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LLM-Maroc / llama.cpp /ggml /src /ggml-cpu /llamafile /sgemm.cpp
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 // Copyright 2024 Mozilla Foundation
//
// Permission is hereby granted, free of charge, to any person obtaining
// a copy of this software and associated documentation files (the
// "Software"), to deal in the Software without restriction, including
// without limitation the rights to use, copy, modify, merge, publish,
// distribute, sublicense, and/or sell copies of the Software, and to
// permit persons to whom the Software is furnished to do so, subject to
// the following conditions:
//
// The above copyright notice and this permission notice shall be
// included in all copies or substantial portions of the Software.
//
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
// MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS
// BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN
// ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
// CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
// SOFTWARE.
//
// _ _ ___ _ _ ___
// | |_(_)_ _ _ _| _ ) | /_\ / __|
// | _| | ' \ || | _ \ |__ / _ \\__ \.
// \__|_|_||_\_, |___/____/_/ \_\___/
// |__/
//
// BASIC LINEAR ALGEBRA SUBPROGRAMS
//
//
// This file implements multithreaded CPU matrix multiplication for the
// common contiguous use case C = Aᵀ * B. These kernels are designed to
// have excellent performance[1] for matrices that fit in the CPU cache
// without imposing any overhead such as cache filling or malloc calls.
//
// This implementation does not guarantee any upper bound with rounding
// errors, which grow along with k. Our goal's to maximally exploit the
// hardware for performance, and then use whatever resources remain for
// improving numerical accuracy.
//
// [1] J. Tunney, ‘LLaMA Now Goes Faster on CPUs’, Mar. 2024. [Online].
// Available: https://justine.lol/matmul/. [Accessed: 29-Mar-2024].
#if defined(__GNUC__)
#pragma GCC diagnostic ignored "-Wpedantic"
#pragma GCC diagnostic ignored "-Wignored-attributes"
#endif
#include "sgemm.h"
#include "ggml-impl.h"
#include "ggml-cpu-impl.h"
#include "ggml-quants.h"
#include "simd-mappings.h"
#include <array>
#include <type_traits>
#ifdef _MSC_VER
#define NOINLINE __declspec(noinline)
#else
#define NOINLINE __attribute__((__noinline__))
#endif
#if defined(__ARM_NEON) || defined(__AVX512F__) || defined(__VXE__) || defined(__VXE2__)
#define VECTOR_REGISTERS 32
#else
#define VECTOR_REGISTERS 16
#endif
#define MM256_SET_M128I(a, b) _mm256_insertf128_si256(_mm256_castsi128_si256(b), (a), 1)
namespace {
inline float unhalf(ggml_fp16_t d) {
return GGML_CPU_FP16_TO_FP32(d);
}
////////////////////////////////////////////////////////////////////////////////////////////////////
// VECTORIZED ARITHMETIC OPERATIONS
#if defined(__SSE__) || defined(__AVX__) || defined(__AVX2__) || defined(__AVX512F__)
inline __m128 add(__m128 x, __m128 y) { return _mm_add_ps(x, y); }
inline __m128 sub(__m128 x, __m128 y) { return _mm_sub_ps(x, y); }
inline __m128 mul(__m128 x, __m128 y) { return _mm_mul_ps(x, y); }
#endif // __SSE__
#if defined(__AVX__) || defined(__AVX2__) || defined(__AVX512F__)
inline __m256 add(__m256 x, __m256 y) { return _mm256_add_ps(x, y); }
inline __m256 sub(__m256 x, __m256 y) { return _mm256_sub_ps(x, y); }
inline __m256 mul(__m256 x, __m256 y) { return _mm256_mul_ps(x, y); }
#endif // __AVX__
#if defined(__AVX512F__)
inline __m512 add(__m512 x, __m512 y) { return _mm512_add_ps(x, y); }
inline __m512 sub(__m512 x, __m512 y) { return _mm512_sub_ps(x, y); }
inline __m512 mul(__m512 x, __m512 y) { return _mm512_mul_ps(x, y); }
#endif // __AVX512F__
#if defined(__ARM_NEON)
inline float32x4_t add(float32x4_t x, float32x4_t y) { return vaddq_f32(x, y); }
inline float32x4_t sub(float32x4_t x, float32x4_t y) { return vsubq_f32(x, y); }
inline float32x4_t mul(float32x4_t x, float32x4_t y) { return vmulq_f32(x, y); }
#endif // __ARM_NEON
#if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC)
inline float16x8_t add(float16x8_t x, float16x8_t y) { return vaddq_f16(x, y); }
inline float16x8_t sub(float16x8_t x, float16x8_t y) { return vsubq_f16(x, y); }
inline float16x8_t mul(float16x8_t x, float16x8_t y) { return vmulq_f16(x, y); }
#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
#if defined(__VXE__) || defined(__VXE2__)
inline float32x4_t add(float32x4_t x, float32x4_t y) { return vec_add(x, y); }
inline float32x4_t sub(float32x4_t x, float32x4_t y) { return vec_sub(x, y); }
inline float32x4_t mul(float32x4_t x, float32x4_t y) { return vec_mul(x, y); }
#endif
#if defined(__MMA__)
typedef vector unsigned char vec_t;
typedef __vector_quad acc_t;
#endif
////////////////////////////////////////////////////////////////////////////////////////////////////
// VECTORIZED FUSED MULTIPLY ADD
/**
* Computes a * b + c.
*/
template <typename T, typename U>
inline U madd(T a, T b, U c) {
return add(mul(a, b), c);
}
#if defined(__FMA__)
#if defined(__AVX__) || defined(__AVX2__) || defined(__AVX512F__)
template <>
inline __m256 madd(__m256 a, __m256 b, __m256 c) {
return _mm256_fmadd_ps(a, b, c);
}
#endif
#if defined(__AVX512F__)
template <>
inline __m512 madd(__m512 a, __m512 b, __m512 c) {
return _mm512_fmadd_ps(a, b, c);
}
#endif
#if defined(__AVX512BF16__)
template <>
inline __m512 madd(__m512bh a, __m512bh b, __m512 c) {
return _mm512_dpbf16_ps(c, a, b);
}
template <>
inline __m256 madd(__m256bh a, __m256bh b, __m256 c) {
return _mm256_dpbf16_ps(c, a, b);
}
#endif
#endif
#if defined(__ARM_FEATURE_FMA)
template <>
inline float32x4_t madd(float32x4_t a, float32x4_t b, float32x4_t c) {
return vfmaq_f32(c, b, a);
}
#if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && !defined(_MSC_VER)
template <>
inline float16x8_t madd(float16x8_t a, float16x8_t b, float16x8_t c) {
return vfmaq_f16(c, b, a);
}
#endif
#endif
#if defined(__VXE__) || defined(__VXE2__)
template <>
inline float32x4_t madd(float32x4_t a, float32x4_t b, float32x4_t c) {
return vec_madd(a, b, c);
}
#endif
////////////////////////////////////////////////////////////////////////////////////////////////////
// VECTORIZED HORIZONTAL SUM
#if defined(__ARM_NEON)
inline float hsum(float32x4_t x) {
return vaddvq_f32(x);
}
#endif // __ARM_NEON
#if defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC) && !defined(_MSC_VER)
inline float hsum(float16x8_t x) {
return vaddvq_f32(vaddq_f32(vcvt_f32_f16(vget_low_f16(x)),
vcvt_f32_f16(vget_high_f16(x))));
}
#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
#if defined(__VXE__) || defined(__VXE2__)
inline float hsum(float32x4_t x) {
