp16_t * x) {
#if defined(__NNPA__)
uint16x8_t v_x = vec_xl(0, (const ggml_fp16_t *)x);
uint16x8_t v_xd = vec_convert_from_fp16(v_x, 0);
return vec_extend_to_fp32_hi(v_xd, 0);
#else
float tmp[4];
for (int i = 0; i < 4; i++) {
tmp[i] = GGML_FP16_TO_FP32(x[i]);
tmp[i] = GGML_CPU_FP16_TO_FP32(x[i]);
}
// note: keep type-cast here to prevent compiler bugs
// see: https://github.com/ggml-org/llama.cpp/issues/12846
return vec_xl(0, (const float *)(tmp));
#endif
}
static inline void __lzs_f16cx4_store(ggml_fp16_t * x, __vector float y) {
static inline void __lzs_f16cx4_store(ggml_fp16_t * x, float32x4_t v_y) {
#if defined(__NNPA__)
float32x4_t v_zero = vec_splats(0.0f);
uint16x8_t v_xd = vec_round_from_fp32(v_y, v_zero, 0);
uint16x8_t v_x = vec_convert_to_fp16(v_xd, 0);
x[0] = vec_extract(v_x, 0);
x[1] = vec_extract(v_x, 1);
x[2] = vec_extract(v_x, 2);
x[3] = vec_extract(v_x, 3);
#else
float arr[4];
// note: keep type-cast here to prevent compiler bugs
// see: https://github.com/ggml-org/llama.cpp/issues/12846
vec_xst(y, 0, (float *)(arr));
vec_xst(v_y, 0, (float *)(arr));
for (int i = 0; i < 4; i++) {
x[i] = GGML_FP32_TO_FP16(arr[i]);
x[i] = GGML_CPU_FP32_TO_FP16(arr[i]);
}
#endif
}
#define GGML_F16_VEC GGML_F32x4
@ -1004,3 +1178,7 @@ static inline void __lzs_f16cx4_store(ggml_fp16_t * x, __vector float y) {
#define GGML_F32_ARR (GGML_F32_STEP/GGML_F32_EPR)
#define GGML_F16_ARR (GGML_F16_STEP/GGML_F16_EPR)
#endif
#ifdef __cplusplus
}
#endif

4
ggml/src/ggml-cpu/vec.cpp
View File

@ -219,11 +219,11 @@ void ggml_vec_dot_f16(int n, float * GGML_RESTRICT s, size_t bs, ggml_fp16_t * G
// leftovers
for (int i = np; i < n; ++i) {
sumf += (ggml_float)(GGML_FP16_TO_FP32(x[i])*GGML_FP16_TO_FP32(y[i]));
sumf += (ggml_float)(GGML_CPU_FP16_TO_FP32(x[i])*GGML_CPU_FP16_TO_FP32(y[i]));
}
#else
for (int i = 0; i < n; ++i) {
sumf += (ggml_float)(GGML_FP16_TO_FP32(x[i])*GGML_FP16_TO_FP32(y[i]));
sumf += (ggml_float)(GGML_CPU_FP16_TO_FP32(x[i])*GGML_CPU_FP16_TO_FP32(y[i]));
}
#endif

90
ggml/src/ggml-cpu/vec.h
View File

@ -58,7 +58,7 @@ inline static void ggml_vec_set_bf16(const int n, ggml_bf16_t * x, const ggml_bf
inline static void ggml_vec_add_f32 (const int n, float * z, const float * x, const float * y) { for (int i = 0; i < n; ++i) z[i] = x[i] + y[i]; }
inline static void ggml_vec_add_f16 (const int n, ggml_fp16_t * z, const ggml_fp16_t * x, const ggml_fp16_t * y) {
for (int i = 0; i < n; ++i) {
z[i] = GGML_FP32_TO_FP16(GGML_FP16_TO_FP32(x[i]) + GGML_FP16_TO_FP32(y[i]));
z[i] = GGML_CPU_FP32_TO_FP16(GGML_CPU_FP16_TO_FP32(x[i]) + GGML_CPU_FP16_TO_FP32(y[i]));
}
}
inline static void ggml_vec_add1_f32(const int n, float * z, const float * x, const float v) { for (int i = 0; i < n; ++i) z[i] = x[i] + v; }
@ -67,7 +67,7 @@ inline static void ggml_vec_acc1_f32(const int n, float * y, const float v)
inline static void ggml_vec_sub_f32 (const int n, float * z, const float * x, const float * y) { for (int i = 0; i < n; ++i) z[i] = x[i] - y[i]; }
