mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-12-25 13:58:46 +01:00
ggml : more perfo with llamafile tinyblas on x86_64 (#10714)
* more perfo with llamafile tinyblas on x86_64. - add bf16 suport - change dispache strategie (thanks: https://github.com/ikawrakow/ik_llama.cpp/pull/71 ) - reduce memory bandwidth simple tinyblas dispache and more cache freindly * tinyblas dynamic dispaching * sgemm: add M blocs. * - git 2.47 use short id of len 9. - show-progress is not part of GNU Wget2 * remove not stable test
This commit is contained in:
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09fe2e7613
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@ -95,7 +95,7 @@ def test_consistent_result_same_seed(n_slots: int):
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res = server.make_request("POST", "/completion", data={
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"prompt": "I believe the meaning of life is",
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"seed": 42,
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"temperature": 1.0,
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"temperature": 0.0,
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"cache_prompt": False, # TODO: remove this once test_cache_vs_nocache_prompt is fixed
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})
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if last_res is not None:
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@ -120,9 +120,10 @@ def test_different_result_different_seed(n_slots: int):
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assert res.body["content"] != last_res.body["content"]
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last_res = res
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# TODO figure why it don't work with temperature = 1
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# @pytest.mark.parametrize("temperature", [0.0, 1.0])
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@pytest.mark.parametrize("n_batch", [16, 32])
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@pytest.mark.parametrize("temperature", [0.0, 1.0])
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@pytest.mark.parametrize("temperature", [0.0])
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def test_consistent_result_different_batch_size(n_batch: int, temperature: float):
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global server
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server.n_batch = n_batch
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@ -7419,14 +7419,14 @@ static void ggml_compute_forward_mul_mat(
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if (src1_cont) {
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for (int64_t i13 = 0; i13 < ne13; i13++)
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for (int64_t i12 = 0; i12 < ne12; i12++)
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if (!llamafile_sgemm(ne01, ne11, ne00/ggml_blck_size(src0->type),
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if (!llamafile_sgemm(params,
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ne01, ne11, ne00/ggml_blck_size(src0->type),
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(const char *)src0->data + i12/r2*nb02 + i13/r3*nb03,
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nb01/ggml_type_size(src0->type),
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(const char *)src1->data + i12*nb12 + i13*nb13,
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nb11/ggml_type_size(src1->type),
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(char *)dst->data + i12*nb2 + i13*nb3,
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nb1/ggml_type_size(dst->type),
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ith, nth,
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src0->type,
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src1->type,
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dst->type))
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@ -7471,14 +7471,14 @@ UseGgmlGemm1:;
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for (int64_t i13 = 0; i13 < ne13; i13++)
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for (int64_t i12 = 0; i12 < ne12; i12++)
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if (!llamafile_sgemm(ne01, ne11, ne00/ggml_blck_size(src0->type),
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if (!llamafile_sgemm(params,
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ne01, ne11, ne00/ggml_blck_size(src0->type),
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(const char *)src0->data + i12/r2*nb02 + i13/r3*nb03,
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nb01/ggml_type_size(src0->type),
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(const char *)wdata + (i12*ne11 + i13*ne12*ne11)*row_size,
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row_size/ggml_type_size(vec_dot_type),
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(char *)dst->data + i12*nb2 + i13*nb3,
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nb1/ggml_type_size(dst->type),
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ith, nth,
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src0->type,
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vec_dot_type,
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dst->type))
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@ -53,6 +53,8 @@
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#include "ggml-cpu-impl.h"
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#include "ggml-quants.h"
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#include <atomic>
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#ifdef _MSC_VER
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#define NOINLINE __declspec(noinline)
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#else
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@ -134,6 +136,16 @@ inline __m512 madd(__m512 a, __m512 b, __m512 c) {
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return _mm512_fmadd_ps(a, b, c);
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}
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#endif
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#if defined(__AVX512BF16__)
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template <>
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inline __m512 madd(__m512bh a, __m512bh b, __m512 c) {
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return _mm512_dpbf16_ps(c, a, b);
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}
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template <>
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inline __m256 madd(__m256bh a, __m256bh b, __m256 c) {
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return _mm256_dpbf16_ps(c, a, b);
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}
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#endif
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#endif
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#if defined(__ARM_FEATURE_FMA)
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@ -226,6 +238,13 @@ template <> inline __m256 load(const float *p) {
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}
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#endif // __AVX__
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#if defined(__AVX2__) || defined(__AVX512F__)
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template <> inline __m256 load(const ggml_bf16_t *p) {
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return _mm256_castsi256_ps(
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_mm256_slli_epi32(_mm256_cvtepu16_epi32(_mm_loadu_si128((const __m128i *)p)), 16));
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}
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#endif // __AVX2__
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#if defined(__F16C__)
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template <> inline __m256 load(const ggml_fp16_t *p) {
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return _mm256_cvtph_ps(_mm_loadu_si128((const __m128i *)p));
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@ -239,8 +258,27 @@ template <> inline __m512 load(const float *p) {
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template <> inline __m512 load(const ggml_fp16_t *p) {
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return _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)p));
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}
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template <> inline __m512 load(const ggml_bf16_t *p) {