float32x4_t tmp = x + vec_reve(x);
return tmp[0] + tmp[1];
}
#endif
#if defined(__SSE__) || defined(__AVX__) || defined(__AVX2__) || defined(__AVX512F__)
inline float hsum(__m128 x) {
#if defined(__AVX__) || defined(__AVX2__) || defined(__AVX512F__)
x = _mm_add_ps(x, _mm_movehl_ps(x, x));
x = _mm_add_ss(x, _mm_movehdup_ps(x));
#else
__m128 t;
t = _mm_shuffle_ps(x, x, _MM_SHUFFLE(2, 3, 0, 1));
x = _mm_add_ps(x, t);
t = _mm_movehl_ps(t, x);
x = _mm_add_ss(x, t);
#endif
return _mm_cvtss_f32(x);
}
#endif
#if defined(__AVX__) || defined(__AVX2__) || defined(__AVX512F__)
inline float hsum(__m256 x) {
return hsum(_mm_add_ps(_mm256_extractf128_ps(x, 1),
_mm256_castps256_ps128(x)));
}
#endif // __AVX__
#if defined(__AVX512F__)
inline float hsum(__m512 x) {
return _mm512_reduce_add_ps(x);
}
#endif // __AVX512F__
////////////////////////////////////////////////////////////////////////////////////////////////////
// VECTORIZED MEMORY LOADING
template <typename T, typename U> T load(const U *);
#if defined(__ARM_NEON)
template <> inline float32x4_t load(const float *p) {
return vld1q_f32(p);
}
#if !defined(_MSC_VER)
// FIXME: this should check for __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
template <> inline float16x8_t load(const ggml_fp16_t *p) {
return vld1q_f16((const float16_t *)p);
}
template <> inline float32x4_t load(const ggml_fp16_t *p) {
return vcvt_f32_f16(vld1_f16((const float16_t *)p));
}
#endif // _MSC_VER
#endif // __ARM_NEON
#if defined(__VXE__) || defined(__VXE2__)
template <> inline float32x4_t load(const ggml_fp16_t * p) {
float tmp[4];
for (int i = 0; i < 4; i++) {
tmp[i] = GGML_CPU_FP16_TO_FP32(p[i]);
}
return vec_xl(0, (const float *)(tmp));
}
template <> inline float32x4_t load(const float * p) {
return vec_xl(0, p);
}
#endif
#if defined(__SSE__) || defined(__AVX__) || defined(__AVX2__) || defined(__AVX512F__)
template <> inline __m128 load(const float *p) {
return _mm_loadu_ps(p);
}
#endif // __SSE__
#if defined(__AVX__) || defined(__AVX2__) || defined(__AVX512F__)
template <> inline __m256 load(const float *p) {
return _mm256_loadu_ps(p);
}
#endif // __AVX__
#if defined(__AVX2__) || defined(__AVX512F__)
template <> inline __m256 load(const ggml_bf16_t *p) {
return _mm256_castsi256_ps(
_mm256_slli_epi32(_mm256_cvtepu16_epi32(_mm_loadu_si128((const __m128i *)p)), 16));
}
#endif // __AVX2__
#if defined(__F16C__)
template <> inline __m256 load(const ggml_fp16_t *p) {
return _mm256_cvtph_ps(_mm_loadu_si128((const __m128i *)p));
}
#endif // __F16C__
#if defined(__AVX512F__)
template <> inline __m512 load(const float *p) {
return _mm512_loadu_ps(p);
}
template <> inline __m512 load(const ggml_fp16_t *p) {
return _mm512_cvtph_ps(_mm256_loadu_si256((const __m256i *)p));
}
template <> inline __m512 load(const ggml_bf16_t *p) {
return _mm512_castsi512_ps(
_mm512_slli_epi32(_mm512_cvtepu16_epi32(_mm256_loadu_si256((const __m256i *)p)), 16));
}
#endif // __AVX512F__
#if defined(__AVX512BF16__)
template <> inline __m512bh load(const ggml_bf16_t *p) {
return (__m512bh)_mm512_loadu_ps((const float *)p);
}
template <> inline __m256bh load(const ggml_bf16_t *p) {
return (__m256bh)_mm256_loadu_ps((const float *)p);
}
template <> inline __m512bh load(const float *p) {
return _mm512_cvtne2ps_pbh(_mm512_loadu_ps(p + 16), _mm512_loadu_ps(p));
}
template <> inline __m256bh load(const float *p) {
return _mm512_cvtneps_pbh(_mm512_loadu_ps(p));
}
#endif
////////////////////////////////////////////////////////////////////////////////////////////////////
// FLOATING POINT MATRIX MULTIPLICATION
template <int M>
static inline int64_t BLOCK_SIZE(size_t m) {
const int64_t NB_BLOC_M = (m + M - 1) / M;
return (m % NB_BLOC_M == 0) ? m / NB_BLOC_M : (m / NB_BLOC_M) + 1;
}
static constexpr inline int64_t BLOC_POS(int64_t ib, int64_t ibN, int64_t bloc_size) {
return ib < ibN ? ib * bloc_size : ibN * bloc_size + (ib - ibN) * (bloc_size - 1);
}
template <int KN, typename D, typename V, typename TA, typename TB, typename TC>
class tinyBLAS {
public:
tinyBLAS(const ggml_compute_params * params, int64_t k,
const TA *A, int64_t lda,
const TB *B, int64_t ldb,
TC *C, int64_t ldc)
: params(params), A(A), B(B), C(C), k(k), lda(lda), ldb(ldb), ldc(ldc) {
}
bool matmul(int64_t m, int64_t n) {
if (k % KN != 0)
return false;
// compute RM for only need tile with size RM&RM-1
#if VECTOR_REGISTERS == 32
if (m % 16 == 0 && (m/16 >= params->nth)) {
const int64_t SIZE_N = BLOCK_SIZE<6>(n);
mnpack<4, 6, 4>(m, n, SIZE_N, 12);
return true;
}
if (m % 8 == 0 ) {
const int64_t SIZE_N = BLOCK_SIZE<6>(n);
mnpack<4, 6, 2>(m, n, SIZE_N, 12);
return true;
}
if (m % 4 == 0) {
const int64_t SIZE_N = BLOCK_SIZE<6>(n);
mnpack<4, 6, 1>(m, n, SIZE_N, 12);
return true;
}
#else // VECTOR_REGISTERS == 16
if (m % 16 == 0 && (m/16 >= params->nth)) {
const int64_t SIZE_N = BLOCK_SIZE<3>(n);
mnpack<4, 3, 4>(m, n, SIZE_N, 24);
return true;
}
if (m % 8 == 0 ) {
const int64_t SIZE_N = BLOCK_SIZE<3>(n);
mnpack<4, 3, 2>(m, n, SIZE_N, 24);
return true;
}
if (m % 4 == 0) {
const int64_t SIZE_N = BLOCK_SIZE<3>(n);
mnpack<4, 3, 1>(m, n, SIZE_N, 24);
return true;
}
#endif
return false;
}
private:
template <int RM, int RN, int BM>
inline void mnpack(int64_t m, int64_t n, int64_t SIZE_N, int64_t BN) {
if (SIZE_N == RN) {
return gemm<RM, RN, BM>(m, n, BN);
}
if constexpr (RN > 1) {
return mnpack<RM, RN-1, BM>(m, n, SIZE_N, BN);
} else {
GGML_LOG_ERROR("mnpack<%d, %d> bloc size not supported\n", RM, (int)SIZE_N);
GGML_ASSERT(false); // we have miss something.
}
}
template <int RM, int RN>
inline void gemm_bloc(int64_t ii, int64_t jj) {
D Cv[RN][RM] = {};
for (int64_t l = 0; l < k; l += KN) {
// help compiler for op order.
if constexpr (RM <= RN) {
V Av[RM];
for (int64_t i = 0; i < RM; ++i) {
Av[i] = load<V>(A + lda * (ii + i) + l);
}
for (int64_t j = 0; j < RN; ++j) {
V Bv = load<V>(B + ldb * (jj + j) + l);
for (int64_t i = 0; i < RM; ++i) {
Cv[j][i] = madd(Av[i], Bv, Cv[j][i]);
}
}
} else {
V Bv[RN];
for (int64_t j = 0; j < RN; ++j) {
Bv[j] = load<V>(B + ldb * (jj + j) + l);
}
for (int64_t i = 0; i < RM; ++i) {
V Av = load<V>(A + lda * (ii + i) + l);
for (int64_t j = 0; j < RN; ++j) {
Cv[j][i] = madd(Av, Bv[j], Cv[j][i]);
}
}
}
}
for (int64_t j = 0; j < RN; ++j)
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) {
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.
ggml_threadpool_chunk_set(params->threadpool, params->nth);
}
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);
}
job = ggml_threadpool_chunk_add(params->threadpool, 1);
}
ggml_barrier(params->threadpool);
return;
}
const ggml_compute_params * params;
const TA *const A;
const TB *const B;
TC *const C;