inline static void ggml_vec_sub_f16 (const int n, ggml_fp16_t * z, const ggml_fp16_t * x, const ggml_fp16_t * y) {
for (int i = 0; i < n; ++i) {
z[i] = GGML_FP32_TO_FP16(GGML_FP16_TO_FP32(x[i]) - GGML_FP16_TO_FP32(y[i]));
z[i] = GGML_CPU_FP32_TO_FP16(GGML_CPU_FP16_TO_FP32(x[i]) - GGML_CPU_FP16_TO_FP32(y[i]));
}
}
inline static void ggml_vec_set_f32 (const int n, float * x, const float v) { for (int i = 0; i < n; ++i) x[i] = v; }
@ -75,20 +75,20 @@ inline static void ggml_vec_cpy_f32 (const int n, float * y, const float * x)
inline static void ggml_vec_neg_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = -x[i]; }
inline static void ggml_vec_neg_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(-GGML_FP16_TO_FP32(x[i]));
y[i] = GGML_CPU_FP32_TO_FP16(-GGML_CPU_FP16_TO_FP32(x[i]));
}
}
inline static void ggml_vec_mul_f32 (const int n, float * z, const float * x, const float * y) { for (int i = 0; i < n; ++i) z[i] = x[i]*y[i]; }
inline static void ggml_vec_mul_f16 (const int n, ggml_fp16_t * z, const ggml_fp16_t * x, const ggml_fp16_t * y) {
for (int i = 0; i < n; ++i) {
z[i] = GGML_FP32_TO_FP16(GGML_FP16_TO_FP32(x[i]) * GGML_FP16_TO_FP32(y[i]));
z[i] = GGML_CPU_FP32_TO_FP16(GGML_CPU_FP16_TO_FP32(x[i]) * GGML_CPU_FP16_TO_FP32(y[i]));
}
}
inline static void ggml_vec_div_f32 (const int n, float * z, const float * x, const float * y) { for (int i = 0; i < n; ++i) z[i] = x[i]/y[i]; }
inline static void ggml_vec_div_f16 (const int n, ggml_fp16_t * z, const ggml_fp16_t * x, const ggml_fp16_t * y) {
for (int i = 0; i < n; ++i) {
z[i] = GGML_FP32_TO_FP16(GGML_FP16_TO_FP32(x[i]) / GGML_FP16_TO_FP32(y[i]));
z[i] = GGML_CPU_FP32_TO_FP16(GGML_CPU_FP16_TO_FP32(x[i]) / GGML_CPU_FP16_TO_FP32(y[i]));
}
}
@ -131,13 +131,13 @@ inline static void ggml_vec_dot_f16_unroll(const int n, const int xs, float * GG
// leftovers
for (int i = np; i < n; ++i) {
for (int j = 0; j < GGML_VEC_DOT_UNROLL; ++j) {
sumf[j] += (ggml_float)(GGML_FP16_TO_FP32(x[j][i])*GGML_FP16_TO_FP32(y[i]));
sumf[j] += (ggml_float)(GGML_CPU_FP16_TO_FP32(x[j][i])*GGML_CPU_FP16_TO_FP32(y[i]));
}
}
#else
for (int i = 0; i < n; ++i) {
for (int j = 0; j < GGML_VEC_DOT_UNROLL; ++j) {
sumf[j] += (ggml_float)(GGML_FP16_TO_FP32(x[j][i])*GGML_FP16_TO_FP32(y[i]));
sumf[j] += (ggml_float)(GGML_CPU_FP16_TO_FP32(x[j][i])*GGML_CPU_FP16_TO_FP32(y[i]));
}
}
#endif
@ -280,12 +280,12 @@ inline static void ggml_vec_mad_f16(const int n, ggml_fp16_t * GGML_RESTRICT y,
// leftovers
for (int i = np; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(GGML_FP16_TO_FP32(y[i]) + GGML_FP16_TO_FP32(x[i])*v);
y[i] = GGML_CPU_FP32_TO_FP16(GGML_CPU_FP16_TO_FP32(y[i]) + GGML_CPU_FP16_TO_FP32(x[i])*v);
}
#else
// scalar
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(GGML_FP16_TO_FP32(y[i]) + GGML_FP16_TO_FP32(x[i])*v);
y[i] = GGML_CPU_FP32_TO_FP16(GGML_CPU_FP16_TO_FP32(y[i]) + GGML_CPU_FP16_TO_FP32(x[i])*v);
}
#endif
}
@ -430,12 +430,12 @@ inline static void ggml_vec_scale_f16(const int n, ggml_fp16_t * y, const float
// leftovers