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return _mm512_castsi512_ps(
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_mm512_slli_epi32(_mm512_cvtepu16_epi32(_mm256_loadu_si256((const __m256i *)p)), 16));
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}
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#endif // __AVX512F__
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#if defined(__AVX512BF16__)
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template <> inline __m512bh load(const ggml_bf16_t *p) {
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return (__m512bh)_mm512_loadu_ps((const float *)p);
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}
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template <> inline __m256bh load(const ggml_bf16_t *p) {
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return (__m256bh)_mm256_loadu_ps((const float *)p);
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}
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template <> inline __m512bh load(const float *p) {
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return _mm512_cvtne2ps_pbh(_mm512_loadu_ps(p + 16), _mm512_loadu_ps(p));
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}
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template <> inline __m256bh load(const float *p) {
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return _mm512_cvtneps_pbh(_mm512_loadu_ps(p));
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}
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#endif
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////////////////////////////////////////////////////////////////////////////////////////////////////
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// CONSTANTS
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@ -252,199 +290,170 @@ static const __m128i iq4nlt = _mm_loadu_si128((const __m128i *) kvalues_iq4nl);
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////////////////////////////////////////////////////////////////////////////////////////////////////
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// FLOATING POINT MATRIX MULTIPLICATION
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template <int M>
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static inline int64_t BLOCK_SIZE(size_t m) {
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const int64_t NB_BLOC_M = (m + M - 1) / M;
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return (m % NB_BLOC_M == 0) ? m / NB_BLOC_M : (m / NB_BLOC_M) + 1;
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}
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static constexpr inline int64_t BLOC_POS(int64_t ib, int64_t ibN, int64_t bloc_size) {
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return ib < ibN ? ib * bloc_size : ibN * bloc_size + (ib - ibN) * (bloc_size - 1);
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}
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template <int KN, typename D, typename V, typename TA, typename TB, typename TC>
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class tinyBLAS {
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public:
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tinyBLAS(int64_t k,
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tinyBLAS(const ggml_compute_params * params, int64_t k,
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const TA *A, int64_t lda,
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const TB *B, int64_t ldb,
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TC *C, int64_t ldc,
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int ith, int nth)
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: A(A), B(B), C(C), k(k), lda(lda), ldb(ldb), ldc(ldc), ith(ith), nth(nth) {
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TC *C, int64_t ldc)
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: params(params), A(A), B(B), C(C), k(k), lda(lda), ldb(ldb), ldc(ldc) {
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}
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void matmul(int64_t m, int64_t n) {
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mnpack(0, m, 0, n);
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bool matmul(int64_t m, int64_t n) {
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if (k % KN != 0)
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return false;
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// compute RM for only need tile with size RM&RM-1
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#if VECTOR_REGISTERS == 32
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if (m % 16 == 0 && (m/16 >= params->nth)) {
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const int64_t SIZE_N = BLOCK_SIZE<6>(n);
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mnpack<4, 6, 4>(m, n, SIZE_N, 12);
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return true;
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}
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if (m % 8 == 0 ) {
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const int64_t SIZE_N = BLOCK_SIZE<6>(n);
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mnpack<4, 6, 2>(m, n, SIZE_N, 12);
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return true;
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}
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if (m % 4 == 0) {
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const int64_t SIZE_N = BLOCK_SIZE<6>(n);
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mnpack<4, 6, 1>(m, n, SIZE_N, 12);
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return true;
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}
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#else // VECTOR_REGISTERS == 16
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if (m % 16 == 0 && (m/16 >= params->nth)) {
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const int64_t SIZE_N = BLOCK_SIZE<3>(n);
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mnpack<4, 3, 4>(m, n, SIZE_N, 24);
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return true;
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}
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if (m % 8 == 0 ) {
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const int64_t SIZE_N = BLOCK_SIZE<3>(n);
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mnpack<4, 3, 2>(m, n, SIZE_N, 24);
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return true;
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}
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if (m % 4 == 0) {
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const int64_t SIZE_N = BLOCK_SIZE<3>(n);
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mnpack<4, 3, 1>(m, n, SIZE_N, 24);
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return true;
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}
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#endif
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return false;
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}
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private:
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NOINLINE void mnpack(int64_t m0, int64_t m, int64_t n0, int64_t n) {
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int64_t mc, nc, mp, np;
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switch ((MIN(m - m0, 5) << 4) | MIN(n - n0, 5)) {
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#if VECTOR_REGISTERS == 32
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case 0x55:
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mc = 5;
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nc = 5;
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gemm<5, 5>(m0, m, n0, n);
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break;
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case 0x45:
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mc = 4;
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nc = 5;
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gemm<4, 5>(m0, m, n0, n);
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break;
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case 0x54:
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mc = 5;
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nc = 4;
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gemm<5, 4>(m0, m, n0, n);
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break;
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case 0x44:
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mc = 4;
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nc = 4;