const int64_t k;
const int64_t lda;
const int64_t ldb;
const int64_t ldc;
};
//////////////////////////////////////////////////////////////////////////////////////////
// QUANT ZERO MATRIX MULTIPLICATION
#if defined(__ARM_FEATURE_DOTPROD)
template <typename TA>
class tinyBLAS_Q0_ARM {
public:
tinyBLAS_Q0_ARM(int64_t k,
const TA *A, int64_t lda,
const block_q8_0 *B, int64_t ldb,
float *C, int64_t ldc,
int ith, int nth)
: A(A), B(B), C(C), k(k), lda(lda), ldb(ldb), ldc(ldc), ith(ith), nth(nth) {
}
void matmul(int64_t m, int64_t n) {
mnpack(0, m, 0, n);
}
private:
NOINLINE void mnpack(int64_t m0, int64_t m, int64_t n0, int64_t n) {
int64_t mc, nc, mp, np;
switch ((MIN(m - m0, 3) << 4) | MIN(n - n0, 3ll)) {
case 0x33:
mc = 3;
nc = 3;
gemm<3, 3>(m0, m, n0, n);
break;
case 0x32:
mc = 3;
nc = 2;
gemm<3, 2>(m0, m, n0, n);
break;
case 0x23:
mc = 2;
nc = 3;
gemm<2, 3>(m0, m, n0, n);
break;
case 0x22:
mc = 2;
nc = 2;
gemm<2, 2>(m0, m, n0, n);
break;
case 0x31:
mc = 3;
nc = 1;
gemm<3, 1>(m0, m, n0, n);
break;
case 0x13:
mc = 1;
nc = 3;
gemm<1, 3>(m0, m, n0, n);
break;
case 0x21:
mc = 2;
nc = 1;
gemm<2, 1>(m0, m, n0, n);
break;
case 0x12:
mc = 1;
nc = 2;
gemm<1, 2>(m0, m, n0, n);
break;
case 0x11:
mc = 1;
nc = 1;
gemm<1, 1>(m0, m, n0, n);
break;
default:
return;
}
mp = m0 + (m - m0) / mc * mc;
np = n0 + (n - n0) / nc * nc;
mnpack(mp, m, n0, np);
mnpack(m0, m, np, n);
}
template <int RM, int RN>
NOINLINE void gemm(int64_t m0, int64_t m, int64_t n0, int64_t n) {
int64_t ytiles = (m - m0) / RM;
int64_t xtiles = (n - n0) / RN;
int64_t tiles = xtiles * ytiles;
int64_t duty = (tiles + nth - 1) / nth;
int64_t start = duty * ith;
int64_t end = start + duty;
if (end > tiles)
end = tiles;
for (int64_t job = start; job < end; ++job) {
int64_t ii = m0 + job / xtiles * RM;
int64_t jj = n0 + job % xtiles * RN;
float32x4_t Cv[RN][RM] = {};
for (int64_t l = 0; l < k; ++l)
for (int64_t j = 0; j < RN; ++j)
for (int64_t i = 0; i < RM; ++i)
Cv[j][i] = vmlaq_n_f32(Cv[j][i],
vcvtq_f32_s32(vdotq_s32(
vdotq_s32(vdupq_n_s32(0),
load_lo(A + lda * (ii + i) + l),
load_lo(B + ldb * (jj + j) + l)),
load_hi(A + lda * (ii + i) + l),
load_hi(B + ldb * (jj + j) + l))),
unhalf(A[lda * (ii + i) + l].d) *
unhalf(B[ldb * (jj + j) + l].d));
for (int64_t j = 0; j < RN; ++j)
for (int64_t i = 0; i < RM; ++i)
C[ldc * (jj + j) + (ii + i)] = hsum(Cv[j][i]);
}
}
inline int8x16_t load_lo(const block_q8_0 *b) {
return vld1q_s8(b->qs);
}
inline int8x16_t load_hi(const block_q8_0 *b) {
return vld1q_s8(b->qs + 16);
}
inline int8x16_t load_lo(const block_q4_0 *b) {
return vsubq_s8(vreinterpretq_s8_u8(vandq_u8(vld1q_u8(b->qs),
vdupq_n_u8(0x0f))),
vdupq_n_s8(0x8));
}
inline int8x16_t load_hi(const block_q4_0 *b) {
return vsubq_s8(vreinterpretq_s8_u8(vshrq_n_u8(vld1q_u8(b->qs), 4)),
vdupq_n_s8(0x8));
}
const TA *const A;
const block_q8_0 *const B;
float *const C;
const int64_t k;
const int64_t lda;
const int64_t ldb;
const int64_t ldc;
const int ith;
const int nth;
};
#endif // __ARM_FEATURE_DOTPROD
#if defined(__AVX2__) || defined(__AVX512F__) || defined(__AVX__)
template <typename TA, typename TB, typename TC>
class tinyBLAS_Q0_AVX {
public:
tinyBLAS_Q0_AVX(int64_t k,
const TA *A, int64_t lda,
const TB *B, int64_t ldb,
TC *C, int64_t ldc,
int ith, int nth)
: A(A), B(B), C(C), k(k), lda(lda), ldb(ldb), ldc(ldc), ith(ith), nth(nth) {
const int8_t kvalues_iq4nl[16] = {
-127, -104, -83, -65,
-49, -35, -22, -10,
1, 13, 25, 38,
53, 69, 89, 113
};
iq4nlt = _mm_loadu_si128((const __m128i *)kvalues_iq4nl);
}
void matmul(int64_t m, int64_t n) {
mnpack(0, m, 0, n);
}
private:
void mnpack(int64_t m0, int64_t m, int64_t n0, int64_t n) {
int64_t mc, nc, mp, np;
switch ((MIN(m - m0, 4) << 4) | MIN(n - n0, 4)) {
#if VECTOR_REGISTERS == 32
case 0x44:
mc = 4;
nc = 4;
#if defined(__AVX2__) && defined(__F16C__)
gemm4xN<4>(m0, m, n0, n);
#else
gemm<4, 4>(m0, m, n0, n);
#endif
break;
case 0x43:
mc = 4;
nc = 3;
#if defined(__AVX2__) && defined(__F16C__)
gemm4xN<3>(m0, m, n0, n);
#else
gemm<4, 3>(m0, m, n0, n);
#endif
break;
case 0x34:
mc = 3;
nc = 4;
#if defined(__AVX2__) && defined(__F16C__)
gemmMx4<3>(m0, m, n0, n);
#else
gemm<3, 4>(m0, m, n0, n);
#endif
break;
case 0x33:
mc = 3;
nc = 3;
gemm<3, 3>(m0, m, n0, n);
break;
case 0x42:
mc = 4;
nc = 2;
#if defined(__AVX2__) && defined(__F16C__)
gemm4xN<2>(m0, m, n0, n);
#else
gemm<4, 2>(m0, m, n0, n);
#endif
break;
case 0x24:
mc = 2;
nc = 4;
#if defined(__AVX2__) && defined(__F16C__)
gemmMx4<2>(m0, m, n0, n);
#else
gemm<2, 4>(m0, m, n0, n);
#endif
break;
#else
case 0x44:
case 0x43:
case 0x42:
mc = 4;
nc = 2;
#if defined(__AVX2__) && defined(__F16C__)
gemm4xN<2>(m0, m, n0, n);
#else
gemm<4, 2>(m0, m, n0, n);
#endif
break;
case 0x34:
case 0x24:
mc = 2;
nc = 4;
#if defined(__AVX2__) && defined(__F16C__)
gemmMx4<2>(m0, m, n0, n);
#else
gemm<2, 4>(m0, m, n0, n);
#endif
break;
case 0x33:
#endif
case 0x32:
mc = 3;
nc = 2;
gemm<3, 2>(m0, m, n0, n);
break;
case 0x23:
mc = 2;
nc = 3;
gemm<2, 3>(m0, m, n0, n);
break;
case 0x41:
mc = 4;
nc = 1;
#if defined(__AVX2__) && defined(__F16C__)
gemm4xN<1>(m0, m, n0, n);
#else
gemm<4, 1>(m0, m, n0, n);
#endif
break;
case 0x22:
mc = 2;
nc = 2;
gemm<2, 2>(m0, m, n0, n);
break;
case 0x14:
mc = 1;
nc = 4;
#if defined(__AVX2__) && defined(__F16C__)
gemmMx4<1>(m0, m, n0, n);
#else
gemm<1, 4>(m0, m, n0, n);
#endif
break;
case 0x31:
mc = 3;
nc = 1;
gemm<3, 1>(m0, m, n0, n);
break;
case 0x13:
mc = 1;
nc = 3;
gemm<1, 3>(m0, m, n0, n);
break;
case 0x21:
mc = 2;
nc = 1;
gemm<2, 1>(m0, m, n0, n);
break;
case 0x12:
mc = 1;
nc = 2;
gemm<1, 2>(m0, m, n0, n);
break;
case 0x11:
mc = 1;
nc = 1;
gemm<1, 1>(m0, m, n0, n);
break;
default:
return;
}
mp = m0 + (m - m0) / mc * mc;
np = n0 + (n - n0) / nc * nc;
mnpack(mp, m, n0, np);
mnpack(m0, m, np, n);
}
#if defined(__AVX2__) && defined(__F16C__)
// Templated functions for gemm of dimensions 4xN
template <int RN>
NOINLINE void gemm4xN(int64_t m0, int64_t m, int64_t n0, int64_t n) {
int64_t ytiles = (m - m0) / 4;
int64_t xtiles = (n - n0) / RN;
int64_t tiles = xtiles * ytiles;
int64_t duty = (tiles + nth - 1) / nth;
int64_t start = duty * ith;
int64_t end = start + duty;
if (end > tiles)
end = tiles;
for (int64_t job = start; job < end; ++job) {
int64_t ii = m0 + job / xtiles * 4;
int64_t jj = n0 + job % xtiles * RN;
__m256 Cv[RN][4] = {};
for (int64_t l = 0; l < k; ++l) {
uint64_t a_delta = ((uint64_t)A[lda * (ii + 3) + l].d << 48) | ((uint64_t)A[lda * (ii + 2) + l].d << 32) | ((uint64_t)A[lda * (ii + 1) + l].d << 16) | (A[lda * (ii + 0) + l].d);
// Convert delta values for four blocks to float values
