mirror of
https://github.com/ggml-org/llama.cpp.git
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ggml-cpu: Support s390x SIMD Instruction Set (#12019)
* ggml: add s390x ARCH_FLAGS for compilation
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: add SIMD for s390x using vector intrinsics
SIMD is activated for:
* ggml_vec_dot_f32
* ggml_vec_dot_f16
* ggml_vec_mad_f32
* ggml_vec_mad_f16
* ggml_vec_mad_f32_unroll
* ggml_vec_scale_f32
* ggml_vec_scale_f16
SIMD is NOT activated for:
* ggml_vec_dot_f16_unroll (pending bugfix)
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: fix missing escape character in GGML_F32x4_REDUCE
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: add temporary patch for GGML_F32_ARR and GGML_F16_ARR
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: fix s390x GGML_F32x4_REDUCE
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: full SIMD activation for F32,F16 s390x
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: add option to disable s390x VXE/VXE2
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: change vecintrin.h include to ggml-cpu-impl
* add __VXE__ and __VXE2__ macros
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* cmake: add s390x target detection for VX/VXE/VXE2
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: move s390x vector intrinsics to ggml-cpu-impl.h
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: s390x Q8_0 SIMD
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: correct documentation for Q8_0
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: s390x reduce code complexity Q8_0
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: s390x bugfix typo Q8_0
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: s390x SIMD activated for Q4_1
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: s390x inline vec_reve
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: s390x SIMD activation for Q4_0
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: add VXE backend feature
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: remove test.py
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: s390x SIMD activation for quantize_row_q8_0
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: s390x SIMD activation for quantize_row_q8_1
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: s390x SIMD activation for iq4_xs
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: bugfix iq4_xs
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: s390x SIMD activation for iq4_nl
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: add float, double, and long vector data type
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: clean up iq4_xs SIMD
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: fix improper use of restrict keyword
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: update warning message for ggml_vec_tbl
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: untested implementation of ggml_vec_dot_iq2_xxs_q8_K
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: update ggml_vec_dot_q4_1_q8_1 to use typedefs
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: switch to restrict for iq4_nl
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: slight dot product speed improvement for q4_1_q8_1
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: s390x SIMD activation for q6_K
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: add missing `_t` to ggml_int8x16x4_t
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: fix missing `_t` for ggml_vec_xl_s8x4
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: fix more missing `_t`
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: add unroll and prefetch to Q8_0
increase of 3.86% for prompt processing and 32.22% for token generation
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: patch Q8_0 to use proper vector sizes
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: optimise Q8_0 dot prod compute kernel further
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: add unroll and prefetch to Q4_1
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: refactor Q6_K variable naming for readability
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: fix Q6_K typos
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: s390x SIMD activation for Q5_K
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: fix wrong char*x16_t naming
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: Q5_K y0 wrong signness
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: fix Q5_K invalid uchar type
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: fix Q5_K invalid uchar type