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gemm<4, 4>(m0, m, n0, n);
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break;
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case 0x53:
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mc = 5;
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nc = 3;
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gemm<5, 3>(m0, m, n0, n);
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break;
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case 0x35:
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mc = 3;
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nc = 5;
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gemm<3, 5>(m0, m, n0, n);
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break;
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case 0x43:
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mc = 4;
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nc = 3;
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gemm<4, 3>(m0, m, n0, n);
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break;
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#else
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case 0x55:
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case 0x54:
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case 0x53:
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case 0x45:
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case 0x44:
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case 0x43:
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mc = 4;
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nc = 3;
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gemm<4, 3>(m0, m, n0, n);
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break;
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case 0x35:
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#endif
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case 0x34:
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mc = 3;
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nc = 4;
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gemm<3, 4>(m0, m, n0, n);
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break;
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case 0x52:
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mc = 5;
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nc = 2;
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gemm<5, 2>(m0, m, n0, n);
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break;
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case 0x33:
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mc = 3;
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nc = 3;
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gemm<3, 3>(m0, m, n0, n);
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break;
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case 0x25:
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mc = 2;
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nc = 5;
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gemm<2, 5>(m0, m, n0, n);
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break;
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case 0x42:
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mc = 4;
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nc = 2;
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gemm<4, 2>(m0, m, n0, n);
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break;
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case 0x24:
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mc = 2;
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nc = 4;
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gemm<2, 4>(m0, m, n0, n);
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break;
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case 0x32:
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mc = 3;
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nc = 2;
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gemm<3, 2>(m0, m, n0, n);
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break;
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case 0x23:
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mc = 2;
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nc = 3;
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gemm<2, 3>(m0, m, n0, n);
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break;
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case 0x51:
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mc = 5;
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nc = 1;
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gemm<5, 1>(m0, m, n0, n);
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break;
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case 0x41:
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mc = 4;
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nc = 1;
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gemm<4, 1>(m0, m, n0, n);
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break;
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case 0x22:
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mc = 2;
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nc = 2;
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gemm<2, 2>(m0, m, n0, n);
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break;
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case 0x15:
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mc = 1;
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nc = 5;
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gemm<1, 5>(m0, m, n0, n);
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break;
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case 0x14:
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mc = 1;
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nc = 4;
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gemm<1, 4>(m0, m, n0, n);
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break;
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case 0x31:
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mc = 3;
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nc = 1;
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gemm<3, 1>(m0, m, n0, n);
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break;
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case 0x13:
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mc = 1;
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nc = 3;
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gemm<1, 3>(m0, m, n0, n);
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break;
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case 0x21:
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mc = 2;
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nc = 1;
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gemm<2, 1>(m0, m, n0, n);
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break;
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case 0x12:
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mc = 1;
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nc = 2;
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gemm<1, 2>(m0, m, n0, n);
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break;
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case 0x11:
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mc = 1;
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nc = 1;
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gemm<1, 1>(m0, m, n0, n);
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break;
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default:
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return;
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template <int RM, int RN, int BM>
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inline void mnpack(int64_t m, int64_t n, int64_t SIZE_N, int64_t BN) {
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if (SIZE_N == RN) {
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return gemm<RM, RN, BM>(m, n, BN);
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}
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if constexpr (RN > 1) {
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return mnpack<RM, RN-1, BM>(m, n, SIZE_N, BN);
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} else {
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GGML_LOG_ERROR("mnpack<%d, %d> bloc size not supported\n", RM, (int)SIZE_N);
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GGML_ASSERT(false); // we have miss something.