__m128 da = _mm_cvtph_ps(_mm_set_epi64x(0, a_delta));
__m256i avec0 = load(A + lda * (ii + 0) + l);
__m256i avec1 = load(A + lda * (ii + 1) + l);
__m256i avec2 = load(A + lda * (ii + 2) + l);
__m256i avec3 = load(A + lda * (ii + 3) + l);
for (int64_t j = 0; j < RN; ++j) {
__m128 db = _mm_set1_ps(unhalf(B[ldb * (jj + j) + l].d));
// Computation of product of delta values for four blocks and replicate it across 256 bit lane
__m256 dvec = _mm256_castps128_ps256(_mm_mul_ps(da, db));
dvec = _mm256_permute2f128_ps(dvec ,dvec, 0);
// Computation of dot product and multiplication with appropriate delta value products
Cv[j][0] = madd(_mm256_shuffle_ps(dvec, dvec, 0),
updot(_mm256_sign_epi8(avec0, avec0),
_mm256_sign_epi8(load(B + ldb * (jj + j) + l), avec0)),
Cv[j][0]);
Cv[j][1] = madd(_mm256_shuffle_ps(dvec, dvec, 85),
updot(_mm256_sign_epi8(avec1, avec1),
_mm256_sign_epi8(load(B + ldb * (jj + j) + l), avec1)),
Cv[j][1]);
Cv[j][2] = madd(_mm256_shuffle_ps(dvec, dvec, 170),
updot(_mm256_sign_epi8(avec2, avec2),
_mm256_sign_epi8(load(B + ldb * (jj + j) + l), avec2)),
Cv[j][2]);
Cv[j][3] = madd(_mm256_shuffle_ps(dvec, dvec, 255),
updot(_mm256_sign_epi8(avec3, avec3),
_mm256_sign_epi8(load(B + ldb * (jj + j) + l), avec3)),
Cv[j][3]);
}
}
for (int64_t j = 0; j < RN; ++j)
for (int64_t i = 0; i < 4; ++i)
C[ldc * (jj + j) + (ii + i)] = hsum(Cv[j][i]);
}
}
// Templated functions for gemm of dimensions Mx4
template <int RM>
NOINLINE void gemmMx4(int64_t m0, int64_t m, int64_t n0, int64_t n) {
int64_t ytiles = (m - m0) / RM;
int64_t xtiles = (n - n0) / 4;
int64_t tiles = xtiles * ytiles;
int64_t duty = (tiles + nth - 1) / nth;
int64_t start = duty * ith;
int64_t end = start + duty;
if (end > tiles)
end = tiles;
for (int64_t job = start; job < end; ++job) {
int64_t ii = m0 + job / xtiles * RM;
int64_t jj = n0 + job % xtiles * 4;
__m256 Cv[4][RM] = {};
for (int64_t l = 0; l < k; ++l) {
uint64_t b_delta = ((uint64_t)B[ldb * (jj + 3) + l].d << 48) | ((uint64_t)B[ldb * (jj + 2) + l].d << 32) | ((uint64_t)B[ldb * (jj + 1) + l].d << 16) | (B[ldb * (jj + 0) + l].d);
// Convert delta values for four blocks to float values
__m128 db = _mm_cvtph_ps(_mm_set_epi64x(0, b_delta));
__m256i bvec0 = load(B + ldb * (jj + 0) + l);
__m256i bvec1 = load(B + ldb * (jj + 1) + l);
__m256i bvec2 = load(B + ldb * (jj + 2) + l);
__m256i bvec3 = load(B + ldb * (jj + 3) + l);
for (int64_t i = 0; i < RM; ++i) {
__m128 da = _mm_set1_ps(unhalf((A[lda * (ii + i) + l].d)));
// Computation of product of delta values for four blocks and replicate it across 256 bit lane
__m256 dvec = _mm256_castps128_ps256(_mm_mul_ps(da, db));
dvec = _mm256_permute2f128_ps(dvec ,dvec, 0);
// Computation of dot product and multiplication with appropriate delta value products
Cv[0][i] = madd(_mm256_shuffle_ps(dvec, dvec, 0),
updot(_mm256_sign_epi8(load(A + lda * (ii + i) + l),
load(A + lda * (ii + i) + l)),
_mm256_sign_epi8(bvec0, load(A + lda * (ii + i) + l))),
Cv[0][i]);
Cv[1][i] = madd(_mm256_shuffle_ps(dvec, dvec, 85),
updot(_mm256_sign_epi8(load(A + lda * (ii + i) + l),
load(A + lda * (ii + i) + l)),
_mm256_sign_epi8(bvec1, load(A + lda * (ii + i) + l))),
Cv[1][i]);
Cv[2][i] = madd(_mm256_shuffle_ps(dvec, dvec, 170),
updot(_mm256_sign_epi8(load(A + lda * (ii + i) + l),
load(A + lda * (ii + i) + l)),
_mm256_sign_epi8(bvec2, load(A + lda * (ii + i) + l))),
Cv[2][i]);
Cv[3][i] = madd(_mm256_shuffle_ps(dvec, dvec, 255),
updot(_mm256_sign_epi8(load(A + lda * (ii + i) + l),
load(A + lda * (ii + i) + l)),
_mm256_sign_epi8(bvec3, load(A + lda * (ii + i) + l))),
Cv[3][i]);
}
}
for (int64_t j = 0; j < 4; ++j)
for (int64_t i = 0; i < RM; ++i)
C[ldc * (jj + j) + (ii + i)] = hsum(Cv[j][i]);
}
}
#endif
template <int RM, int RN>
NOINLINE void gemm(int64_t m0, int64_t m, int64_t n0, int64_t n) {
int64_t ytiles = (m - m0) / RM;
int64_t xtiles = (n - n0) / RN;
int64_t tiles = xtiles * ytiles;
int64_t duty = (tiles + nth - 1) / nth;
int64_t start = duty * ith;
int64_t end = start + duty;
if (end > tiles)
end = tiles;
for (int64_t job = start; job < end; ++job) {
int64_t ii = m0 + job / xtiles * RM;
int64_t jj = n0 + job % xtiles * RN;
__m256 Cv[RN][RM] = {};
for (int64_t l = 0; l < k; ++l)
for (int64_t j = 0; j < RN; ++j)
for (int64_t i = 0; i < RM; ++i) {
#if defined(__AVX2__)
__m256 udTmp = updot(_mm256_sign_epi8(load(A + lda * (ii + i) + l),
load(A + lda * (ii + i) + l)),
_mm256_sign_epi8(load(B + ldb * (jj + j) + l),
load(A + lda * (ii + i) + l)));
#else
__m128i ali0 = load0(A + lda * (ii + i) + l);
__m128i ali1 = load1(A + lda * (ii + i) + l);
__m128i blj0 = load0(B + ldb * (jj + j) + l);
__m128i blj1 = load1(B + ldb * (jj + j) + l);
__m128i sepAA0 = _mm_sign_epi8(ali0, ali0);
__m128i sepAA1 = _mm_sign_epi8(ali1, ali1);
__m128i sepBA0 = _mm_sign_epi8(blj0, ali0);
__m128i sepBA1 = _mm_sign_epi8(blj1, ali1);
// updot
const __m128i oneFill = _mm_set1_epi16(1);
__m128i mad0 = _mm_maddubs_epi16(sepAA0, sepBA0);
__m128i mad1 = _mm_maddubs_epi16(sepAA1, sepBA1);
__m256 udTmp = _mm256_cvtepi32_ps(MM256_SET_M128I(_mm_madd_epi16(oneFill, mad1), _mm_madd_epi16(oneFill, mad0)));
#endif
Cv[j][i] = madd(_mm256_set1_ps(unhalf(A[lda * (ii + i) + l].d) *
unhalf(B[ldb * (jj + j) + l].d)),
udTmp,
Cv[j][i]);
}
for (int64_t j = 0; j < RN; ++j)
for (int64_t i = 0; i < RM; ++i)
C[ldc * (jj + j) + (ii + i)] = hsum(Cv[j][i]);
}
}
inline __m256i load(const block_q8_0 *b) {
return _mm256_loadu_si256((const __m256i *)b->qs);
}
inline __m128i load0(const block_q8_0 *b) {
return _mm_loadu_si128((const __m128i *)b->qs);
}
inline __m128i load1(const block_q8_0 *b) {
return _mm_loadu_si128(((const __m128i *)b->qs) + 1);
}
inline __m256i load(const block_q4_0 *b) {
return _mm256_sub_epi8(denibble(b->qs), _mm256_set1_epi8(8));
}
inline __m128i load0(const block_q4_0 *b) {
const __m128i x = _mm_loadu_si128((const __m128i *)(b->qs));
return _mm_sub_epi8(_mm_and_si128(_mm_set1_epi8(15), x), _mm_set1_epi8(8));
}
inline __m128i load1(const block_q4_0 *b) {
const __m128i x = _mm_loadu_si128((const __m128i *)(b->qs));
return _mm_sub_epi8(_mm_and_si128(_mm_set1_epi8(15), _mm_srli_epi16(x, 4)), _mm_set1_epi8(8));
}
inline __m256i load(const block_q5_0 *b) {
return _mm256_or_si256(denibble(b->qs), bittobyte(b->qh));
}
inline __m128i load0(const block_q5_0* b) {
const __m128i x = _mm_loadu_si128((const __m128i *)(b->qs));
uint32_t x32;
memcpy(&x32, b->qh, sizeof(uint32_t));
__m128i qxl = _mm_and_si128(_mm_set1_epi8(15), x);
__m128i bytesl = _mm_cmpeq_epi8(_mm_set1_epi64x(-1),
_mm_or_si128(_mm_set1_epi64x(0x7fbfdfeff7fbfdfe),
_mm_shuffle_epi8(_mm_set1_epi32(x32),
_mm_set_epi64x(0x0101010101010101, 0x0000000000000000))));
bytesl = _mm_andnot_si128(bytesl, _mm_set1_epi8((char)0xF0));
return _mm_or_si128(qxl, bytesl);
}
inline __m128i load1(const block_q5_0* b) {