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: s390x SIMD activation for Q4_K
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: fix Q4_K invalid vector intrinsics
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: simplify ggml_padd_s16 compute kernel
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: correct ggml-cpu vxe wording
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: change ggml_aligned_malloc alignment to 256
256 is the cache line size for s390x platforms
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: resolve pr merge via cherry-pick 225bbbf
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml : fix LoongArch compile error with 128-bit SIMD (#11701)
* ggml: resolve pr merge via cherry-pick 4571953
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
* ggml: cmake remove fork when determining s390x machine type
thank you @ericcurtin
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
---------
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
Co-authored-by: Jinyang He <hejinyang@loongson.cn>
Co-authored-by: junchao-zhao <68935141+junchao-loongson@users.noreply.github.com>
This commit is contained in:
Aaron Teo
GitHub
@ -1011,6 +1011,38 @@ void quantize_row_q8_0(const float * restrict x, void * restrict vy, int64_t k)
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__lsx_vst(ni4, (__m128i *)(y[i].qs + 16), 0);
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}
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#elif defined(__VXE__) || defined(__VXE2__)
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for (int i = 0; i < nb; i++) {
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__vector float srcv [8];
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__vector float asrcv[8];
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__vector float amaxv[8];
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for (int j = 0; j < 8; j++) srcv[j] = vec_xl(0, x + i*32 + 4*j);
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for (int j = 0; j < 8; j++) asrcv[j] = vec_abs(srcv[j]);
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for (int j = 0; j < 4; j++) amaxv[2*j] = vec_max(asrcv[2*j], asrcv[2*j+1]);
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for (int j = 0; j < 2; j++) amaxv[4*j] = vec_max(amaxv[4*j], amaxv[4*j+2]);
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for (int j = 0; j < 1; j++) amaxv[8*j] = vec_max(amaxv[8*j], amaxv[8*j+4]);
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const float amax = MAX(MAX(vec_extract(amaxv[0], 0),
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vec_extract(amaxv[0], 1)),
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MAX(vec_extract(amaxv[0], 2),
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vec_extract(amaxv[0], 3)));
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const float d = amax / ((1 << 7) - 1);
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const float id = d ? 1.0f / d : 0.0f;
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y[i].d = GGML_FP32_TO_FP16(d);
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for (int j = 0; j < 8; j++) {
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const __vector float v = vec_mul(srcv[j], vec_splats(id));
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const __vector int32_t vi = vec_signed(v);
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y[i].qs[4*j + 0] = vec_extract(vi, 0);
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y[i].qs[4*j + 1] = vec_extract(vi, 1);
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y[i].qs[4*j + 2] = vec_extract(vi, 2);
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y[i].qs[4*j + 3] = vec_extract(vi, 3);
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}
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}
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#else
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GGML_UNUSED(nb);
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// scalar
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@ -1337,6 +1369,44 @@ void quantize_row_q8_1(const float * restrict x, void * restrict vy, int64_t k)
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__lsx_vst(ni0, (__m128i *)(y[i].qs + 0), 0);
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__lsx_vst(ni4, (__m128i *)(y[i].qs + 16), 0);
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}
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#elif defined(__VXE__) || defined(__VXE2__)
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for (int i = 0; i < nb; i++) {
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__vector float srcv [8];