for (int i = np; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(GGML_FP16_TO_FP32(y[i])*v);
y[i] = GGML_CPU_FP32_TO_FP16(GGML_CPU_FP16_TO_FP32(y[i])*v);
}
#else
// scalar
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(GGML_FP16_TO_FP32(y[i])*v);
y[i] = GGML_CPU_FP32_TO_FP16(GGML_CPU_FP16_TO_FP32(y[i])*v);
}
#endif
}
@ -444,103 +444,103 @@ inline static void ggml_vec_norm_f32 (const int n, float * s, const float * x) {
inline static void ggml_vec_sqr_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = x[i]*x[i]; }
inline static void ggml_vec_sqr_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
float v = GGML_FP16_TO_FP32(x[i]);
y[i] = GGML_FP32_TO_FP16(v*v);
float v = GGML_CPU_FP16_TO_FP32(x[i]);
y[i] = GGML_CPU_FP32_TO_FP16(v*v);
}
}
inline static void ggml_vec_sqrt_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = sqrtf(x[i]); }
inline static void ggml_vec_sqrt_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(sqrtf(GGML_FP16_TO_FP32(x[i])));
y[i] = GGML_CPU_FP32_TO_FP16(sqrtf(GGML_CPU_FP16_TO_FP32(x[i])));
}
}
inline static void ggml_vec_log_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = logf(x[i]); }
inline static void ggml_vec_log_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(logf(GGML_FP16_TO_FP32(x[i])));
y[i] = GGML_CPU_FP32_TO_FP16(logf(GGML_CPU_FP16_TO_FP32(x[i])));
}
}
inline static void ggml_vec_sin_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = sinf(x[i]); }
inline static void ggml_vec_sin_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(sinf(GGML_FP16_TO_FP32(x[i])));
y[i] = GGML_CPU_FP32_TO_FP16(sinf(GGML_CPU_FP16_TO_FP32(x[i])));
}
}
inline static void ggml_vec_cos_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = cosf(x[i]); }
inline static void ggml_vec_cos_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(cosf(GGML_FP16_TO_FP32(x[i])));
y[i] = GGML_CPU_FP32_TO_FP16(cosf(GGML_CPU_FP16_TO_FP32(x[i])));
}
}
inline static void ggml_vec_abs_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = fabsf(x[i]); }
inline static void ggml_vec_abs_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(fabsf(GGML_FP16_TO_FP32(x[i])));
y[i] = GGML_CPU_FP32_TO_FP16(fabsf(GGML_CPU_FP16_TO_FP32(x[i])));
}
}
inline static void ggml_vec_sgn_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = (x[i] > 0.f) ? 1.f : ((x[i] < 0.f) ? -1.f : 0.f); }
inline static void ggml_vec_sgn_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
float v = GGML_FP16_TO_FP32(x[i]);
y[i] = GGML_FP32_TO_FP16((v > 0.f) ? 1.f : ((v < 0.f) ? -1.f : 0.f));
float v = GGML_CPU_FP16_TO_FP32(x[i]);
y[i] = GGML_CPU_FP32_TO_FP16((v > 0.f) ? 1.f : ((v < 0.f) ? -1.f : 0.f));
}
}
inline static void ggml_vec_step_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = (x[i] > 0.f) ? 1.f : 0.f; }
inline static void ggml_vec_step_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16((GGML_FP16_TO_FP32(x[i]) > 0.f) ? 1.f : 0.f);
y[i] = GGML_CPU_FP32_TO_FP16((GGML_CPU_FP16_TO_FP32(x[i]) > 0.f) ? 1.f : 0.f);
}
}
inline static void ggml_vec_tanh_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = tanhf(x[i]); }