const __m128i x = _mm_loadu_si128((const __m128i *)(b->qs));
uint32_t x32;
memcpy(&x32, b->qh, sizeof(uint32_t));
__m128i qxh = _mm_and_si128(_mm_set1_epi8(15), _mm_srli_epi16(x, 4));
__m128i bytesh = _mm_cmpeq_epi8(_mm_set1_epi64x(-1),
_mm_or_si128(_mm_set1_epi64x(0x7fbfdfeff7fbfdfe),
_mm_shuffle_epi8(_mm_set1_epi32(x32),
_mm_set_epi64x(0x0303030303030303, 0x0202020202020202))));
bytesh = _mm_andnot_si128(bytesh, _mm_set1_epi8((char)0xF0));
return _mm_or_si128(qxh, bytesh);
}
inline __m256i load(const block_iq4_nl *b) {
return MM256_SET_M128I(load1(b), load0(b));
}
inline __m128i load0(const block_iq4_nl *b) {
const __m128i x = _mm_loadu_si128((const __m128i *)(b->qs));
return _mm_shuffle_epi8(iq4nlt, _mm_and_si128(_mm_set1_epi8(15), x));
}
inline __m128i load1(const block_iq4_nl *b) {
const __m128i x = _mm_loadu_si128((const __m128i *)(b->qs));
return _mm_shuffle_epi8(iq4nlt, _mm_and_si128(_mm_set1_epi8(15), _mm_srli_epi16(x, 4)));
}
inline __m256 updot(__m256i u, __m256i s) {
__m256i res;
#if defined(__AVX512VNNI__) && defined(__AVX512VL__)
res = _mm256_dpbusd_epi32(_mm256_setzero_si256(), u, s);
#elif defined(__AVXVNNI__)
res = _mm256_dpbusd_avx_epi32(_mm256_setzero_si256(), u, s);
#else
res = _mm256_madd_epi16(_mm256_set1_epi16(1), _mm256_maddubs_epi16(u, s));
#endif
return _mm256_cvtepi32_ps(res);
}
static inline __m256i denibble(const uint8_t *p) {
__m128i x = _mm_loadu_si128((const __m128i *)p);
return _mm256_and_si256(_mm256_set1_epi8(15),
_mm256_insertf128_si256(_mm256_castsi128_si256(x),
_mm_srli_epi16(x, 4), 1));
}
static inline __m256i bittobyte(const uint8_t *p) {
uint32_t x32;
memcpy(&x32, p, sizeof(uint32_t));
__m256i bytes = _mm256_cmpeq_epi8(_mm256_set1_epi64x(-1),
_mm256_or_si256(_mm256_set1_epi64x(0x7fbfdfeff7fbfdfe),
_mm256_shuffle_epi8(_mm256_set1_epi32(x32),
_mm256_set_epi64x(0x0303030303030303, 0x0202020202020202,
0x0101010101010101, 0x0000000000000000))));
return _mm256_andnot_si256(bytes, _mm256_set1_epi8((char)0xF0));
}
const TA *const A;
const TB *const B;
TC *const C;
const int64_t k;
const int64_t lda;
const int64_t ldb;
const int64_t ldc;
const int ith;
const int nth;
__m128i iq4nlt;
};
#endif // __AVX__
//PPC Implementation
#if defined(__MMA__)
#define SAVE_ACC(ACC, ii, jj) \
__builtin_mma_disassemble_acc(vec_C, ACC); \
for (int I = 0; I < 4; I++) { \
for (int J = 0; J < 4; J++) { \
*((float*)(C+ii+((jj+J)*ldc)+I)) = *((float*)&vec_C[I]+J); \
} \
} \
template <typename TA, typename TB, typename TC>
class tinyBLAS_BF16_PPC {
public:
tinyBLAS_BF16_PPC(int64_t k,
const TA *A, int64_t lda,
const TB *B, int64_t ldb,
TC *C, int64_t ldc,
int ith, int nth)
: A(A), B(B), C(C), k(k), lda(lda), ldb(ldb), ldc(ldc), ith(ith), nth(nth) {
}
void matmul(int64_t m, int64_t n) {
mnpack(0, m, 0, n);
}
private:
void vector_permute_store(vec_t *c, int numVec, unsigned char *vecOffset) {
vec_t t[8], s[8];
vec_t swiz1 = {0, 1, 2, 3, 16, 17, 18, 19, 4, 5, 6, 7, 20, 21, 22, 23};
vec_t swiz2 = {8, 9, 10, 11, 24, 25, 26, 27, 12, 13, 14, 15, 28, 29, 30, 31};
vec_t swiz3 = {0, 1, 2, 3, 4, 5, 6, 7, 16, 17, 18, 19, 20, 21, 22, 23};
vec_t swiz4 = {8, 9, 10, 11, 12, 13, 14, 15, 24, 25, 26, 27, 28, 29, 30, 31};
if (numVec == 2) {
t[0] = vec_perm(c[0], c[1], swiz1);
t[1] = vec_perm(c[2], c[3], swiz1);
s[0] = vec_perm(t[0], t[1], swiz3);
s[1] = vec_perm(t[0], t[1], swiz4);
vec_xst(s[0], 0, (vec_t*)vecOffset);
vec_xst(s[1], 0, (vec_t*)(vecOffset + 16));
} else if (numVec == 4) {
t[0] = vec_perm(c[0], c[1], swiz1);
t[1] = vec_perm(c[0], c[1], swiz2);
t[2] = vec_perm(c[2], c[3], swiz1);
t[3] = vec_perm(c[2], c[3], swiz2);
s[0] = vec_perm(t[0], t[2], swiz3);
s[1] = vec_perm(t[0], t[2], swiz4);
s[2] = vec_perm(t[1], t[3], swiz3);
s[3] = vec_perm(t[1], t[3], swiz4);
for (int i = 0; i < 4; ++i)
vec_xst(s[i], 0, (vec_t*)(vecOffset + i * 16));
} else if (numVec == 8) {
for (int i = 0; i < 4; i += 2) {
t[i+0] = vec_perm(c[i+0], c[i+1], swiz1);
t[i+1] = vec_perm(c[i+0], c[i+1], swiz2);
}
for (int i = 4; i < 8; i += 2) {
t[i+0] = vec_perm(c[i+0], c[i+1], swiz1);
t[i+1] = vec_perm(c[i+0], c[i+1], swiz2);
}
s[0] = vec_perm(t[0], t[2], swiz3);
s[1] = vec_perm(t[0], t[2], swiz4);
s[2] = vec_perm(t[1], t[3], swiz3);
s[3] = vec_perm(t[1], t[3], swiz4);
s[4] = vec_perm(t[4], t[6], swiz3);
s[5] = vec_perm(t[4], t[6], swiz4);
s[6] = vec_perm(t[5], t[7], swiz3);
s[7] = vec_perm(t[5], t[7], swiz4);
for (int i = 0; i < 8; ++i)
vec_xst(s[i], 0, (vec_t*)(vecOffset + i * 16));
}
}
void packNormal(const TA* a, int64_t lda, int rows, int cols, unsigned char* vec) {
int64_t i, j;
TA *aoffset = NULL;
unsigned char *vecOffset = NULL;
TA * aoffsets[8];
vector unsigned char c_arr[8];
aoffset = const_cast<TA*>(a);
vecOffset = vec;
j = (rows >> 3);
if (j > 0) {
do {
if (cols == 4) {
aoffsets[0] = aoffset;
for (int it = 1; it < 4; ++it)
aoffsets[it] = aoffsets[it-1] + lda;
aoffset += 4 * lda;
for (int i = 0; i < 4; ++i)
c_arr[i] = vec_xl(0, (vector unsigned char*)aoffsets[i]);
vector_permute_store(c_arr, 4, vecOffset);
for (int i = 0; i<4; i++)
aoffsets[i] = aoffsets[i]+lda;
vecOffset +=64;
}
i = (cols >> 3);
if (i > 0) {
aoffsets[0] = aoffset;
for (int it = 1; it < 8; ++it) {
aoffsets[it] = aoffsets[it-1] + lda;
}
aoffset += 8 * lda;
do {
for (int it = 0; it < 8; ++it)
c_arr[it] = vec_xl(0, (vector unsigned char*)aoffsets[it]);
vector_permute_store(c_arr, 8, vecOffset);
for (int it = 0; it < 8; ++it)
aoffsets[it] = aoffsets[it] + 8*lda;
vecOffset += 128;
i--;
} while(i > 0);
}
j--;
} while(j > 0);
}
if (rows & 4) {
aoffsets[0] = aoffset;
for (int it = 1; it < 4; ++it)
aoffsets[it] = aoffsets[it-1] + lda;
aoffset += 4 * lda;
if (cols == 4) {
for (int it = 0; it < 4; ++it)
c_arr[it] = vec_xl(0, (vector unsigned char*)aoffsets[it]);
vector_permute_store(c_arr, 2, vecOffset);
for (int it = 0; it< 4; it++)
aoffsets[it] = aoffsets[it] + lda;
vecOffset += 32;
}
i = (cols >> 3);
if (i > 0) {
do {
for (int it = 0; it < 4; ++it)
c_arr[it] = vec_xl(0, (vector unsigned char*)aoffsets[it]);
vector_permute_store(c_arr, 4, vecOffset);
for (int it = 0; it< 4; it++)
aoffsets[it] = aoffsets[it] + 8*lda;
vecOffset += 64;
i--;
} while(i > 0);
}
}
if (rows & 3) {
aoffsets[0] = aoffset;
for (int it = 1; it < 4; ++it)
aoffsets[it] = aoffsets[it-1] + lda;
if (cols == 4) {
switch(rows) {
case 3: c_arr[2] = vec_xl(0, (vector unsigned char*)aoffsets[2]);
case 2: c_arr[1] = vec_xl(0, (vector unsigned char*)aoffsets[1]);
case 1: c_arr[0] = vec_xl(0, (vector unsigned char*)aoffsets[0]);
break;
}
vector_permute_store(c_arr, 2, vecOffset);
for (int it = 0; it< 4; it++)
aoffsets[it] = aoffsets[it] + lda;
vecOffset += 32;
}
i = (cols >> 3);
if (i > 0) {
do {
switch(rows) {