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__vector float asrcv[8];
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__vector float amaxv[8];
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for (int j = 0; j < 8; j++) srcv[j] = vec_xl(0, x + i*32 + 4*j);
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for (int j = 0; j < 8; j++) asrcv[j] = vec_abs(srcv[j]);
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for (int j = 0; j < 4; j++) amaxv[2*j] = vec_max(asrcv[2*j], asrcv[2*j+1]);
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for (int j = 0; j < 2; j++) amaxv[4*j] = vec_max(amaxv[4*j], amaxv[4*j+2]);
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for (int j = 0; j < 1; j++) amaxv[8*j] = vec_max(amaxv[8*j], amaxv[8*j+4]);
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const float amax = MAX(MAX(vec_extract(amaxv[0], 0),
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vec_extract(amaxv[0], 1)),
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MAX(vec_extract(amaxv[0], 2),
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vec_extract(amaxv[0], 3)));
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const float d = amax / ((1 << 7) - 1);
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const float id = d ? 1.0f / d : 0.0f;
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y[i].d = GGML_FP32_TO_FP16(d);
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__vector int32_t acc = vec_splats(0);
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for (int j = 0; j < 8; j++) {
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const __vector float v = vec_mul(srcv[j], vec_splats(id));
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const __vector int32_t vi = vec_signed(v);
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y[i].qs[4*j + 0] = vec_extract(vi, 0);
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y[i].qs[4*j + 1] = vec_extract(vi, 1);
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y[i].qs[4*j + 2] = vec_extract(vi, 2);
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y[i].qs[4*j + 3] = vec_extract(vi, 3);
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acc = vec_add(acc, vi);
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}
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y[i].s = GGML_FP32_TO_FP16(d * (acc[0] + acc[1] + acc[2] + acc[3]));
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}
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#else
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GGML_UNUSED(nb);
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// scalar
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@ -2488,6 +2558,37 @@ void ggml_vec_dot_q4_0_q8_0(int n, float * restrict s, size_t bs, const void * r
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}
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sumf = hsum_float_4x4(acc_0, acc_1, acc_2, acc_3);
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#elif defined(__VXE__) || defined(__VXE2__)
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__vector float acc = vec_splats(0.0f);
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const __vector uint8_t v_m = vec_splats((const uint8_t)0x0F);
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const __vector int8_t v_s = vec_splats( (const int8_t)0x08);
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for (; ib < nb; ++ib) {
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const __vector uint8_t v_x = vec_xl(0, x[ib].qs);
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const __vector int8_t v_xl = (const __vector int8_t)(v_x & v_m);
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const __vector int8_t v_xh = (const __vector int8_t)(v_x >> 4);
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const __vector int8_t v_xls = vec_sub(v_xl, v_s);
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const __vector int8_t v_xhs = vec_sub(v_xh, v_s);
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const __vector int8_t v_yl = vec_xl(0 , y[ib].qs);
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const __vector int8_t v_yh = vec_xl(QK8_0/2, y[ib].qs);
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const __vector int16_t v_xylso = vec_mulo(v_xls, v_yl);
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const __vector int16_t v_xylse = vec_mule(v_xls, v_yl);
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const __vector int16_t v_xyhso = vec_mulo(v_xhs, v_yh);
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const __vector int16_t v_xyhse = vec_mule(v_xhs, v_yh);