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}
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mp = m0 + (m - m0) / mc * mc;
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np = n0 + (n - n0) / nc * nc;
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mnpack(mp, m, n0, np);
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mnpack(m0, m, np, n);
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}
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template <int RM, int RN>
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NOINLINE void gemm(int64_t m0, int64_t m, int64_t n0, int64_t n) {
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int64_t ytiles = (m - m0) / RM;
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int64_t xtiles = (n - n0) / RN;
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int64_t tiles = xtiles * ytiles;
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int64_t duty = (tiles + nth - 1) / nth;
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int64_t start = duty * ith;
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int64_t end = start + duty;
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if (end > tiles)
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end = tiles;
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for (int64_t job = start; job < end; ++job) {
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int64_t ii = m0 + job / xtiles * RM;
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int64_t jj = n0 + job % xtiles * RN;
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D Cv[RN][RM] = {};
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for (int64_t l = 0; l < k; l += KN)
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for (int64_t j = 0; j < RN; ++j)
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for (int64_t i = 0; i < RM; ++i)
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Cv[j][i] = madd(load<V>(A + lda * (ii + i) + l),
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load<V>(B + ldb * (jj + j) + l),
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Cv[j][i]);
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for (int64_t j = 0; j < RN; ++j)
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for (int64_t i = 0; i < RM; ++i)
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C[ldc * (jj + j) + (ii + i)] = hsum(Cv[j][i]);
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inline void gemm_bloc(int64_t ii, int64_t jj) {
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D Cv[RN][RM] = {};
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for (int64_t l = 0; l < k; l += KN) {
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// help compiler for op order.
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if constexpr (RM <= RN) {
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V Av[RM];
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for (int64_t i = 0; i < RM; ++i) {
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Av[i] = load<V>(A + lda * (ii + i) + l);
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}
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for (int64_t j = 0; j < RN; ++j) {
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V Bv = load<V>(B + ldb * (jj + j) + l);
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for (int64_t i = 0; i < RM; ++i) {
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Cv[j][i] = madd(Av[i], Bv, Cv[j][i]);
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}
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}
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} else {
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V Bv[RN];
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for (int64_t j = 0; j < RN; ++j) {
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Bv[j] = load<V>(B + ldb * (jj + j) + l);
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}
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for (int64_t i = 0; i < RM; ++i) {
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V Av = load<V>(A + lda * (ii + i) + l);
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for (int64_t j = 0; j < RN; ++j) {
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Cv[j][i] = madd(Av, Bv[j], Cv[j][i]);
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}
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}
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}
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}
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for (int64_t j = 0; j < RN; ++j)
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for (int64_t i = 0; i < RM; ++i)
|
||||
C[ldc * (jj + j) + (ii + i)] = hsum(Cv[j][i]);
|
||||
}
|
||||
|
||||
template <int RM, int RN, int BM>
|
||||
NOINLINE void gemm(int64_t m, int64_t n, int64_t BN) {
|
||||
static std::atomic<int64_t> current_chunk;
|
||||
|
||||
GGML_ASSERT(m % (RM * BM) == 0);
|
||||
const int64_t ytiles = m / (RM * BM);
|
||||
const int64_t xtiles = (n + RN -1) / RN;
|
||||
const int64_t jj_RN = (xtiles - (xtiles * RN - n));
|
||||
|
||||
// "round" bloc_size to "nearest" BN
|
||||
const int64_t NB_BN = xtiles < BN ? 1 : (xtiles + BN / 2) / BN;
|
||||
const int64_t SIZE_BN = xtiles % NB_BN == 0 ? xtiles / NB_BN : xtiles / NB_BN + 1;
|
||||
const int64_t jj_BN = (NB_BN - (NB_BN * SIZE_BN - xtiles));
|
||||
const int64_t nb_job = ytiles * NB_BN;
|
||||
|
||||
if (params->ith == 0) {
|
||||
GGML_ASSERT( jj_BN * SIZE_BN + (NB_BN - jj_BN) * (SIZE_BN - 1) == xtiles);
|
||||
// Every thread starts at ith, so the first unprocessed chunk is nth. This save a bit of coordination right at the start.
|
||||
std::atomic_store_explicit(¤t_chunk, (int64_t)params->nth, std::memory_order_relaxed);
|
||||
}
|
||||
|
||||
ggml_barrier(params->threadpool);
|
||||
|
||||
int64_t job = params->ith;
|
||||
while (job < nb_job) {
|
||||
const int64_t ii = (job % ytiles) * RM * BM;
|
||||
const int64_t jb = job / ytiles;
|
||||
const int64_t jr0 = BLOC_POS(jb , jj_BN, SIZE_BN);
|
||||
const int64_t jrN = BLOC_POS(jb+1, jj_BN, SIZE_BN);
|
||||
|
||||
const int64_t jj0 = BLOC_POS(jr0, jj_RN, RN);
|
||||
const int64_t jj2 = BLOC_POS(jrN, jj_RN, RN);
|
||||
const int64_t jj1 = jj2 < jj_RN * RN ? jj2 : jj_RN * RN;
|
||||
|
||||
for (int64_t bi = 0; bi < BM * RM; bi += RM) {
|
||||
int64_t jj = jj0;
|
||||
for (; jj < jj1; jj += RN) {
|
||||
gemm_bloc<RM, RN>(ii + bi, jj);
|
||||
}
|
||||
if constexpr (RN > 1) {
|
||||
for (; jj < jj2; jj += RN - 1) {
|
||||
gemm_bloc<RM, RN-1>(ii + bi, jj);
|
||||
}
|
||||
}
|
||||
GGML_ASSERT(jj == jj2);
|
||||
}
|
||||
|
||||
// next step.