case 3: c_arr[2] = vec_xl(0, (vector unsigned char*)aoffsets[2]);
case 2: c_arr[1] = vec_xl(0, (vector unsigned char*)aoffsets[1]);
case 1: c_arr[0] = vec_xl(0, (vector unsigned char*)aoffsets[0]);
break;
}
vector_permute_store(c_arr, 4, vecOffset);
for (int it = 0; it <4; it++)
aoffsets[it] = aoffsets[it] + 8* lda;
vecOffset += 64;
i--;
} while(i > 0);
}
}
}
void mnpack(int64_t m0, int64_t m, int64_t n0, int64_t n) {
int64_t mc, nc, mp, np;
int m_rem = MIN(m - m0, 8);
int n_rem = MIN(n - n0, 8);
if (m_rem >= 8 && n_rem >= 8) {
mc = 8;
nc = 8;
gemm<8,8>(m0, m, n0, n);
} else if (m_rem >= 4 && n_rem >= 8) {
mc = 4;
nc = 8;
gemm<4,8>(m0, m, n0, n);
} else if (m_rem >=8 && n_rem >=4){
mc = 8;
nc = 4;
gemm<8,4>(m0, m, n0, n);
} else if ((m_rem < 4) && (n_rem >= 8)) {
nc = 8;
switch(m_rem) {
case 1:
mc = 1;
gemm_Mx8<1>(m0, m, n0, n);
break;
case 2:
mc = 2;
gemm_Mx8<2>(m0, m, n0, n);
break;
case 3:
mc = 3;
gemm_Mx8<3>(m0, m, n0, n);
break;
default:
return;
}
} else if (m_rem >= 4 && n_rem >= 4) {
mc = 4;
nc = 4;
gemm_small<4, 4>(m0, m, n0, n);
} else if ((m_rem > 4) && (n_rem < 4)) {
mc = 4;
switch(n_rem) {
case 1:
nc = 1;
gemm_small<4, 1>(m0, m, n0, n);
break;
case 2:
nc = 2;
gemm_small<4, 2>(m0, m, n0, n);
break;
case 3:
nc = 3;
gemm_small<4, 3>(m0, m, n0, n);
break;
default:
return;
}
} else {
switch((m_rem << 4) | n_rem) {
case 0x43:
mc = 4;
nc = 3;
gemm_small<4, 3>(m0, m, n0, n);
break;
case 0x42:
mc = 4;
nc = 2;
gemm_small<4, 2>(m0, m, n0, n);
break;
case 0x41:
mc = 4;
nc = 1;
gemm_small<4, 1>(m0, m, n0, n);
break;
case 0x34:
mc = 3;
nc = 4;
gemm_small<3, 4>(m0, m, n0, n);
break;
case 0x33:
mc = 3;
nc = 3;
gemm_small<3, 3>(m0, m, n0, n);
break;
case 0x32:
mc = 3;
nc = 2;
gemm_small<3, 2>(m0, m, n0, n);
break;
case 0x31:
mc = 3;
nc = 1;
gemm_small<3, 1>(m0, m, n0, n);
break;
case 0x24:
mc = 2;
nc = 4;
gemm_small<2,4>(m0, m, n0, n);
break;
case 0x23:
mc = 2;
nc = 3;
gemm_small<2, 3>(m0, m, n0, n);
break;
case 0x22:
mc = 2;
nc = 2;
gemm_small<2, 2>(m0, m, n0, n);
break;
case 0x21:
mc = 2;
nc = 1;
gemm_small<2, 1>(m0, m, n0, n);
break;
case 0x14:
mc = 1;
nc = 4;
gemm_small<1, 4>(m0, m, n0, n);
break;
case 0x13:
mc = 1;
nc = 3;
gemm_small<1, 3>(m0, m, n0, n);
break;
case 0x12:
mc = 1;
nc = 2;
gemm_small<1, 2>(m0, m, n0, n);
break;
case 0x11:
mc = 1;
nc = 1;
gemm_small<1, 1>(m0, m, n0, n);
break;
default:
return;
}
}
mp = m0 + (m - m0) / mc * mc;
np = n0 + (n - n0) / nc * nc;
mnpack(mp, m, n0, np);
mnpack(m0, m, np, n);
}
void KERNEL_4x8(int64_t ii, int64_t jj) {
vec_t vec_A[4], vec_B[8] , vec_C[4];
acc_t acc_0, acc_1;
__builtin_mma_xxsetaccz(&acc_0);
__builtin_mma_xxsetaccz(&acc_1);
for (int l = 0; l < k; l+=8) {
packNormal((A+(ii*lda)+l), lda, 4, 8, (uint8_t*)vec_A);
packNormal((B+(jj*ldb)+l), ldb, 8, 8, (uint8_t*)vec_B);
for (int x = 0; x < 4; x++) {
__builtin_mma_xvbf16ger2pp(&acc_0, vec_A[x], vec_B[x]);
__builtin_mma_xvbf16ger2pp(&acc_1, vec_A[x], vec_B[x+4]);
}
}
SAVE_ACC(&acc_0, ii, jj);
SAVE_ACC(&acc_1, ii, jj+4);
}
void KERNEL_8x4(int64_t ii, int64_t jj) {
vec_t vec_A[8], vec_B[4] , vec_C[4];
acc_t acc_0, acc_1;
__builtin_mma_xxsetaccz(&acc_0);
__builtin_mma_xxsetaccz(&acc_1);
for (int l = 0; l < k; l+=8) {
packNormal((A+(ii*lda)+l), lda, 8, 8, (uint8_t*)vec_A);
packNormal((B+(jj*ldb)+l), ldb, 8, 4, (uint8_t*)vec_B);
for (int x = 0; x < 4; x++) {
__builtin_mma_xvbf16ger2pp(&acc_0, vec_A[x], vec_B[x]);
__builtin_mma_xvbf16ger2pp(&acc_1, vec_A[x+4], vec_B[x]);
}
}
SAVE_ACC(&acc_0, ii, jj);
SAVE_ACC(&acc_1, ii+4, jj);
}
void KERNEL_8x8(int64_t ii, int64_t jj) {
vec_t vec_A[8], vec_B[8], vec_C[4];
acc_t acc_0, acc_1, acc_2, acc_3;
__builtin_mma_xxsetaccz(&acc_0);
__builtin_mma_xxsetaccz(&acc_1);
__builtin_mma_xxsetaccz(&acc_2);
__builtin_mma_xxsetaccz(&acc_3);
for (int l = 0; l < k; l+=8) {
packNormal(A+(ii*lda)+l, lda, 8, 8, (uint8_t*)vec_A);
packNormal(B+(jj*ldb)+l, ldb, 8, 8, (uint8_t*)vec_B);
for (int x = 0; x < 4; x++) {
__builtin_mma_xvbf16ger2pp(&acc_0, vec_A[x], vec_B[x]);
__builtin_mma_xvbf16ger2pp(&acc_1, (vec_t)vec_A[x], (vec_t)vec_B[x+4]);
__builtin_mma_xvbf16ger2pp(&acc_2, (vec_t)vec_A[x+4], (vec_t)vec_B[x]);
__builtin_mma_xvbf16ger2pp(&acc_3, (vec_t)vec_A[x+4], (vec_t)vec_B[x+4]);
}
}
SAVE_ACC(&acc_0, ii, jj);
SAVE_ACC(&acc_1, ii, jj+4);
SAVE_ACC(&acc_2, ii+4, jj);
SAVE_ACC(&acc_3, ii+4, jj+4);
}
template<int RM, int RN>
void gemm_small(int64_t m0, int64_t m, int64_t n0, int64_t n) {
int64_t ytiles = (m - m0) / RM;
int64_t xtiles = (n - n0) / RN;
int64_t tiles = xtiles * ytiles;
int64_t duty = (tiles + nth - 1) / nth;
int64_t start = duty * ith;
int64_t end = start + duty;
if (end > tiles)
end = tiles;
for (int64_t job = start; job < end; ++job) {
int64_t ii = m0 + job / xtiles * RM;
int64_t jj = n0 + job % xtiles * RN;
vec_t vec_C[4];
acc_t acc_0;
__builtin_mma_xxsetaccz(&acc_0);
vec_t vec_A[2], vec_B[2];
for (int l=0; l<k; l+=4) {
packNormal(A+(ii*lda)+l, lda, RM, 4, (uint8_t*)vec_A);
packNormal(B+(jj*ldb)+l, ldb, RN, 4, (uint8_t*)vec_B);
for (int x = 0; x<2; x++) {
__builtin_mma_xvbf16ger2pp(&acc_0, vec_A[x], vec_B[x]);
}
}
__builtin_mma_disassemble_acc(vec_C, &acc_0);
for (int I = 0; I < RM; I++) {
for (int J = 0; J < RN; J++) {
*((TC*)(C+ii+((jj+J)*ldc)+I)) = *((TC*)&vec_C[I]+J);
}
}
}
}
template<int RM>
void gemm_Mx8(int64_t m0, int64_t m, int64_t n0, int64_t n) {
int RN = 8;
int64_t ytiles = (m - m0) / RM;
int64_t xtiles = (n - n0) / RN;
int64_t tiles = xtiles * ytiles;
int64_t duty = (tiles + nth - 1) / nth;
int64_t start = duty * ith;
int64_t end = start + duty;
if (end > tiles)
end = tiles;
for (int64_t job = start; job < end; ++job) {
int64_t ii = m0 + job / xtiles * RM;
int64_t jj = n0 + job % xtiles * RN;
vec_t vec_C[4];
acc_t acc_0, acc_1;
__builtin_mma_xxsetaccz(&acc_0);
__builtin_mma_xxsetaccz(&acc_1);
vec_t vec_A[4], vec_B[8];
for (int l=0; l<k; l+=8) {
packNormal(A+(ii*lda)+l, lda, RM, 8, (uint8_t*)vec_A);
packNormal(B+(jj*ldb)+l, ldb, RN, 8, (uint8_t*)vec_B);
for (int x = 0; x<4; x++) {
__builtin_mma_xvbf16ger2pp(&acc_0, vec_A[x], vec_B[x]);
__builtin_mma_xvbf16ger2pp(&acc_1, vec_A[x], vec_B[x+4]);
}
}
__builtin_mma_disassemble_acc(vec_C, &acc_0);
for (int I = 0; I < RM; I++) {
for (int J = 0; J < 4; J++) {
*((TC*)(C+ii+((jj+J)*ldc)+I)) = *((TC*)&vec_C[I]+J);
}
}
__builtin_mma_disassemble_acc(vec_C, &acc_1);
for (int I = 0; I < RM; I++) {
for (int J = 0; J < 4; J++) {
*((TC*)(C+ii+((jj+4+J)*ldc)+I)) = *((TC*)&vec_C[I]+J);
}
}
}
}
template<int RM, int RN>
inline void kernel(int64_t ii, int64_t jj) {
if constexpr(RM == 4 && RN == 8) {
KERNEL_4x8(ii,jj);
} else if constexpr(RM == 8 && RN == 8) {
KERNEL_8x8(ii,jj);
} else if constexpr(RM == 8 && RN == 4) {
KERNEL_8x4(ii,jj);
} else {