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__vector int16_t v_xy_ = v_xylso + v_xylse + v_xyhso + v_xyhse; v_xy_ += vec_reve(v_xy_);
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const __vector float v_xy = vec_float(vec_unpackh(v_xy_));
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const __vector float v_d = vec_splats(GGML_FP16_TO_FP32(x[ib].d) * GGML_FP16_TO_FP32(y[ib].d));
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acc = vec_madd(v_xy, v_d, acc);
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}
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sumf = acc[0] + acc[1] + acc[2] + acc[3];
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#endif
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for (; ib < nb; ++ib) {
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int sumi0 = 0;
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@ -2781,6 +2882,35 @@ void ggml_vec_dot_q4_1_q8_1(int n, float * restrict s, size_t bs, const void * r
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}
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sumf = hsum_float_8(acc) + summs;
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#elif defined(__VXE__) || defined(__VXE2__)
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float summs = 0;
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float32x4_t acc = vec_splats(0.0f);
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const uint8x16_t v_m = vec_splat_u8(0x0F);
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#pragma GCC unroll 4
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for (; ib < nb; ++ib) {
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__builtin_prefetch(x[ib].qs, 0, 1);
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__builtin_prefetch(y[ib].qs, 0, 1);
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summs += GGML_FP16_TO_FP32(x[ib].m) * GGML_FP16_TO_FP32(y[ib].s);
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const uint8x16_t v_x = vec_xl(0, x[ib].qs);
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const int8x16_t v_xl = (const int8x16_t)(v_x & v_m);
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const int8x16_t v_xh = (const int8x16_t)(v_x >> 4);
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const int8x16_t v_yl = vec_xl(0 , y[ib].qs);
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const int8x16_t v_yh = vec_xl(QK8_1/2, y[ib].qs);
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const int32x4_t v_xy_ = ggml_vec_dot(ggml_vec_dot(vec_splats(0), v_xl, v_yl), v_xh, v_yh);
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const float32x4_t v_xy = vec_float(v_xy_);
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const float32x4_t v_d = vec_splats(GGML_FP16_TO_FP32(x[ib].d) * GGML_FP16_TO_FP32(y[ib].d));
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acc = vec_madd(v_xy, v_d, acc);
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}
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sumf = acc[0] + acc[1] + acc[2] + acc[3] + summs;
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#endif
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for (; ib < nb; ++ib) {
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int sumi0 = 0;
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@ -3915,6 +4045,27 @@ void ggml_vec_dot_q8_0_q8_0(int n, float * restrict s, size_t bs, const void * r
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}
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sumf = hsum_float_8(acc);
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#elif defined(__VXE__) || defined(__VXE2__)
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__vector float acc = vec_splats(0.0f);
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#pragma GCC unroll 8
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for (; ib < nb; ++ib) {
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__builtin_prefetch(x[ib].qs, 0, 1);
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__builtin_prefetch(y[ib].qs, 0, 1);
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const int8x16_t v_xl = vec_xl(0 , x[ib].qs);
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const int8x16_t v_xh = vec_xl(QK8_0/2, x[ib].qs);
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const int8x16_t v_yl = vec_xl(0 , y[ib].qs);
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const int8x16_t v_yh = vec_xl(QK8_0/2, y[ib].qs);
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const int32x4_t v_xy_ = ggml_vec_dot(ggml_vec_dot(vec_splats(0), v_xl, v_yl), v_xh, v_yh);
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const float32x4_t v_xy = vec_float(v_xy_);
