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b284197df426fb189cdcfe56a43c863a788ac756
llama.cpp/ggml/src/ggml-cuda
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Johannes Gäßler b284197df4 CUDA: fix compilation with GGML_CUDA_F16 (#14837)
2025-07-23 18:22:30 +02:00
..
template-instances
CUDA: FA support for Deepseek (Ampere or newer) (#13306)
2025-05-09 13:34:58 +02:00
vendors
HIP : Add HIP 7.0+ compatibility for hipBLAS compute types (#14634)
2025-07-11 18:55:00 +02:00
acc.cu
llama/ggml: add LLM training support (#10544)
2025-05-12 14:44:49 +02:00
acc.cuh
…
arange.cu
…
arange.cuh
…
argmax.cu
cuda : optimize argmax (#10441)
2024-11-21 18:18:50 +01:00
argmax.cuh
ggml/ex: calculate accuracy in graph, adapt MNIST (ggml/980)
2024-10-03 21:17:26 +03:00
argsort.cu
ggml : reduce hash table reset cost (#8698)
2024-07-27 04:41:55 +02:00
argsort.cuh
…
binbcast.cu
Support pure float16 add/sub/mul/div operations in the CUDA (and CPU) backend (ggml/1121)
2025-03-03 18:18:11 +02:00
binbcast.cuh
ggml/examples: add backend support for numerical optimization (ggml/949)
2024-09-20 21:15:05 +03:00
clamp.cu
cuda: unary ops as float + de-duplicate (ggml/1130)
2025-03-03 18:18:11 +02:00
clamp.cuh
…
CMakeLists.txt
cuda: remove linking to cublasLt (#14790)
2025-07-22 07:45:26 +08:00
common.cuh
musa: fix build warnings (unused variable) (#14561)
2025-07-08 07:58:30 +08:00
concat.cu
musa: fix all warnings, re-enable -DLLAMA_FATAL_WARNINGS=ON in ci and update doc (#12611)
2025-03-30 10:59:38 +02:00
concat.cuh
…
conv2d-dw.cu
CUDA: add conv_2d_dw (#14265)
2025-06-20 09:50:24 +08:00
conv2d-dw.cuh
CUDA: add conv_2d_dw (#14265)
2025-06-20 09:50:24 +08:00
conv2d-transpose.cu
CUDA: add conv_2d_transpose (#14287)
2025-06-20 22:48:24 +08:00
conv2d-transpose.cuh
CUDA: add conv_2d_transpose (#14287)
2025-06-20 22:48:24 +08:00
conv-transpose-1d.cu
musa: fix all warnings, re-enable -DLLAMA_FATAL_WARNINGS=ON in ci and update doc (#12611)
2025-03-30 10:59:38 +02:00
conv-transpose-1d.cuh
feat: cuda implementation for ggml_conv_transpose_1d (ggml/854)
2024-07-08 12:23:00 +03:00
convert.cu
CUDA: fix compilation with GGML_CUDA_F16 (#14837)
2025-07-23 18:22:30 +02:00
convert.cuh
CUDA: add bf16 and f32 support to cublas_mul_mat_batched (#14361)
2025-06-29 01:30:53 +08:00
count-equal.cu
ggml: fix zero division in ‘dne’ calculation in CUDA COUNT_EQUAL operator when ‘ne’ is small (#10213)
2024-11-09 08:35:46 +01:00
count-equal.cuh
ggml/ex: calculate accuracy in graph, adapt MNIST (ggml/980)
2024-10-03 21:17:26 +03:00
cp-async.cuh
CUDA: FA support for Deepseek (Ampere or newer) (#13306)
2025-05-09 13:34:58 +02:00
cpy-utils.cuh
cuda : implement bf16 cpy ops and enable bf16 cont (#14763)
2025-07-22 12:33:10 +02:00
cpy.cu