|
||||
job = std::atomic_fetch_add_explicit(¤t_chunk, (int64_t)1, std::memory_order_relaxed);
|
||||
}
|
||||
|
||||
ggml_barrier(params->threadpool);
|
||||
return;
|
||||
}
|
||||
|
||||
const ggml_compute_params * params;
|
||||
const TA *const A;
|
||||
const TB *const B;
|
||||
TC *const C;
|
||||
@ -452,8 +461,6 @@ class tinyBLAS {
|
||||
const int64_t lda;
|
||||
const int64_t ldb;
|
||||
const int64_t ldc;
|
||||
const int ith;
|
||||
const int nth;
|
||||
};
|
||||
|
||||
//////////////////////////////////////////////////////////////////////////////////////////
|
||||
@ -1657,8 +1664,9 @@ class tinyBLAS_PPC {
|
||||
* @param Ctype is GGML data type of `C`
|
||||
* @return true if this function was able to service the matmul request
|
||||
*/
|
||||
bool llamafile_sgemm(int64_t m, int64_t n, int64_t k, const void *A, int64_t lda, const void *B, int64_t ldb, void *C,
|
||||
int64_t ldc, int ith, int nth, int Atype, int Btype, int Ctype) {
|
||||
bool llamafile_sgemm(const struct ggml_compute_params * params, int64_t m, int64_t n, int64_t k,
|
||||
const void *A, int64_t lda, const void *B, int64_t ldb, void *C,
|
||||
int64_t ldc, int Atype, int Btype, int Ctype) {
|
||||
|
||||
assert(m >= 0);
|
||||
assert(n >= 0);
|
||||
@ -1666,8 +1674,8 @@ bool llamafile_sgemm(int64_t m, int64_t n, int64_t k, const void *A, int64_t lda
|
||||
assert(lda >= k);
|
||||
assert(ldb >= k);
|
||||
assert(ldc >= m);
|
||||
assert(nth > 0);
|
||||
assert(ith < nth);
|
||||
assert(params->nth > 0);
|
||||
assert(params->ith < params->nth);
|
||||
|
||||
// only enable sgemm for prompt processing
|
||||
if (n < 2)
|
||||
@ -1682,37 +1690,25 @@ bool llamafile_sgemm(int64_t m, int64_t n, int64_t k, const void *A, int64_t lda
|
||||
if (Btype != GGML_TYPE_F32)
|
||||
return false;
|
||||
#if defined(__AVX512F__)
|
||||
if (k % 16)
|
||||
return false;
|
||||
tinyBLAS<16, __m512, __m512, float, float, float> tb{
|
||||
tinyBLAS<16, __m512, __m512, float, float, float> tb{ params,
|
||||
k, (const float *)A, lda,
|
||||
(const float *)B, ldb,
|
||||
(float *)C, ldc,
|
||||
ith, nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
(float *)C, ldc};
|
||||
return tb.matmul(m, n);
|
||||
#elif defined(__AVX__) || defined(__AVX2__)
|
||||
if (k % 8)
|
||||
return false;
|
||||
tinyBLAS<8, __m256, __m256, float, float, float> tb{
|
||||
tinyBLAS<8, __m256, __m256, float, float, float> tb{ params,
|
||||
k, (const float *)A, lda,
|
||||
(const float *)B, ldb,
|
||||
(float *)C, ldc,
|
||||
ith, nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
(float *)C, ldc};
|
||||
return tb.matmul(m, n);
|
||||
#elif defined(__ARM_NEON)
|
||||
if (n < 4)
|
||||
return false;
|
||||
if (k % 4)
|
||||
return false;
|
||||
tinyBLAS<4, float32x4_t, float32x4_t, float, float, float> tb{
|
||||
tinyBLAS<4, float32x4_t, float32x4_t, float, float, float> tb{ params,
|
||||
k, (const float *)A, lda,
|
||||
(const float *)B, ldb,
|
||||
(float *)C, ldc,
|
||||
ith, nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
(float *)C, ldc};
|
||||
return tb.matmul(m, n);
|
||||
#elif defined(__MMA__)
|
||||
if (k % 8)
|
||||
return false;
|
||||
@ -1720,7 +1716,7 @@ bool llamafile_sgemm(int64_t m, int64_t n, int64_t k, const void *A, int64_t lda