inline static void ggml_vec_tanh_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(tanhf(GGML_FP16_TO_FP32(x[i])));
y[i] = GGML_CPU_FP32_TO_FP16(tanhf(GGML_CPU_FP16_TO_FP32(x[i])));
}
}
inline static void ggml_vec_elu_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = (x[i] > 0.f) ? x[i] : expm1f(x[i]); }
inline static void ggml_vec_elu_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(expm1f(GGML_FP16_TO_FP32(x[i])));
y[i] = GGML_CPU_FP32_TO_FP16(expm1f(GGML_CPU_FP16_TO_FP32(x[i])));
}
}
inline static void ggml_vec_relu_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = (x[i] > 0.f) ? x[i] : 0.f; }
inline static void ggml_vec_relu_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
float v = GGML_FP16_TO_FP32(x[i]);
y[i] = GGML_FP32_TO_FP16((v > 0.f) ? v : 0.f);
float v = GGML_CPU_FP16_TO_FP32(x[i]);
y[i] = GGML_CPU_FP32_TO_FP16((v > 0.f) ? v : 0.f);
}
}
inline static void ggml_vec_leaky_relu_f32 (const int n, float * y, const float * x, const float ns) { for (int i = 0; i < n; ++i) y[i] = ((x[i] > 0.f) ? x[i] : 0.f) + ns * ((x[i] < 0.0f) ? x[i] : 0.f); }
inline static void ggml_vec_leaky_relu_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x, const float ns) {
for (int i = 0; i < n; ++i) {
float v = GGML_FP16_TO_FP32(x[i]);
y[i] = GGML_FP32_TO_FP16(((v > 0.f) ? v : 0.f) + ns * ((v < 0.0f) ? v : 0.f));
float v = GGML_CPU_FP16_TO_FP32(x[i]);
y[i] = GGML_CPU_FP32_TO_FP16(((v > 0.f) ? v : 0.f) + ns * ((v < 0.0f) ? v : 0.f));
}
}
inline static void ggml_vec_sigmoid_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = 1.f / (1.f + expf(-x[i])); }
inline static void ggml_vec_sigmoid_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(1.f / (1.f + expf(-GGML_FP16_TO_FP32(x[i]))));
y[i] = GGML_CPU_FP32_TO_FP16(1.f / (1.f + expf(-GGML_CPU_FP16_TO_FP32(x[i]))));
}
}
// TODO: optimize performance
inline static void ggml_vec_hardswish_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = x[i] * fminf(1.0f, fmaxf(0.0f, (x[i] + 3.0f) / 6.0f)); }
inline static void ggml_vec_hardswish_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
float v = GGML_FP16_TO_FP32(x[i]);
y[i] = GGML_FP32_TO_FP16(v * fminf(1.0f, fmaxf(0.0f, (v + 3.0f) / 6.0f)));
float v = GGML_CPU_FP16_TO_FP32(x[i]);
y[i] = GGML_CPU_FP32_TO_FP16(v * fminf(1.0f, fmaxf(0.0f, (v + 3.0f) / 6.0f)));
}
}
inline static void ggml_vec_hardsigmoid_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = fminf(1.0f, fmaxf(0.0f, (x[i] + 3.0f) / 6.0f)); }
inline static void ggml_vec_hardsigmoid_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(fminf(1.0f, fmaxf(0.0f, (GGML_FP16_TO_FP32(x[i]) + 3.0f) / 6.0f)));
y[i] = GGML_CPU_FP32_TO_FP16(fminf(1.0f, fmaxf(0.0f, (GGML_CPU_FP16_TO_FP32(x[i]) + 3.0f) / 6.0f)));
}
}
inline static void ggml_vec_exp_f32 (const int n, float * y, const float * x) { for (int i = 0; i < n; ++i) y[i] = expf(x[i]); }
inline static void ggml_vec_exp_f16 (const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