cuda : implement bf16 cpy ops and enable bf16 cont (#14763)
2025-07-22 12:33:10 +02:00
cpy.cuh
ggml: Re-enable CUDA graphs in presence of CONT and DUP nodes (#12970)
2025-04-17 15:19:42 +02:00
cross-entropy-loss.cu
CUDA: add dynamic shared mem to softmax, refactor general usage (#14497)
2025-07-03 07:45:11 +08:00
cross-entropy-loss.cuh
ggml/examples: add backend support for numerical optimization (ggml/949)
2024-09-20 21:15:05 +03:00
dequantize.cuh
…
diagmask.cu
…
diagmask.cuh
…
fattn-common.cuh
CUDA: fix quantized KV cache + multiple sequences (#14822)
2025-07-23 14:08:09 +03:00
fattn-mma-f16.cuh
llama : add high-throughput mode (#14363)
2025-07-16 16:35:42 +03:00
fattn-tile-f16.cu
llama : add high-throughput mode (#14363)
2025-07-16 16:35:42 +03:00
fattn-tile-f16.cuh
…
fattn-tile-f32.cu
llama : add high-throughput mode (#14363)
2025-07-16 16:35:42 +03:00
fattn-tile-f32.cuh
…
fattn-vec-f16.cuh
llama : add high-throughput mode (#14363)
2025-07-16 16:35:42 +03:00
fattn-vec-f32.cuh
llama : add high-throughput mode (#14363)
2025-07-16 16:35:42 +03:00
fattn-wmma-f16.cu
llama : add high-throughput mode (#14363)
2025-07-16 16:35:42 +03:00
fattn-wmma-f16.cuh
CUDA: use mma PTX instructions for FlashAttention (#11583)
2025-02-02 19:31:09 +01:00
fattn.cu
CUDA: faster Deepseek FA, add Turing support (#13435)
2025-05-14 16:08:20 +02:00
fattn.cuh
…
getrows.cu
CUDA: add bf16 and i32 to getrows (#14529)
2025-07-07 21:45:43 +08:00
getrows.cuh
CUDA: batched+noncont MMQ, refactor bs>1 MoE code (#13199)
2025-04-30 23:12:59 +02:00
ggml-cuda.cu
CUDA: add fused rms norm (#14800)
2025-07-23 09:25:42 +08:00
gla.cu
llama: add support for QRWKV6 model architecture (#11001)
2025-01-10 09:58:08 +08:00
gla.cuh
llama: add support for QRWKV6 model architecture (#11001)
2025-01-10 09:58:08 +08:00
im2col.cu
vulkan/cuda: Fix im2col when KW!=KH (#14789)
2025-07-21 13:35:40 +02:00
im2col.cuh
…
mean.cu
CUDA: add mean operation (#14313)
2025-06-22 12:39:54 +08:00
mean.cuh
CUDA: add mean operation (#14313)
2025-06-22 12:39:54 +08:00
mma.cuh
musa: fix all warnings, re-enable -DLLAMA_FATAL_WARNINGS=ON in ci and update doc (#12611)
2025-03-30 10:59:38 +02:00
mmq.cu
CUDA: fix crash on large batch size for quant. MoE (#13537)
2025-05-14 16:41:02 +02:00
mmq.cuh
CUDA: add dynamic shared mem to softmax, refactor general usage (#14497)
2025-07-03 07:45:11 +08:00
mmv.cu
CUDA/HIP: optimize mmv paths taken for HIP devices (#14324)
2025-06-24 01:12:56 +02:00
mmv.cuh
CUDA: mul_mat_v support for batch sizes > 1 (#14262)
2025-06-23 13:11:31 +02:00
mmvq.cu
CUDA: fix crash with partial offloading of MoE (#13439)
2025-05-11 16:09:33 +02:00
mmvq.cuh
CUDA: noncont MMVQ + batched bs1 MUL_MAT_ID (#13014)
2025-04-22 21:27:40 +02:00
norm.cu