assert(false && "RN/RM values not supported");
}
}
template <int RM, int RN>
NOINLINE void gemm(int64_t m0, int64_t m, int64_t n0, int64_t n) {
int64_t ytiles = (m - m0) / RM;
int64_t xtiles = (n - n0) / RN;
int64_t tiles = xtiles * ytiles;
int64_t duty = (tiles + nth - 1) / nth;
int64_t start = duty * ith;
int64_t end = start + duty;
if (end > tiles)
end = tiles;
for (int64_t job = start; job < end; ++job) {
int64_t ii = m0 + job / xtiles * RM;
int64_t jj = n0 + job % xtiles * RN;
kernel<RM, RN>(ii, jj);
}
}
const TA *const A;
const TB *const B;
TC *C;
const int64_t k;
const int64_t lda;
const int64_t ldb;
const int64_t ldc;
const int ith;
const int nth;
};
template <typename TA>
class tinyBLAS_Q0_PPC {
public:
tinyBLAS_Q0_PPC(int64_t k,
const TA *A, int64_t lda,
const block_q8_0 *B, int64_t ldb,
float *C, int64_t ldc,
int ith, int nth)
: A(A), B(B), C(C), k(k), lda(lda), ldb(ldb), ldc(ldc), ith(ith), nth(nth) {
}
void matmul(int64_t m, int64_t n) {
mnpack(0, m, 0, n);
}
private:
inline void save_res(int ii, int jj, int idx, vector float* fin_res, int RM=4, int RN=4) {
for (int I = 0; I < RM; I++) {
for (int J = 0; J < RN; J++) {
*((float*)(C+ii+((jj+J)*ldc)+I)) = *((float*)&fin_res[idx+I]+J);
}
}
}
template<int size>
inline void compute(acc_t* ACC, int c_idx, int s_idx, std::array<int, size>& comparray, vector float* vs, vector float* fin_res) {
vector signed int vec_C[4];
vector float CA[4] = {0};
vector float res[4] = {0};
__builtin_mma_disassemble_acc(vec_C, ACC);
for (int i = 0; i < 4; i++) {
CA[i] = vec_splats((float)(((double)comparray[c_idx+i]) * -128.0));
res[i] = vec_add(vec_ctf(vec_C[i], 0), CA[i]);
fin_res[s_idx+i] = vec_madd(res[i], vs[s_idx+i], fin_res[s_idx+i]);
}
}
/* This function processes quantized data from block_q4_0 elements.
* First the we try to extract the two int4 values stored in single int8_t into two signed int8.
* And then we subtract each of the resultant element with 8, to convert signed int8 to unsigned int8.
* Also compute the rowsum which is required to compensate the above conversion. */
inline void process_q4_elements(vector signed char (&c)[2], int* ca) {
const vector signed char lowMask = vec_splats((signed char)0xF);
const vector unsigned char v4 = vec_splats((unsigned char)0x4);
const vector signed char v8 = vec_splats((signed char)0x8);
vector signed int vsum = {0};
vector signed int vsum2 = {0};
c[0] = vec_and(c[1], lowMask);
c[1] = vec_sr(c[1], v4);
c[0] = vec_sub(c[0], v8);
c[1] = vec_sub(c[1], v8);
vsum = vec_sum4s(c[0], vsum);
vsum2 = vec_sum4s(c[1], vsum2);
vsum = vec_add(vsum, vsum2);
*(ca) = vsum[0] + vsum[1] + vsum[2] + vsum[3];
}
template <typename V1, typename V2>
inline void vector_permute_store(V2 &s1, V2 &s2, V2 &s3, V2 &s4, V1 *vecOffset, bool flip) {
vector unsigned char swiz1 = {0, 1, 2, 3, 4, 5, 6, 7, 16, 17, 18, 19, 20, 21, 22, 23};
vector unsigned char swiz2 = {8, 9, 10, 11, 12, 13, 14, 15, 24, 25, 26, 27, 28, 29, 30, 31};
vector unsigned char swiz3 = {0, 1, 2, 3, 8, 9, 10, 11, 16, 17, 18, 19, 24, 25, 26, 27};
vector unsigned char swiz4 = {4, 5, 6, 7, 12, 13, 14, 15, 20, 21, 22, 23, 28, 29, 30, 31};
V2 t1, t2, t3, t4, t5, t6, t7, t8;
vector unsigned char xor_vector;
uint8_t flip_vec = 0x80;
xor_vector = vec_splats(flip_vec);
t1 = vec_perm(s1, s2, swiz1);
t2 = vec_perm(s1, s2, swiz2);
t3 = vec_perm(s3, s4, swiz1);
t4 = vec_perm(s3, s4, swiz2);
t5 = vec_perm(t1, t3, swiz3);
t6 = vec_perm(t1, t3, swiz4);
t7 = vec_perm(t2, t4, swiz3);
t8 = vec_perm(t2, t4, swiz4);
if (flip == true) {
t5 = vec_xor(t5, xor_vector);
t6 = vec_xor(t6, xor_vector);
t7 = vec_xor(t7, xor_vector);
t8 = vec_xor(t8, xor_vector);
}
vec_xst(t5, 0, vecOffset);
vec_xst(t6, 0, vecOffset+16);
vec_xst(t7, 0, vecOffset+32);
vec_xst(t8, 0, vecOffset+48);
}
template<int size>
void packNormalInt4(const TA* a, int64_t lda, int rows, int cols, int8_t* vec, std::array<int, size>& comparray) {
int64_t i, j;
TA *aoffset = NULL;
int8_t *vecOffset = NULL;
TA *aoffset1 = NULL, *aoffset2 = NULL, *aoffset3 = NULL, *aoffset4 = NULL;
TA *aoffset5 = NULL, *aoffset6 = NULL, *aoffset7 = NULL, *aoffset8 = NULL;
vector signed char c1[2] = {0}, c2[2] = {0}, c3[2] = {0}, c4[2] = {0};
vector signed char c5[2] = {0}, c6[2] = {0}, c7[2] = {0}, c8[2] = {0};
aoffset = const_cast<TA*>(a);
vecOffset = vec;
j = (rows >> 3);
if (j > 0) {
do {
aoffset1 = aoffset;
aoffset2 = aoffset1 + lda;
aoffset3 = aoffset2 + lda;
aoffset4 = aoffset3 + lda;
aoffset5 = aoffset4 + lda;
aoffset6 = aoffset5 + lda;
aoffset7 = aoffset6 + lda;
aoffset8 = aoffset7 + lda;
aoffset += 8 * lda;
i = (cols >> 2);
if (i > 0) {
do {
c1[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset1->qs));
c2[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset2->qs));
c3[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset3->qs));
c4[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset4->qs));
c5[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset5->qs));
c6[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset6->qs));
c7[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset7->qs));
c8[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset8->qs));
process_q4_elements(c1, &comparray[0]);
process_q4_elements(c2, &comparray[1]);
process_q4_elements(c3, &comparray[2]);
process_q4_elements(c4, &comparray[3]);
process_q4_elements(c5, &comparray[4]);
process_q4_elements(c6, &comparray[5]);
process_q4_elements(c7, &comparray[6]);
process_q4_elements(c8, &comparray[7]);
vector_permute_store<int8_t, vector signed char>(c1[0], c2[0], c3[0], c4[0], vecOffset, false);
vector_permute_store<int8_t, vector signed char>(c1[1], c2[1], c3[1], c4[1], vecOffset+64, false);
vector_permute_store<int8_t, vector signed char>(c5[0], c6[0], c7[0], c8[0], vecOffset+128, false);
vector_permute_store<int8_t, vector signed char>(c5[1], c6[1], c7[1], c8[1], vecOffset+192, false);
aoffset1 += lda;
aoffset2 += lda;
aoffset3 += lda;
aoffset4 += lda;
aoffset5 += lda;
aoffset6 += lda;
aoffset7 += lda;
aoffset8 += lda;
vecOffset += 256;
i--;
} while (i > 0);
}
j--;
} while (j > 0);
}
if (rows & 4) {
aoffset1 = aoffset;
aoffset2 = aoffset1 + lda;
aoffset3 = aoffset2 + lda;
aoffset4 = aoffset3 + lda;
aoffset += 4 * lda;
i = (cols >> 2);
if (i > 0) {
do {
c1[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset1->qs));
c2[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset2->qs));
c3[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset3->qs));
c4[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset4->qs));
process_q4_elements(c1, &comparray[0]);
process_q4_elements(c2, &comparray[1]);
process_q4_elements(c3, &comparray[2]);
process_q4_elements(c4, &comparray[3]);