|
||||
k, (const float *)A, lda,
|
||||
(const float *)B, ldb,
|
||||
(float *)C, ldc,
|
||||
ith, nth};
|
||||
params->ith, params->nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
#else
|
||||
@ -1728,60 +1724,71 @@ bool llamafile_sgemm(int64_t m, int64_t n, int64_t k, const void *A, int64_t lda
|
||||
#endif
|
||||
}
|
||||
|
||||
case GGML_TYPE_BF16: {
|
||||
#if defined(__AVX512BF16__)
|
||||
if (Btype == GGML_TYPE_BF16) {
|
||||
tinyBLAS<32, __m512, __m512bh, ggml_bf16_t, ggml_bf16_t, float> tb{ params, k,
|
||||
(const ggml_bf16_t *)A, lda,
|
||||
(const ggml_bf16_t *)B, ldb,
|
||||
(float *)C, ldc};
|
||||
return tb.matmul(m, n);
|
||||
}
|
||||
#elif defined(__AVX512F__)
|
||||
if (Btype == GGML_TYPE_BF16) {
|
||||
tinyBLAS<16, __m512, __m512, ggml_bf16_t, ggml_bf16_t, float> tb{ params, k,
|
||||
(const ggml_bf16_t *)A, lda,
|
||||
(const ggml_bf16_t *)B, ldb,
|
||||
(float *)C, ldc};
|
||||
return tb.matmul(m, n);
|
||||
}
|
||||
#elif defined(__AVX2__)
|
||||
if (Btype == GGML_TYPE_BF16) {
|
||||
tinyBLAS<8, __m256, __m256, ggml_bf16_t, ggml_bf16_t, float> tb{ params, k,
|
||||
(const ggml_bf16_t *)A, lda,
|
||||
(const ggml_bf16_t *)B, ldb,
|
||||
(float *)C, ldc};
|
||||
return tb.matmul(m, n);
|
||||
}
|
||||
#endif
|
||||
return false;
|
||||
}
|
||||
case GGML_TYPE_F16: {
|
||||
#if defined(__AVX512F__)
|
||||
if (k % 16)
|
||||
return false;
|
||||
if (Btype != GGML_TYPE_F32)
|
||||
return false;
|
||||
tinyBLAS<16, __m512, __m512, ggml_fp16_t, float, float> tb{
|
||||
k, (const ggml_fp16_t *)A, lda,
|
||||
(const float *)B, ldb,
|
||||
(float *)C, ldc,
|
||||
ith, nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
if (Btype == GGML_TYPE_F16) {
|
||||
tinyBLAS<16, __m512, __m512, ggml_fp16_t, ggml_fp16_t, float> tb{ params, k,
|
||||
(const ggml_fp16_t *)A, lda,
|
||||
(const ggml_fp16_t *)B, ldb,
|
||||
(float *)C, ldc};
|
||||
return tb.matmul(m, n);
|
||||
}
|
||||
#elif (defined(__AVX__) || defined(__AVX2__)) && defined(__F16C__)
|
||||
if (k % 8)
|
||||
return false;
|
||||
if (Btype != GGML_TYPE_F32)
|
||||
return false;
|
||||
tinyBLAS<8, __m256, __m256, ggml_fp16_t, float, float> tb{
|
||||
k, (const ggml_fp16_t *)A, lda,
|
||||
(const float *)B, ldb,
|
||||
(float *)C, ldc,
|
||||
ith, nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
if (Btype == GGML_TYPE_F16) {
|
||||
tinyBLAS<8, __m256, __m256, ggml_fp16_t, ggml_fp16_t, float> tb{ params, k,
|
||||
(const ggml_fp16_t *)A, lda,
|
||||
(const ggml_fp16_t *)B, ldb,
|
||||
(float *)C, ldc};
|
||||
return tb.matmul(m, n);
|
||||
}
|
||||
#elif defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && !defined(_MSC_VER)
|
||||
if (n < 8)
|
||||
return false;
|
||||
if (k % 8)
|
||||
return false;
|
||||
if (Btype != GGML_TYPE_F16)
|
||||
return false;
|
||||
tinyBLAS<8, float16x8_t, float16x8_t, ggml_fp16_t, ggml_fp16_t, float> tb{
|
||||
k, (const ggml_fp16_t *)A, lda,
|
||||
(const ggml_fp16_t *)B, ldb,
|
||||
(float *)C, ldc,
|
||||
ith, nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
if (Btype == GGML_TYPE_F16) {
|
||||
tinyBLAS<8, float16x8_t, float16x8_t, ggml_fp16_t, ggml_fp16_t, float> tb{ params,
|
||||
k, (const ggml_fp16_t *)A, lda,
|
||||