y[i] = GGML_FP32_TO_FP16(expf(GGML_FP16_TO_FP32(x[i])));
y[i] = GGML_CPU_FP32_TO_FP16(expf(GGML_CPU_FP16_TO_FP32(x[i])));
}
}
@ -562,9 +562,9 @@ inline static void ggml_vec_gelu_f16(const int n, ggml_fp16_t * y, const ggml_fp
inline static void ggml_vec_gelu_erf_f16(const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
float xi = GGML_FP16_TO_FP32(x[i]);
float xi = GGML_CPU_FP16_TO_FP32(x[i]);
float res = 0.5f*xi*(1.0f + erff(xi*SQRT_2_INV));
y[i] = GGML_FP32_TO_FP16(res);
y[i] = GGML_CPU_FP32_TO_FP16(res);
}
}
@ -577,9 +577,9 @@ inline static void ggml_vec_gelu_f32(const int n, float * y, const float * x) {
} else if (x[i] >= 10.0f) {
y[i] = x[i];
} else {
ggml_fp16_t fp16 = GGML_FP32_TO_FP16(x[i]);
ggml_fp16_t fp16 = GGML_CPU_FP32_TO_FP16(x[i]);
memcpy(&t, &fp16, sizeof(uint16_t));
y[i] = GGML_FP16_TO_FP32(ggml_table_gelu_f16[t]);
y[i] = GGML_CPU_FP16_TO_FP32(ggml_table_gelu_f16[t]);
}
}
}
@ -613,9 +613,9 @@ inline static float ggml_gelu_quick_f32(float x) {
inline static void ggml_vec_gelu_quick_f32(const int n, float * y, const float * x) {
uint16_t t;
for (int i = 0; i < n; ++i) {
ggml_fp16_t fp16 = GGML_FP32_TO_FP16(x[i]);
ggml_fp16_t fp16 = GGML_CPU_FP32_TO_FP16(x[i]);
memcpy(&t, &fp16, sizeof(uint16_t));
y[i] = GGML_FP16_TO_FP32(ggml_table_gelu_quick_f16[t]);
y[i] = GGML_CPU_FP16_TO_FP32(ggml_table_gelu_quick_f16[t]);
}
}
#else
@ -628,8 +628,8 @@ inline static void ggml_vec_gelu_quick_f32(const int n, float * y, const float *
inline static void ggml_vec_gelu_quick_f16(const int n, ggml_fp16_t * y, const ggml_fp16_t * x) {
for (int i = 0; i < n; ++i) {
float v = GGML_FP16_TO_FP32(x[i]);
y[i] = GGML_FP32_TO_FP16(v*(1.0f/(1.0f+expf(GELU_QUICK_COEF*v))));
float v = GGML_CPU_FP16_TO_FP32(x[i]);
y[i] = GGML_CPU_FP32_TO_FP16(v*(1.0f/(1.0f+expf(GELU_QUICK_COEF*v))));
}
}
@ -638,8 +638,8 @@ inline static float ggml_silu_f32(float x) {
return x/(1.0f + expf(-x));
}
inline static ggml_fp16_t ggml_silu_f16(ggml_fp16_t x) {
float v = GGML_FP16_TO_FP32(x);
return GGML_FP32_TO_FP16(v/(1.0f + expf(-v)));
float v = GGML_CPU_FP16_TO_FP32(x);
return GGML_CPU_FP32_TO_FP16(v/(1.0f + expf(-v)));
}
#if __FINITE_MATH_ONLY__
@ -888,9 +888,9 @@ inline static float ggml_silu_backward_f32(float x, float dy) {
}
inline static ggml_fp16_t ggml_silu_backward_f16(ggml_fp16_t x, ggml_fp16_t dy) {
const float v = GGML_FP16_TO_FP32(x);
const float v = GGML_CPU_FP16_TO_FP32(x);
const float s = 1.0f/(1.0f + expf(-v));
return GGML_FP32_TO_FP16(GGML_FP16_TO_FP32(dy)*s*(1.0f + v*(1.0f - s)));
return GGML_CPU_FP32_TO_FP16(GGML_CPU_FP16_TO_FP32(dy)*s*(1.0f + v*(1.0f - s)));
}
inline static void ggml_vec_silu_backward_f32(const int n, float * dx, const float * x, const float * dy) {
@ -928,7 +928,7 @@ inline static void ggml_vec_sum_f32_ggf(const int n, ggml_float * s, const float
inline static void ggml_vec_sum_f16_ggf(const int n, float * s, const ggml_fp16_t * x) {
float sum = 0.0f;
for (int i = 0; i < n; ++i) {
sum += GGML_FP16_TO_FP32(x[i]);
sum += GGML_CPU_FP16_TO_FP32(x[i]);
}
*s = sum;
}

262