CUDA: add fused rms norm (#14800)
2025-07-23 09:25:42 +08:00
norm.cuh
CUDA: add fused rms norm (#14800)
2025-07-23 09:25:42 +08:00
opt-step-adamw.cu
ggml: new optimization interface (ggml/988)
2024-11-17 08:30:29 +02:00
opt-step-adamw.cuh
ggml/examples: add backend support for numerical optimization (ggml/949)
2024-09-20 21:15:05 +03:00
out-prod.cu
CPU/CUDA: fix (GQA) mul mat back, add CUDA support (#11380)
2025-01-24 12:38:31 +01:00
out-prod.cuh
ggml/examples: add backend support for numerical optimization (ggml/949)
2024-09-20 21:15:05 +03:00
pad.cu
musa: fix all warnings, re-enable -DLLAMA_FATAL_WARNINGS=ON in ci and update doc (#12611)
2025-03-30 10:59:38 +02:00
pad.cuh
…
pool2d.cu
…
pool2d.cuh
…
quantize.cu
CUDA: fix crash on large batch size for quant. MoE (#13537)
2025-05-14 16:41:02 +02:00
quantize.cuh
CUDA: batched+noncont MMQ, refactor bs>1 MoE code (#13199)
2025-04-30 23:12:59 +02:00
rope.cu
cuda : fix rope with partial rotation and non-cont src (#14580)
2025-07-08 10:15:21 +03:00
rope.cuh
RoPE: fix back, CUDA support for back + noncont. (#11240)
2025-01-15 12:51:37 +01:00
scale.cu
ggml : add ggml_scale_bias (#14417)
2025-07-09 18:16:12 +02:00
scale.cuh
…
set-rows.cu
cuda : implement bf16 cpy ops and enable bf16 cont (#14763)
2025-07-22 12:33:10 +02:00
set-rows.cuh
CUDA: add set rows for f32 and f16 (#14551)
2025-07-12 16:31:38 +03:00
softmax.cu
CUDA: add dynamic shared mem to softmax, refactor general usage (#14497)
2025-07-03 07:45:11 +08:00
softmax.cuh
CUDA: backwards pass for misc. ops, add tests (#11257)
2025-01-16 16:43:38 +01:00
ssm-conv.cu
model : support LiquidAI LFM2 hybrid family (#14620)
2025-07-11 20:27:01 +02:00
ssm-conv.cuh
ggml : faster ssm scan (#10558)
2025-03-31 18:05:13 +02:00
ssm-scan.cu
cuda : support Falcon-H1 state size for SSM_SCAN (#14602)
2025-07-09 23:54:38 -04:00
ssm-scan.cuh
ggml : faster ssm scan (#10558)
2025-03-31 18:05:13 +02:00
sum.cu
llama/ggml: add LLM training support (#10544)
2025-05-12 14:44:49 +02:00
sum.cuh
tests: add gradient tests for all backends (ggml/932)
2024-09-08 11:05:55 +03:00
sumrows.cu
CUDA: add mean operation (#14313)
2025-06-22 12:39:54 +08:00
sumrows.cuh
CUDA: add mean operation (#14313)
2025-06-22 12:39:54 +08:00
tsembd.cu
…
tsembd.cuh
…
unary.cu
cuda : add ELU support (#14657)
2025-07-13 11:33:16 +02:00
unary.cuh
cuda : add ELU support (#14657)
2025-07-13 11:33:16 +02:00
upscale.cu
CUDA: add bilinear interpolation for upscale (#14563)
2025-07-08 10:11:18 +08:00
upscale.cuh
…
vecdotq.cuh
CUDA: noncont MMVQ + batched bs1 MUL_MAT_ID (#13014)
2025-04-22 21:27:40 +02:00
wkv.cu
llama: Add support for RWKV v7 architecture (#12412)
2025-03-18 07:27:50 +08:00
wkv.cuh
llama: Add support for RWKV v7 architecture (#12412)
2025-03-18 07:27:50 +08:00