(const ggml_fp16_t *)B, ldb,
|
||||
(float *)C, ldc};
|
||||
return tb.matmul(m, n);
|
||||
}
|
||||
#elif defined(__ARM_NEON) && !defined(_MSC_VER)
|
||||
if (k % 4)
|
||||
return false;
|
||||
if (Btype != GGML_TYPE_F32)
|
||||
return false;
|
||||
tinyBLAS<4, float32x4_t, float32x4_t, ggml_fp16_t, float, float> tb{
|
||||
k, (const ggml_fp16_t *)A, lda,
|
||||
(const float *)B, ldb,
|
||||
(float *)C, ldc,
|
||||
ith, nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
#else
|
||||
return false;
|
||||
if (Btype == GGML_TYPE_F32) {
|
||||
tinyBLAS<4, float32x4_t, float32x4_t, ggml_fp16_t, float, float> tb{ params,
|
||||
k, (const ggml_fp16_t *)A, lda,
|
||||
(const float *)B, ldb,
|
||||
(float *)C, ldc};
|
||||
return tb.matmul(m, n);
|
||||
}
|
||||
#endif
|
||||
return false;
|
||||
}
|
||||
|
||||
case GGML_TYPE_Q8_0: {
|
||||
@ -1792,7 +1799,7 @@ bool llamafile_sgemm(int64_t m, int64_t n, int64_t k, const void *A, int64_t lda
|
||||
k, (const block_q8_0 *)A, lda,
|
||||
(const block_q8_0 *)B, ldb,
|
||||
(float *)C, ldc,
|
||||
ith, nth};
|
||||
params->ith, params->nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
#elif defined(__ARM_FEATURE_DOTPROD)
|
||||
@ -1800,7 +1807,7 @@ bool llamafile_sgemm(int64_t m, int64_t n, int64_t k, const void *A, int64_t lda
|
||||
k, (const block_q8_0 *)A, lda,
|
||||
(const block_q8_0 *)B, ldb,
|
||||
(float *)C, ldc,
|
||||
ith, nth};
|
||||
params->ith, params->nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
#else
|
||||
@ -1816,7 +1823,7 @@ bool llamafile_sgemm(int64_t m, int64_t n, int64_t k, const void *A, int64_t lda
|
||||
k, (const block_q4_0 *)A, lda,
|
||||
(const block_q8_0 *)B, ldb,
|
||||
(float *)C, ldc,
|
||||
ith, nth};
|
||||
params->ith, params->nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
#elif defined(__ARM_FEATURE_DOTPROD)
|
||||
@ -1824,7 +1831,7 @@ bool llamafile_sgemm(int64_t m, int64_t n, int64_t k, const void *A, int64_t lda
|
||||
k, (const block_q4_0 *)A, lda,
|
||||
(const block_q8_0 *)B, ldb,
|
||||
(float *)C, ldc,
|
||||
ith, nth};
|
||||
params->ith, params->nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
#else
|
||||
@ -1840,7 +1847,7 @@ bool llamafile_sgemm(int64_t m, int64_t n, int64_t k, const void *A, int64_t lda
|
||||
k, (const block_q5_0 *)A, lda,
|
||||
(const block_q8_0 *)B, ldb,
|
||||
(float *)C, ldc,
|
||||
ith, nth};
|
||||
params->ith, params->nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
#else
|
||||
@ -1856,7 +1863,7 @@ bool llamafile_sgemm(int64_t m, int64_t n, int64_t k, const void *A, int64_t lda
|
||||
k, (const block_iq4_nl *)A, lda,
|
||||
(const block_q8_0 *)B, ldb,
|
||||
(float *)C, ldc,
|
||||
ith, nth};
|
||||
params->ith, params->nth};
|
||||
tb.matmul(m, n);
|
||||
return true;
|
||||
#else
|
||||
@ -1868,6 +1875,7 @@ bool llamafile_sgemm(int64_t m, int64_t n, int64_t k, const void *A, int64_t lda
|
||||
return false;
|
||||
}
|
||||
|
||||
(void)params;
|
||||
(void)m;
|
||||
(void)n;
|
||||
(void)k;
|
||||
@ -1877,8 +1885,6 @@ bool llamafile_sgemm(int64_t m, int64_t n, int64_t k, const void *A, int64_t lda
|
||||
(void)ldb;
|
||||
(void)C;
|
||||
(void)ldc;
|
||||
(void)ith;
|
||||
(void)nth;
|
||||
(void)Atype;
|
||||
(void)Btype;
|
||||