ggml/src/ggml-impl.h
View File

@ -317,203 +317,81 @@ struct ggml_cgraph ggml_graph_view(struct ggml_cgraph * cgraph, int i0, int i1);
GGML_API void * ggml_aligned_malloc(size_t size);
GGML_API void ggml_aligned_free(void * ptr, size_t size);
// FP16 to FP32 conversion
// FP16 <-> FP32
// ref: https://github.com/Maratyszcza/FP16
// 16-bit float
// on Arm, we use __fp16
// on x86, we use uint16_t
//
// for old CUDA compilers (<= 11), we use uint16_t: ref https://github.com/ggml-org/llama.cpp/pull/10616
// for MUSA compilers , we use uint16_t: ref https://github.com/ggml-org/llama.cpp/pull/11843
//
#if defined(__ARM_NEON) && !(defined(__CUDACC__) && __CUDACC_VER_MAJOR__ <= 11) && !defined(__MUSACC__)
#define GGML_COMPUTE_FP16_TO_FP32(x) ggml_compute_fp16_to_fp32(x)
#define GGML_COMPUTE_FP32_TO_FP16(x) ggml_compute_fp32_to_fp16(x)
#define GGML_FP16_TO_FP32(x) ggml_compute_fp16_to_fp32(x)
static inline float ggml_compute_fp16_to_fp32(ggml_fp16_t h) {
__fp16 tmp;
memcpy(&tmp, &h, sizeof(ggml_fp16_t));
return (float)tmp;
}
static inline ggml_fp16_t ggml_compute_fp32_to_fp16(float f) {
ggml_fp16_t res;
__fp16 tmp = f;
memcpy(&res, &tmp, sizeof(ggml_fp16_t));
return res;
}
#elif defined(__F16C__)
#ifdef _MSC_VER
#define GGML_COMPUTE_FP16_TO_FP32(x) _mm_cvtss_f32(_mm_cvtph_ps(_mm_cvtsi32_si128(x)))
#define GGML_COMPUTE_FP32_TO_FP16(x) _mm_extract_epi16(_mm_cvtps_ph(_mm_set_ss(x), 0), 0)
#else
#define GGML_COMPUTE_FP16_TO_FP32(x) _cvtsh_ss(x)
#define GGML_COMPUTE_FP32_TO_FP16(x) _cvtss_sh(x, 0)
#endif
#elif defined(__POWER9_VECTOR__)
#define GGML_COMPUTE_FP16_TO_FP32(x) ggml_compute_fp16_to_fp32(x)
#define GGML_COMPUTE_FP32_TO_FP16(x) ggml_compute_fp32_to_fp16(x)
/* the inline asm below is about 12% faster than the lookup method */
#define GGML_FP16_TO_FP32(x) GGML_COMPUTE_FP16_TO_FP32(x)
#define GGML_FP32_TO_FP16(x) GGML_COMPUTE_FP32_TO_FP16(x)
static inline float ggml_compute_fp16_to_fp32(ggml_fp16_t h) {
float f;
double d;
__asm__(
"mtfprd %0,%2\n"
"xscvhpdp %0,%0\n"
"frsp %1,%0\n" :
/* temp */ "=d"(d),
/* out */ "=f"(f):
/* in */ "r"(h));
return f;
}
static inline ggml_fp16_t ggml_compute_fp32_to_fp16(float f) {
double d;
ggml_fp16_t r;
__asm__( /* xscvdphp can work on double or single precision */
"xscvdphp %0,%2\n"
"mffprd %1,%0\n" :
/* temp */ "=d"(d),
/* out */ "=r"(r):
/* in */ "f"(f));
return r;
}
#elif defined(__riscv) && defined(__riscv_zfhmin)
static inline float ggml_compute_fp16_to_fp32(ggml_fp16_t h) {
float f;
__asm__(
"fmv.h.x %[f], %[h]\n\t"
"fcvt.s.h %[f], %[f]"
: [f] "=&f" (f)
: [h] "r" (h)
);
return f;
}
static inline ggml_fp16_t ggml_compute_fp32_to_fp16(float f) {
ggml_fp16_t res;
__asm__(
"fcvt.h.s %[f], %[f]\n\t"
"fmv.x.h %[h], %[f]"
: [h] "=&r" (res)
: [f] "f" (f)
);
return res;
}
#define GGML_COMPUTE_FP16_TO_FP32(x) ggml_compute_fp16_to_fp32(x)
#define GGML_COMPUTE_FP32_TO_FP16(x) ggml_compute_fp32_to_fp16(x)
#define GGML_FP16_TO_FP32(x) GGML_COMPUTE_FP16_TO_FP32(x)
#define GGML_FP32_TO_FP16(x) GGML_COMPUTE_FP32_TO_FP16(x)
#else
// FP16 <-> FP32