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const float32x4_t v_d = vec_splats(GGML_FP16_TO_FP32(x[ib].d) * GGML_FP16_TO_FP32(y[ib].d));
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acc = vec_madd(v_xy, v_d, acc);
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}
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sumf = acc[0] + acc[1] + acc[2] + acc[3];
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#endif
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for (; ib < nb; ++ib) {
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int sumi = 0;
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@ -6797,6 +6948,77 @@ void ggml_vec_dot_q4_K_q8_K(int n, float * restrict s, size_t bs, const void * r
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*s = hsum_float_8(acc) + ((v4f32)acc_m)[0];
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#elif defined(__VXE__) || defined(__VXE2__)
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const uint8x16_t v_lm = vec_splat_u8(0x0F);
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const int32x4_t v_z = vec_splat_s32(0);
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uint8x16_t v_x[2];
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int8x16_t v_xl[2];
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int8x16_t v_y[2];
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float sumf = 0;
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for (int i = 0; i < nb; ++i) {
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const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
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const float dmin = y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
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const int16x8_t v_ysumsl = vec_xl(0 , y[i].bsums);
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const int16x8_t v_ysumsh = vec_xl(16, y[i].bsums);
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const int16x8_t v_ysums = vec_padd_s16(v_ysumsl, v_ysumsh);
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memcpy(utmp, x[i].scales, 12);
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uint32x4_t v_mins8 = { 0 };
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v_mins8 = vec_insert(utmp[1] & kmask1, v_mins8, 0);
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v_mins8 = vec_insert(((utmp[2] >> 4) & kmask2) | (((utmp[1] >> 6) & kmask3) << 4), v_mins8, 1);
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utmp[1] = (utmp[2] & kmask2) | (((utmp[0] >> 6) & kmask3) << 4);
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utmp[0] &= kmask1;
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const int16x8_t v_minsh = (int16x8_t)vec_unpackh((uint8x16_t)v_mins8);
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const int32x4_t v_minso = vec_mulo(v_ysums, v_minsh);
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const int32x4_t v_minse = vec_mule(v_ysums, v_minsh);
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const int32x4_t v_mins = v_minso + v_minse;
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sumf -= dmin * (v_mins[0] + v_mins[1] + v_mins[2] + v_mins[3]);
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|
||||
const uint8_t * scales = (const uint8_t *)utmp;
|
||||
const uint8_t * restrict x0 = x[i].qs;
|
||||
const int8_t * restrict y0 = y[i].qs;
|
||||
|
||||
int32_t sumi1 = 0;
|
||||
int32_t sumi2 = 0;
|
||||
|
||||
for (int j = 0; j < QK_K/64; ++j) {
|
||||
v_x[0] = vec_xl(0 , x0);
|
||||
v_x[1] = vec_xl(16, x0);
|
||||
x0 += 32;
|
||||
|
||||
v_y[0] = vec_xl(0 , y0);
|
||||
v_y[1] = vec_xl(16, y0);
|
||||
y0 += 32;
|
||||
|
||||
v_xl[0] = (int8x16_t)vec_and(v_x[0], v_lm);
|
||||
v_xl[1] = (int8x16_t)vec_and(v_x[1], v_lm);
|
||||
|
||||
const int32x4_t p1 = ggml_vec_dot(ggml_vec_dot(v_z, v_xl[0], v_y[0]), v_xl[1], v_y[1]);
|
||||
sumi1 += (p1[0] + p1[1] + p1[2] + p1[3]) * scales[2*j+0];
|
||||
|
||||
v_y[0] = vec_xl(0 , y0);
|
||||
v_y[1] = vec_xl(16, y0);
|
||||
y0 += 32;
|
||||
|
||||
v_xl[0] = (int8x16_t)vec_sr(v_x[0], 4);
|
||||
v_xl[1] = (int8x16_t)vec_sr(v_x[1], 4);
|
||||
|
||||
const int32x4_t p2 = ggml_vec_dot(ggml_vec_dot(v_z, v_xl[0], v_y[0]), v_xl[1], v_y[1]);
|
||||
sumi2 += (p2[0] + p2[1] + p2[2] + p2[3]) * scales[2*j+1];
|
||||
}
|
||||
|
||||
sumf += d * (sumi1 + sumi2);
|
||||
}
|
||||
|
||||
*s = sumf;
|
||||
#else
|
||||
|
||||
const uint8_t * scales = (const uint8_t*)&utmp[0];
|
||||
@ -7526,7 +7748,94 @@ void ggml_vec_dot_q5_K_q8_K(int n, float * restrict s, size_t bs, const void * r
|
||||
acc_m = __lsx_vfadd_s(acc_m, (__m128)__lsx_vbsrl_v(acc_m, 4));