(void)Ctype;
|
||||
|
@ -5,8 +5,8 @@
|
||||
extern "C" {
|
||||
#endif
|
||||
|
||||
bool llamafile_sgemm(int64_t, int64_t, int64_t, const void *, int64_t,
|
||||
const void *, int64_t, void *, int64_t, int, int,
|
||||
bool llamafile_sgemm(const struct ggml_compute_params * params, int64_t, int64_t, int64_t,
|
||||
const void *, int64_t, const void *, int64_t, void *, int64_t,
|
||||
int, int, int);
|
||||
|
||||
#ifdef __cplusplus
|
||||
|
@ -126,6 +126,8 @@ connection = sqlite3.connect(input_file)
|
||||
cursor = connection.cursor()
|
||||
builds = cursor.execute("SELECT DISTINCT build_commit FROM test;").fetchall()
|
||||
|
||||
commit_short_len = len(builds[0][0])
|
||||
|
||||
try:
|
||||
repo = git.Repo(".", search_parent_directories=True)
|
||||
except git.InvalidGitRepositoryError:
|
||||
@ -138,11 +140,11 @@ def find_parent_in_data(commit: git.Commit):
|
||||
seen_hexsha8 = set()
|
||||
while heap:
|
||||
depth, current_commit = heapq.heappop(heap)
|
||||
current_hexsha8 = commit.hexsha[:8]
|
||||
current_hexsha8 = commit.hexsha[:commit_short_len]
|
||||
if (current_hexsha8,) in builds:
|
||||
return current_hexsha8
|
||||
for parent in commit.parents:
|
||||
parent_hexsha8 = parent.hexsha[:8]
|
||||
parent_hexsha8 = parent.hexsha[:commit_short_len]
|
||||
if parent_hexsha8 not in seen_hexsha8:
|
||||
seen_hexsha8.add(parent_hexsha8)
|
||||
heapq.heappush(heap, (depth + 1, parent))
|
||||
@ -156,9 +158,9 @@ def get_all_parent_hexsha8s(commit: git.Commit):
|
||||
|
||||
while unvisited:
|
||||
current_commit = unvisited.pop(0)
|
||||
visited.append(current_commit.hexsha[:8])
|
||||
visited.append(current_commit.hexsha[:commit_short_len])
|
||||
for parent in current_commit.parents:
|
||||
if parent.hexsha[:8] not in visited:
|
||||
if parent.hexsha[:commit_short_len] not in visited:
|
||||
unvisited.append(parent)
|
||||
|
||||
return visited
|
||||
@ -169,10 +171,10 @@ def get_commit_name(hexsha8):
|
||||
if repo is None:
|
||||
return hexsha8
|
||||
for h in repo.heads:
|
||||
if h.commit.hexsha[:8] == hexsha8:
|
||||
if h.commit.hexsha[:commit_short_len] == hexsha8:
|
||||
return h.name
|
||||
for t in repo.tags:
|
||||
if t.commit.hexsha[:8] == hexsha8:
|
||||
if t.commit.hexsha[:commit_short_len] == hexsha8:
|
||||
return t.name
|
||||
return hexsha8
|
||||
|
||||
@ -183,13 +185,13 @@ def get_commit_hexsha8(name):
|
||||
return None
|
||||
for h in repo.heads:
|
||||
if h.name == name:
|
||||
return h.commit.hexsha[:8]
|
||||
return h.commit.hexsha[:commit_short_len]
|
||||
for t in repo.tags:
|
||||
if t.name == name:
|
||||
return t.commit.hexsha[:8]
|
||||
return t.commit.hexsha[:commit_short_len]
|
||||
for c in repo.iter_commits("--all"):
|
||||
if c.hexsha[:8] == name[:8]:
|
||||
return c.hexsha[:8]
|
||||
if c.hexsha[:commit_short_len] == name[:commit_short_len]:
|
||||
return c.hexsha[:commit_short_len]
|
||||
return None
|
||||
|
||||
|
||||
|
@ -26,7 +26,7 @@ function has_cmd {
|
||||
}
|
||||
|
||||
if has_cmd wget; then
|
||||
cmd="wget -q --show-progress -c -O %s/%s %s"
|
||||
cmd="wget -q -c -O %s/%s %s"
|
||||
elif has_cmd curl; then
|
||||
cmd="curl -C - -f --output-dir %s -o %s -L %s"
|
||||
else
|
||||
|
Loading…
Reference in New Issue
Block a user