// ref: https://github.com/Maratyszcza/FP16
static inline float fp32_from_bits(uint32_t w) {
union {
uint32_t as_bits;
float as_value;
} fp32;
fp32.as_bits = w;
return fp32.as_value;
}
static inline uint32_t fp32_to_bits(float f) {
union {
float as_value;
uint32_t as_bits;
} fp32;
fp32.as_value = f;
return fp32.as_bits;
}
static inline float ggml_compute_fp16_to_fp32(ggml_fp16_t h) {
const uint32_t w = (uint32_t) h << 16;
const uint32_t sign = w & UINT32_C(0x80000000);
const uint32_t two_w = w + w;
const uint32_t exp_offset = UINT32_C(0xE0) << 23;
#if (defined(__STDC_VERSION__) && (__STDC_VERSION__ >= 199901L) || defined(__GNUC__) && !defined(__STRICT_ANSI__)) && (!defined(__cplusplus) || __cplusplus >= 201703L)
const float exp_scale = 0x1.0p-112f;
#else
const float exp_scale = fp32_from_bits(UINT32_C(0x7800000));
#endif
const float normalized_value = fp32_from_bits((two_w >> 4) + exp_offset) * exp_scale;
const uint32_t magic_mask = UINT32_C(126) << 23;
const float magic_bias = 0.5f;
const float denormalized_value = fp32_from_bits((two_w >> 17) | magic_mask) - magic_bias;
const uint32_t denormalized_cutoff = UINT32_C(1) << 27;
const uint32_t result = sign |
(two_w < denormalized_cutoff ? fp32_to_bits(denormalized_value) : fp32_to_bits(normalized_value));
return fp32_from_bits(result);
}
static inline ggml_fp16_t ggml_compute_fp32_to_fp16(float f) {
#if (defined(__STDC_VERSION__) && (__STDC_VERSION__ >= 199901L) || defined(__GNUC__) && !defined(__STRICT_ANSI__)) && (!defined(__cplusplus) || __cplusplus >= 201703L)
const float scale_to_inf = 0x1.0p+112f;
const float scale_to_zero = 0x1.0p-110f;
#else
const float scale_to_inf = fp32_from_bits(UINT32_C(0x77800000));
const float scale_to_zero = fp32_from_bits(UINT32_C(0x08800000));
#endif
float base = (fabsf(f) * scale_to_inf) * scale_to_zero;
const uint32_t w = fp32_to_bits(f);
const uint32_t shl1_w = w + w;
const uint32_t sign = w & UINT32_C(0x80000000);
uint32_t bias = shl1_w & UINT32_C(0xFF000000);
if (bias < UINT32_C(0x71000000)) {
bias = UINT32_C(0x71000000);
}
base = fp32_from_bits((bias >> 1) + UINT32_C(0x07800000)) + base;
const uint32_t bits = fp32_to_bits(base);
const uint32_t exp_bits = (bits >> 13) & UINT32_C(0x00007C00);
const uint32_t mantissa_bits = bits & UINT32_C(0x00000FFF);
const uint32_t nonsign = exp_bits + mantissa_bits;
return (sign >> 16) | (shl1_w > UINT32_C(0xFF000000) ? UINT16_C(0x7E00) : nonsign);
}
#define GGML_COMPUTE_FP16_TO_FP32(x) ggml_compute_fp16_to_fp32(x)
#define GGML_COMPUTE_FP32_TO_FP16(x) ggml_compute_fp32_to_fp16(x)
#endif // defined(__ARM_NEON) && !(defined(__CUDACC__) && __CUDACC_VER_MAJOR__ <= 11) && !defined(__MUSACC__)
// precomputed f32 table for f16 (256 KB)
// defined in ggml.c, initialized in ggml_init()
GGML_API float ggml_table_f32_f16[1 << 16];
// On ARM NEON, it's quicker to directly convert x -> x instead of calling into ggml_lookup_fp16_to_fp32,
// so we define GGML_FP16_TO_FP32 and GGML_FP32_TO_FP16 elsewhere for NEON.
// This is also true for POWER9.