|
||||
|
||||
*s = hsum_float_8(acc) + ((v4f32)acc_m)[0];
|
||||
#elif defined(__VXE__) || defined(__VXE2__)
|
||||
const uint8x16_t v_lm = vec_splat_u8(0x0F);
|
||||
const uint8x16_t v_1m = vec_splat_u8(0x01);
|
||||
const uint8x16_t v_2m = vec_splat_u8(0x02);
|
||||
|
||||
const int32x4_t v_z = vec_splat_s32(0);
|
||||
|
||||
const uchar8x16_t v_minsm = {
|
||||
0x08, 0x09, 0x0A, 0x0B, 0x0C, 0x0D, 0x0E, 0x0F,
|
||||
0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF, 0xFF
|
||||
};
|
||||
|
||||
int8x16_t q5b[4];
|
||||
uint8x16_t q5h[4];
|
||||
|
||||
uint8x16_t v_xl[2];
|
||||
uint8x16_t v_xh[2];
|
||||
int8x16_t v_y[4];
|
||||
|
||||
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 int16x8_t v_ysumsl = vec_xl(0 , y[i].bsums);
|
||||
const int16x8_t v_ysumsh = vec_xl(16, y[i].bsums);
|
||||
const int16x8_t v_ysums = vec_padd_s16(v_ysumsl, v_ysumsh);
|
||||
|
||||
memcpy(utmp, x[i].scales, 12);
|
||||
utmp[3] = ((utmp[2] >> 4) & kmask2) | (((utmp[1] >> 6) & kmask3) << 4);
|
||||
const uint32_t uaux = utmp[1] & kmask1;
|
||||
utmp[1] = (utmp[2] & kmask2) | (((utmp[0] >> 6) & kmask3) << 4);
|
||||
utmp[2] = uaux;
|
||||
utmp[0] &= kmask1;
|
||||
|
||||
const uint8x16_t v_mins16 = vec_xl(0, (const uint8_t *)utmp);
|
||||
const uint8x16_t v_mins8 = vec_perm(v_mins16, v_mins16, v_minsm);
|
||||
const int16x8_t v_minsh = (int16x8_t)vec_unpackh(v_mins8);
|
||||
|
||||
const int32x4_t v_minsho = vec_mulo(v_ysums, v_minsh);
|
||||
const int32x4_t v_minshe = vec_mule(v_ysums, v_minsh);
|
||||
const int32x4_t v_mins = vec_add(v_minsho, v_minshe);
|
||||
const int32_t mins = v_mins[0] + v_mins[1] + v_mins[2] + v_mins[3];
|
||||
|
||||
const uint8_t * scales = (const uint8_t *)utmp;
|
||||
const uint8_t * restrict x0l = x[i].qs;
|
||||
const uint8_t * restrict x0h = x[i].qh;
|
||||
const int8_t * restrict y0 = y[i].qs;
|
||||
|
||||
v_xh[0] = vec_xl(0 , x0h);
|
||||
v_xh[1] = vec_xl(16, x0h);
|
||||
|
||||
int32_t sumi = 0;
|
||||
for (int j = 0; j < QK_K/64; ++j) {
|
||||
v_xl[0] = vec_xl(0 , x0l);
|
||||
v_xl[1] = vec_xl(16, x0l);
|
||||
x0l += 32;
|
||||
|
||||
v_y[0] = vec_xl(0 , y0);
|
||||
v_y[1] = vec_xl(16, y0);
|
||||
v_y[2] = vec_xl(32, y0);
|
||||
v_y[3] = vec_xl(48, y0);
|
||||
y0 += 64;
|
||||
|
||||
q5h[0] = vec_sl(vec_and(v_1m, v_xh[0]), 4);
|
||||
q5h[1] = vec_sl(vec_and(v_1m, v_xh[1]), 4);
|
||||
q5h[2] = vec_sl(vec_and(v_2m, v_xh[0]), 3);
|
||||
q5h[3] = vec_sl(vec_and(v_2m, v_xh[1]), 3);
|
||||
v_xh[0] = vec_sr(v_xh[0], 2);
|
||||
v_xh[1] = vec_sr(v_xh[1], 2);
|
||||
|
||||
q5b[0] = (int8x16_t)vec_or(vec_and(v_xl[0], v_lm), q5h[0]);
|
||||
q5b[1] = (int8x16_t)vec_or(vec_and(v_xl[1], v_lm), q5h[1]);
|
||||
q5b[2] = (int8x16_t)vec_or(vec_sr(v_xl[0], 4), q5h[2]);
|
||||
q5b[3] = (int8x16_t)vec_or(vec_sr(v_xl[1], 4), q5h[3]);
|
||||
|
||||
int32x4_t sumi0 = ggml_vec_dot(ggml_vec_dot(v_z, q5b[0], v_y[0]), q5b[1], v_y[1]);
|
||||
int32x4_t sumi1 = ggml_vec_dot(ggml_vec_dot(v_z, q5b[2], v_y[2]), q5b[3], v_y[3]);
|
||||
|
||||
sumi += (sumi0[0] + sumi0[1] + sumi0[2] + sumi0[3]) * *scales++;
|
||||
sumi += (sumi1[0] + sumi1[1] + sumi1[2] + sumi1[3]) * *scales++;
|
||||
}
|
||||
|
||||
sumf += d * sumi - dmin * mins;
|
||||
}
|
||||
|
||||
*s = sumf;
|
||||
#else
|
||||
|
||||
const uint8_t * scales = (const uint8_t*)&utmp[0];
|
||||
@ -8243,7 +8552,130 @@ void ggml_vec_dot_q6_K_q8_K(int n, float * restrict s, size_t bs, const void * r
|
||||
}
|
||||
|
||||
*s = hsum_float_8(acc);
|
||||
#elif defined(__VXE__) || defined(__VXE2__)
|
||||
float sum = 0;
|
||||
|
||||
// Lower 4-bit and upper 2-bit masks
|
||||
const uint8x16_t v_lm = vec_splat_u8(0x0F);
|
||||
const uint8x16_t v_um = vec_splat_u8(0x03);
|
||||
|
||||
const int32x4_t v_z = vec_splat_s32(0);
|
||||
|
||||
int8x16_t q6b[4];
|
||||
uint8x16_t q6h[4];
|
||||
|
||||
uint8x16_t v_xl[4];
|
||||
uint8x16_t v_xh[2];
|
||||
int8x16_t v_y[4];
|
||||
|
||||
for (int i = 0; i < nb; ++i) {
|
||||
const float d_all = GGML_FP16_TO_FP32(x[i].d);
|
||||
|
||||
const uint8_t * restrict x0l = x[i].ql;
|
||||
const uint8_t * restrict x0h = x[i].qh;
|
||||
const int8_t * restrict y0 = y[i].qs;
|
||||
|
||||
const int8_t * restrict scale = x[i].scales;
|
||||
|
||||
const int16x8_t v_ysumsl = vec_xl(0 , y[i].bsums);
|
||||
const int16x8_t v_ysumsh = vec_xl(16, y[i].bsums);
|
||||
|
||||
const int8x16_t v_scale = vec_xl(0, scale);
|
||||
const int16x8_t v_scalel = vec_unpackh(v_scale);
|
||||
const int16x8_t v_scaleh = vec_unpackl(v_scale);
|
||||
|
||||
const int32x4_t v_minslo = vec_mulo(v_ysumsl, v_scalel);
|
||||
const int32x4_t v_minsle = vec_mule(v_ysumsl, v_scalel);
|
||||
const int32x4_t v_minsho = vec_mulo(v_ysumsh, v_scaleh);
|
||||
const int32x4_t v_minshe = vec_mule(v_ysumsh, v_scaleh);
|
||||
const int32x4_t v_mins = v_minslo + v_minsle + v_minsho + v_minshe;
|
||||
|
||||
const int32_t mins = v_mins[0] + v_mins[1] + v_mins[2] + v_mins[3];
|
||||
|
||||
int32_t isum = 0;
|
||||
for (int j = 0; j < QK_K/128; ++j) {
|
||||
// Load model upper 2 bits
|
||||
v_xh[0] = vec_xl(0 , x0h);
|
||||
v_xh[1] = vec_xl(16, x0h);
|
||||
x0h += 32;
|
||||
|
||||
// Load model lower 4 bits
|
||||
v_xl[0] = vec_xl(0 , x0l);
|
||||
v_xl[1] = vec_xl(16, x0l);
|
||||
v_xl[2] = vec_xl(32, x0l);
|
||||
v_xl[3] = vec_xl(48, x0l);
|
||||
x0l += 64;
|
||||
|
||||
// Load activation quants
|
||||
v_y[0] = vec_xl(0 , y0);
|
||||
v_y[1] = vec_xl(16, y0);
|
||||
v_y[2] = vec_xl(32, y0);
|
||||
v_y[3] = vec_xl(48, y0);
|
||||
y0 += 64;
|
||||
|
||||
q6h[0] = vec_sl(vec_and(v_um, v_xh[0]), 4);
|
||||
q6h[1] = vec_sl(vec_and(v_um, v_xh[1]), 4);
|
||||
uint8x16_t shifted = vec_sr(v_xh[0], 2);
|
||||
q6h[2] = vec_sl(vec_and(v_um, shifted), 4);
|
||||
shifted = vec_sr(v_xh[1], 2);
|
||||
q6h[3] = vec_sl(vec_and(v_um, shifted), 4);
|
||||
|
||||
q6b[0] = (int8x16_t)(vec_or(vec_and(v_xl[0], v_lm), q6h[0]));
|
||||
q6b[1] = (int8x16_t)(vec_or(vec_and(v_xl[1], v_lm), q6h[1]));
|
||||
q6b[2] = (int8x16_t)(vec_or(vec_and(v_xl[2], v_lm), q6h[2]));
|
||||
q6b[3] = (int8x16_t)(vec_or(vec_and(v_xl[3], v_lm), q6h[3]));
|
||||
|
||||
int32x4_t summs0 = ggml_vec_dot(v_z, q6b[0], v_y[0]);
|
||||
int32x4_t summs1 = ggml_vec_dot(v_z, q6b[1], v_y[1]);
|
||||
int32x4_t summs2 = ggml_vec_dot(v_z, q6b[2], v_y[2]);
|
||||
int32x4_t summs3 = ggml_vec_dot(v_z, q6b[3], v_y[3]);
|
||||
|
||||
isum += (summs0[0] + summs0[1] + summs0[2] + summs0[3]) * scale[0] +
|
||||
(summs1[0] + summs1[1] + summs1[2] + summs1[3]) * scale[1] +
|
||||
(summs2[0] + summs2[1] + summs2[2] + summs2[3]) * scale[2] +
|
||||
(summs3[0] + summs3[1] + summs3[2] + summs3[3]) * scale[3];
|
||||
|
||||
scale += 4;
|
||||
|
||||
|
||||
// Load activation quants
|
||||
v_y[0] = vec_xl(0 , y0);
|
||||
v_y[1] = vec_xl(16, y0);
|
||||
v_y[2] = vec_xl(32, y0);
|
||||
v_y[3] = vec_xl(48, y0);
|
||||
y0 += 64;
|
||||
|
||||
shifted = vec_sr(v_xh[0], 4);
|
||||
q6h[0] = vec_sl(vec_and(v_um, shifted), 4);
|
||||
shifted = vec_sr(v_xh[1], 4);
|
||||
q6h[1] = vec_sl(vec_and(v_um, shifted), 4);
|
||||
shifted = vec_sr(v_xh[0], 6);
|
||||
q6h[2] = vec_sl(vec_and(v_um, shifted), 4);
|
||||
shifted = vec_sr(v_xh[1], 6);
|
||||
q6h[3] = vec_sl(vec_and(v_um, shifted), 4);
|
||||
|
||||
q6b[0] = (int8x16_t)(vec_or(vec_sr(v_xl[0], 4), q6h[0]));
|
||||
q6b[1] = (int8x16_t)(vec_or(vec_sr(v_xl[1], 4), q6h[1]));
|
||||
q6b[2] = (int8x16_t)(vec_or(vec_sr(v_xl[2], 4), q6h[2]));
|
||||
q6b[3] = (int8x16_t)(vec_or(vec_sr(v_xl[3], 4), q6h[3]));
|
||||
|
||||
summs0 = ggml_vec_dot(v_z, q6b[0], v_y[0]);
|
||||
summs1 = ggml_vec_dot(v_z, q6b[1], v_y[1]);
|
||||
summs2 = ggml_vec_dot(v_z, q6b[2], v_y[2]);
|
||||
summs3 = ggml_vec_dot(v_z, q6b[3], v_y[3]);
|
||||
|
||||
isum += (summs0[0] + summs0[1] + summs0[2] + summs0[3]) * scale[0] +
|
||||
(summs1[0] + summs1[1] + summs1[2] + summs1[3]) * scale[1] +
|
||||
(summs2[0] + summs2[1] + summs2[2] + summs2[3]) * scale[2] +
|
||||
(summs3[0] + summs3[1] + summs3[2] + summs3[3]) * scale[3];
|
||||
|
||||
scale += 4;
|
||||
}
|
||||
|
||||
sum += d_all * y[i].d * (isum - 32 * mins);
|
||||
}
|
||||
|
||||
*s = sum;
|
||||
#else
|
||||
|
||||
int8_t aux8[QK_K];
|
||||
@ -8604,7 +9036,57 @@ void ggml_vec_dot_iq2_xxs_q8_K(int n, float * restrict s, size_t bs, const void
|
||||
}
|
||||
|
||||
*s = 0.125f * hsum_float_8(accumf);
|
||||
|
||||
//#elif defined(__VXE__) || defined(__VXE2__)
|
||||
// const uint64_t * signs64 = (const uint64_t *)keven_signs_q2xs;
|
||||
//
|
||||
// uint32_t aux32[4];
|
||||
// const uint8_t * aux8 = (const uint8_t *)aux32;
|
||||
//
|
||||
// float sumf = 0;
|
||||
//
|
||||
// for (int i = 0; i < nb; ++i) {
|
||||
// const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
|
||||
// const uint16_t * restrict q2 = x[i].qs;
|
||||
// const int8_t * restrict q8 = y[i].qs;
|
||||
//
|
||||
// float sumf1 = 0, sumf2 = 0;
|
||||
//
|
||||
// for (int ib32 = 0; ib32 < QK_K/32; ib += 2) {
|
||||
// int8x16_t q8b0 = vec_xl( 0, q8);
|
||||
// int8x16_t qb81 = vec_xl(16, q8);
|
||||
// int8x16_t q8b2 = vec_xl(32, q8);
|
||||
// int8x16_t q8b3 = vec_xl(48, q8);
|
||||
// q8 += 64;
|
||||
//
|
||||
// memcpy(aux32, q2, 4 * sizeof(uint32_t));
|
||||
// q2 += 8;
|
||||
//
|
||||
// int8x16_t q2u0 = { *(const int64_t *)(iq2xxs_grid + aux8[ 0]), *(const int64_t *)(iq2xxs_grid + aux8[ 1]) };
|
||||
// int8x16_t q2u1 = { *(const int64_t *)(iq2xxs_grid + aux8[ 2]), *(const int64_t *)(iq2xxs_grid + aux8[ 3]) };