#if !defined(GGML_FP16_TO_FP32)
inline static float ggml_lookup_fp16_to_fp32(ggml_fp16_t f) {
uint16_t s;
memcpy(&s, &f, sizeof(uint16_t));
return ggml_table_f32_f16[s];
static inline float fp32_from_bits(uint32_t w) {
union {
uint32_t as_bits;
float as_value;
} fp32;
fp32.as_bits = w;
return fp32.as_value;
}
#define GGML_FP16_TO_FP32(x) ggml_lookup_fp16_to_fp32(x)
#endif
static inline uint32_t fp32_to_bits(float f) {
union {
float as_value;
uint32_t as_bits;
} fp32;
fp32.as_value = f;
return fp32.as_bits;
}
#if !defined(GGML_FP32_TO_FP16)
#define GGML_FP32_TO_FP16(x) GGML_COMPUTE_FP32_TO_FP16(x)
static inline float ggml_compute_fp16_to_fp32(ggml_fp16_t h) {
const uint32_t w = (uint32_t) h << 16;
const uint32_t sign = w & UINT32_C(0x80000000);
const uint32_t two_w = w + w;
const uint32_t exp_offset = UINT32_C(0xE0) << 23;
#if (defined(__STDC_VERSION__) && (__STDC_VERSION__ >= 199901L) || defined(__GNUC__) && !defined(__STRICT_ANSI__)) && (!defined(__cplusplus) || __cplusplus >= 201703L)
const float exp_scale = 0x1.0p-112f;
#else
const float exp_scale = fp32_from_bits(UINT32_C(0x7800000));
#endif
const float normalized_value = fp32_from_bits((two_w >> 4) + exp_offset) * exp_scale;
const uint32_t magic_mask = UINT32_C(126) << 23;
const float magic_bias = 0.5f;
const float denormalized_value = fp32_from_bits((two_w >> 17) | magic_mask) - magic_bias;
const uint32_t denormalized_cutoff = UINT32_C(1) << 27;
const uint32_t result = sign |
(two_w < denormalized_cutoff ? fp32_to_bits(denormalized_value) : fp32_to_bits(normalized_value));
return fp32_from_bits(result);
}
static inline ggml_fp16_t ggml_compute_fp32_to_fp16(float f) {
#if (defined(__STDC_VERSION__) && (__STDC_VERSION__ >= 199901L) || defined(__GNUC__) && !defined(__STRICT_ANSI__)) && (!defined(__cplusplus) || __cplusplus >= 201703L)
const float scale_to_inf = 0x1.0p+112f;
const float scale_to_zero = 0x1.0p-110f;
#else
const float scale_to_inf = fp32_from_bits(UINT32_C(0x77800000));
const float scale_to_zero = fp32_from_bits(UINT32_C(0x08800000));
#endif
float base = (fabsf(f) * scale_to_inf) * scale_to_zero;
const uint32_t w = fp32_to_bits(f);
const uint32_t shl1_w = w + w;
const uint32_t sign = w & UINT32_C(0x80000000);
uint32_t bias = shl1_w & UINT32_C(0xFF000000);
if (bias < UINT32_C(0x71000000)) {
bias = UINT32_C(0x71000000);
}
base = fp32_from_bits((bias >> 1) + UINT32_C(0x07800000)) + base;
const uint32_t bits = fp32_to_bits(base);
const uint32_t exp_bits = (bits >> 13) & UINT32_C(0x00007C00);
const uint32_t mantissa_bits = bits & UINT32_C(0x00000FFF);
const uint32_t nonsign = exp_bits + mantissa_bits;
return (sign >> 16) | (shl1_w > UINT32_C(0xFF000000) ? UINT16_C(0x7E00) : nonsign);
}
#define GGML_COMPUTE_FP16_TO_FP32(x) ggml_compute_fp16_to_fp32(x)
#define GGML_COMPUTE_FP32_TO_FP16(x) ggml_compute_fp32_to_fp16(x)
#define GGML_FP16_TO_FP32(x) GGML_COMPUTE_FP16_TO_FP32(x)
#define GGML_FP32_TO_FP16(x) GGML_COMPUTE_FP32_TO_FP16(x)
/**
* Converts brain16 to float32.

11
ggml/src/ggml.c
View File

@ -61,9 +61,6 @@
#define m512i(p) (__m512i)(p)
#endif
// precomputed f32 table for f16 (256 KB) (ggml-impl.h)
float ggml_table_f32_f16[1 << 16];
#if defined(__linux__) || \
defined(__FreeBSD__) || defined(__NetBSD__) || defined(__OpenBSD__) || \
(defined(__APPLE__) && !TARGET_OS_TV && !TARGET_OS_WATCH)
@ -1422,14 +1419,6 @@ struct ggml_context * ggml_init(struct ggml_init_params params) {
// initialize time system (required on Windows)
ggml_time_init();
for (int i = 0; i < (1 << 16); ++i) {
union {
uint16_t u16;
ggml_fp16_t fp16;
} u = {i};
ggml_table_f32_f16[i] = GGML_COMPUTE_FP16_TO_FP32(u.fp16);
}
is_first_call = false;
}