|
||||
// int8x16_t q2u2 = { *(const int64_t *)(iq2xxs_grid + aux8[ 8]), *(const int64_t *)(iq2xxs_grid + aux8[ 9]) };
|
||||
// int8x16_t q2u3 = { *(const int64_t *)(iq2xxs_grid + aux8[10]), *(const int64_t *)(iq2xxs_grid + aux8[11]) };
|
||||
//
|
||||
// int8x16_t q2s0 = { *(const int64_t *)(signs64 + ((aux32[1] >> 0) & 127)), *(const int64_t *)(signs64 + ((aux32[1] >> 7) & 127)) };
|
||||
// int8x16_t q2s1 = { *(const int64_t *)(signs64 + ((aux32[1] >> 14) & 127)), *(const int64_t *)(signs64 + ((aux32[1] >> 21) & 127)) };
|
||||
// int8x16_t q2s2 = { *(const int64_t *)(signs64 + ((aux32[3] >> 0) & 127)), *(const int64_t *)(signs64 + ((aux32[3] >> 7) & 127)) };
|
||||
// int8x16_t q2s3 = { *(const int64_t *)(signs64 + ((aux32[3] >> 14) & 127)), *(const int64_t *)(signs64 + ((aux32[3] >> 21) & 127)) };
|
||||
//
|
||||
// q2u0 = vec_mul(q2u0, q2s0);
|
||||
// q2u1 = vec_mul(q2u1, q2s1);
|
||||
// q2u2 = vec_mul(q2u2, q2s2);
|
||||
// q2u3 = vec_mul(q2u3, q2s3);
|
||||
//
|
||||
// const int32x4_t p1 = ggml_vec_dot(ggml_vec_dot(vec_splat_s32(0), q2u0, q8b0), q2u1, q8b1);
|
||||
// const int32x4_t p2 = ggml_vec_dot(ggml_vec_dot(vec_splat_s32(0), q2u2, q8b2), q2u3, q8b3);
|
||||
//
|
||||
// sumf1 += (p1[0] + p1[1] + p1[2] + p1[3]) * (0.5f + (aux32[1] >> 28));
|
||||
// sumf2 += (p2[0] + p2[1] + p2[2] + p2[3]) * (0.5f + (aux32[3] >> 28));
|
||||
// }
|
||||
//
|
||||
// sumf += d * (sumf1 + sumf2);
|
||||
// }
|
||||
//
|
||||
// *s = 0.25f * sumf;
|
||||
#else
|
||||
|
||||
uint32_t aux32[2];
|
||||
@ -11365,6 +11847,27 @@ void ggml_vec_dot_iq4_nl_q8_0(int n, float * restrict s, size_t bs, const void *
|
||||
|
||||
sumf = hsum_float_8(__lasx_xvfadd_s(accum1, accum2));
|
||||
|
||||
#elif defined(__VXE__) || defined(__VXE2__)
|
||||
const int8x16_t v_k = vec_xl(0, kvalues_iq4nl);
|
||||
const uint8x16_t v_m = vec_splat_u8(0x0F);
|
||||
|
||||
for (; ib < nb; ++ib) {
|
||||
const block_iq4_nl * restrict x0 = &x[ib];
|
||||
const block_q8_0 * restrict y0 = &y[ib];
|
||||
|
||||
const uint8x16_t v_x = vec_xl(0, x0->qs);
|
||||
int8x16_t v_xl = (int8x16_t)vec_and(v_x, v_m);
|
||||
int8x16_t v_xh = (int8x16_t)vec_sr(v_x, 4);
|
||||
|
||||
v_xl = vec_perm(v_k, v_k, (uchar8x16_t)v_xl);
|
||||
v_xh = vec_perm(v_k, v_k, (uchar8x16_t)v_xh);
|
||||
|
||||
const int8x16_t v_yl = vec_xl(0 , y0->qs);
|
||||
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]);
|
||||
}
|
||||
#endif
|
||||
for (; ib < nb; ++ib) {
|
||||
const float d = GGML_FP16_TO_FP32(y[ib].d)*GGML_FP16_TO_FP32(x[ib].d);
|
||||
@ -11643,6 +12146,56 @@ void ggml_vec_dot_iq4_xs_q8_K(int n, float * restrict s, size_t bs, const void *
|
||||
}
|
||||
|
||||
*s = hsum_float_8(accum);
|
||||
#elif defined(__VXE__) || defined(__VXE2__)
|
||||
const int8x16_t v_k = vec_xl(0, kvalues_iq4nl);
|
||||
const uint8x16_t v_m = vec_splat_u8(0x0F);
|
||||
|
||||
float sumf = 0;
|
||||
|
||||
for (int ibl = 0; ibl < nb; ++ibl) {
|
||||
const uint8_t * restrict q4 = x[ibl].qs;
|
||||
const int8_t * restrict q8 = y[ibl].qs;
|
||||
|
||||
uint16_t h = x[ibl].scales_h;
|
||||
|
||||
int sumi1 = 0, sumi2 = 0;
|
||||
for (int ib = 0; ib < QK_K/64; ++ib) {
|
||||
const uint8x16_t v_x0 = vec_xl(0 , q4);
|
||||
const uint8x16_t v_x1 = vec_xl(QK4_NL/2, q4);
|
||||
q4 += 32;
|
||||
|
||||
int8x16_t v_x0l = (int8x16_t)vec_and(v_x0, v_m);
|
||||
int8x16_t v_x0h = (int8x16_t)vec_sr(v_x0, 4);
|
||||
int8x16_t v_x1l = (int8x16_t)vec_and(v_x1, v_m);
|
||||
int8x16_t v_x1h = (int8x16_t)vec_sr(v_x1, 4);
|
||||
|
||||
v_x0l = vec_perm(v_k, v_k, (uchar8x16_t)v_x0l);
|
||||
v_x0h = vec_perm(v_k, v_k, (uchar8x16_t)v_x0h);
|
||||
v_x1l = vec_perm(v_k, v_k, (uchar8x16_t)v_x1l);
|
||||
v_x1h = vec_perm(v_k, v_k, (uchar8x16_t)v_x1h);
|
||||
|
||||
const int8x16_t v_y0 = vec_xl( 0, q8);
|
||||
const int8x16_t v_y1 = vec_xl(16, q8);
|
||||
const int8x16_t v_y2 = vec_xl(32, q8);
|
||||
const int8x16_t v_y3 = vec_xl(48, q8);
|
||||
q8 += 64;
|
||||
|
||||
int32x4_t vsumi0 = ggml_vec_dot(ggml_vec_dot(vec_splats(0), v_x0l, v_y0), v_x0h, v_y1);
|
||||
int32x4_t vsumi1 = ggml_vec_dot(ggml_vec_dot(vec_splats(0), v_x1l, v_y2), v_x1h, v_y3);
|
||||
|
||||
int ls1 = ((x[ibl].scales_l[ib] & 0xF) | ((h << 4) & 0x30)) - 32;
|
||||
int ls2 = ((x[ibl].scales_l[ib] >> 4) | ((h << 2) & 0x30)) - 32;
|
||||
|
||||
h >>= 4;
|
||||
|
||||
sumi1 += (vsumi0[0] + vsumi0[1] + vsumi0[2] + vsumi0[3]) * ls1;
|
||||
sumi2 += (vsumi1[0] + vsumi1[1] + vsumi1[2] + vsumi1[3]) * ls2;
|
||||
}
|
||||
|
||||
sumf += GGML_FP16_TO_FP32(x[ibl].d) * y[ibl].d * (sumi1 + sumi2);
|
||||
}
|
||||
|
||||
*s = sumf;
|
||||
|
||||
#else
|
||||
float sumf = 0;
|
||||
|
||||
Reference in New Issue
Block a user