vector_permute_store<int8_t, vector signed char>(c1[0], c2[0], c3[0], c4[0], vecOffset, false);
vector_permute_store<int8_t, vector signed char>(c1[1], c2[1], c3[1], c4[1], vecOffset+64, false);
aoffset1 += lda;
aoffset2 += lda;
aoffset3 += lda;
aoffset4 += lda;
vecOffset += 128;
i--;
} while (i > 0);
}
}
if (rows & 3) {
aoffset1 = aoffset;
aoffset2 = aoffset1 + lda;
aoffset3 = aoffset2 + lda;
i = (cols >> 2);
if (i > 0) {
do {
switch(rows) {
case 3: c3[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset3->qs));
case 2: c2[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset2->qs));
case 1: c1[1] = reinterpret_cast<vector signed char>(vec_xl(0, aoffset1->qs));
break;
}
process_q4_elements(c1, &comparray[0]);
process_q4_elements(c2, &comparray[1]);
process_q4_elements(c3, &comparray[2]);
process_q4_elements(c4, &comparray[3]);
vector_permute_store<int8_t, vector signed char>(c1[0], c2[0], c3[0], c4[0], vecOffset, false);
vector_permute_store<int8_t, vector signed char>(c1[1], c2[1], c3[1], c4[1], vecOffset+64, false);
aoffset1 += lda;
aoffset2 += lda;
aoffset3 += lda;
vecOffset += 128;
i--;
} while(i > 0);
}
}
}
template<typename VA, typename VB>
void packNormal(const block_q8_0* a, int64_t lda, int rows, int cols, VA* vec, bool flip) {
int64_t i, j;
block_q8_0 *aoffset = NULL;
VA *vecOffset = NULL;
block_q8_0* aoffsets[8];
__vector_pair arr[8];
VB c[8][2] = {0};
VB c1[8] = {0}; VB c2[8] = {0};
aoffset = const_cast<block_q8_0*>(a);
vecOffset = vec;
j = (rows >> 3);
if (j > 0) {
do {
aoffsets[0] = aoffset;
for (int it = 1; it < 8; it++)
aoffsets[it] = aoffsets[it-1] + lda;
aoffset += 8 * lda;
i = (cols >> 3);
if (i > 0) {
do {
for (int it = 0; it < 8; it++) {
arr[it] = __builtin_vsx_lxvp(0, (__vector_pair*)aoffsets[it]->qs);
__builtin_vsx_disassemble_pair(c[it], &arr[it]);
c1[it] = c[it][0];
c2[it] = c[it][1];
}
vector_permute_store<VA, VB>(c1[0], c1[1], c1[2], c1[3], vecOffset, flip);
vector_permute_store<VA, VB>(c2[0], c2[1], c2[2], c2[3], vecOffset+64, flip);
vector_permute_store<VA, VB>(c1[4], c1[5], c1[6], c1[7], vecOffset+128, flip);
vector_permute_store<VA, VB>(c2[4], c2[5], c2[6], c2[7], vecOffset+192, flip);
for (int it = 0; it < 8; it++)
aoffsets[it] += lda;
vecOffset += 256;
i--;
} while(i > 0);
}
j--;
} while(j > 0);
}
if (rows & 4) {
aoffsets[0] = aoffset;
for (int it = 1; it < 4; it++ )
aoffsets[it] = aoffsets[it-1] + lda;
aoffset += 4 * lda;
i = (cols >> 3);
if (i > 0) {
do {
for (int it = 0; it < 4; it++) {
arr[it] = __builtin_vsx_lxvp(0, (__vector_pair*)aoffsets[it]->qs);
__builtin_vsx_disassemble_pair(c[it], &arr[it]);
c1[it] = c[it][0];
c2[it] = c[it][1];
}
vector_permute_store<VA, VB>(c1[0], c1[1], c1[2], c1[3], vecOffset, flip);
vector_permute_store<VA, VB>(c2[0], c2[1], c2[2], c2[3], vecOffset+64, flip);
for (int it = 0; it < 4; it++) {
aoffsets[it] += lda;
}
vecOffset += 128;
i--;
} while(i > 0);
}
}
if (rows & 3) {
aoffsets[0] = aoffset;
for (int it = 1; it < 3; it++ )
aoffsets[it] = aoffsets[it-1] + lda;
i = (cols >> 3);
if (i > 0) {
do {
switch(rows) {
case 3: arr[2] = __builtin_vsx_lxvp(0, (__vector_pair*)aoffsets[2]->qs);
__builtin_vsx_disassemble_pair(c[2], &arr[2]);
c1[2] = c[2][0]; c2[2] = c[2][1];
case 2: arr[1] = __builtin_vsx_lxvp(0, (__vector_pair*)aoffsets[1]->qs);
__builtin_vsx_disassemble_pair(c[1], &arr[1]);
c1[1] = c[1][0]; c2[1] = c[1][1];
case 1: arr[0] = __builtin_vsx_lxvp(0, (__vector_pair*)aoffsets[0]->qs);
__builtin_vsx_disassemble_pair(c[0], &arr[0]);
c1[0] = c[0][0]; c2[0] = c[0][1];
break;
}
vector_permute_store<VA, VB>(c1[0], c1[1], c1[2], c1[3], vecOffset, flip);
vector_permute_store<VA, VB>(c2[0], c2[1], c2[2], c2[3], vecOffset+64, flip);
for (int it = 0; it < 3; it++)
aoffsets[it] += lda;
vecOffset += 128;
i--;
} while(i > 0);
}
}
}
void mnpack(int64_t m0, int64_t m, int64_t n0, int64_t n) {
int m_rem = MIN(m - m0, 16);
int n_rem = MIN(n - n0, 16);
int mc = 0, nc = 0;
if (m_rem >= 8 && n_rem >= 8) {
mc = 8;
nc = 8;
gemm<8, 8>(m0, m, n0, n);
} else if (m_rem >= 4 && n_rem >= 8) {
mc = 4;
nc = 8;
gemm<4, 8>(m0, m, n0, n);
} else if (m_rem >= 8 && n_rem >= 4) {
mc = 8;
nc = 4;
gemm<8, 4>(m0, m, n0, n);
} else if (m_rem >= 4 && n_rem >= 4) {
mc = 4;
nc = 4;
gemm_small(m0, m, n0, n, mc, nc);
} else {
mc = (m_rem >= 4) ? 4 : m_rem;
nc = (n_rem >= 4) ? 4 : n_rem;
if (mc == 0 || nc == 0)
return;
gemm_small(m0, m, n0, n, mc, nc);
}
int64_t mp = m0 + ((m - m0) / mc) * mc;
int64_t np = n0 + ((n - n0) / nc) * nc;
mnpack(mp, m, n0, np);
mnpack(m0, m, np, n);
}
void KERNEL_4x8(int64_t ii, int64_t jj) {
vec_t vec_A[8], vec_B[16] = {0};
acc_t acc_0, acc_1;
std::array<int, 4> comparray {};
vector float fin_res[8] = {0};
vector float vs[8] = {0};
bool isAblock_q4 = std::is_same_v<TA, block_q4_0>;
for (int l = 0; l < k; l++) {
__builtin_mma_xxsetaccz(&acc_0);
__builtin_mma_xxsetaccz(&acc_1);
if (std::is_same_v<TA, block_q4_0>) {
packNormalInt4<4>((A+(ii*lda)+l), lda, 4, 4, (int8_t*)vec_A, comparray);
} else {
packNormal<int8_t, vector signed char>((const block_q8_0*)(A+(ii*lda)+l), lda, 4, 8, (int8_t*)vec_A, false);
}
packNormal<uint8_t, vector unsigned char>((B+(jj*ldb)+l), ldb, 8, 8, (uint8_t*)vec_B, true);
for(int x = 0; x < 8; x++) {
__builtin_mma_xvi8ger4pp(&acc_0, vec_A[x], vec_B[x]);
__builtin_mma_xvi8ger4pp(&acc_1, vec_A[x], vec_B[x+8]);
}
for (int I = 0; I<4; I++) {
for (int J = 0; J<4; J++) {
*((float*)&vs[I]+J) = (unhalf((A+((ii+I)*lda)+l)->d) * unhalf((B+((jj+J)*ldb)+l)->d));
*((float*)&vs[I+4]+J) = (unhalf((A+((ii+I)*lda)+l)->d) * unhalf((B+((jj+J+4)*ldb)+l)->d));
}
}
if (!isAblock_q4) {
auto aoffset = A+(ii*lda)+l;
for (int i = 0; i < 4; i++) {
comparray[i] = 0;
int ca = 0;
auto *at = aoffset->qs;
for (int j = 0; j < 32; j++)
ca += (int)*at++;
comparray[i] = ca;
aoffset += lda;
}
}
compute<4>(&acc_0, 0, 0, comparray, vs, fin_res);
compute<4>(&acc_1, 0, 4, comparray, vs, fin_res);
}
save_res(ii, jj, 0, fin_res);
save_res(ii, jj+4, 4, fin_res);
}
void KERNEL_8x4(int64_t ii, int64_t jj) {
vec_t vec_A[16], vec_B[8] = {0};
acc_t acc_0, acc_1;
std::array<int, 8> comparray {};
vector float fin_res[8] = {0};
vector float vs[8] = {0};
bool isAblock_q4 = std::is_same_v<TA, block_q4_0>;
for (int l = 0; l < k; l++) {
__builtin_mma_xxsetaccz(&acc_0);
__builtin_mma_xxsetaccz(&acc_1);
if (std::is_same_v<TA, block_q4_0>) {
packNormalInt4<8>((A+(ii*lda)+l), lda, 8, 4, (int8_t*)vec_A, comparray);
} else {
packNormal<int8_t, vector signed char>((const block_q8_0*)(A+(ii*lda)+l), lda, 8, 8, (int8_t*)vec_A, false);
}
packNormal<uint8_t, vector unsigned char>((B+(jj*ldb)+l), ldb, 4, 8, (uint8_t*)vec_B, true);
for(int x = 0; x < 8; x++) {
__builtin_mma_xvi8ger4pp(&acc_0, vec_A[x], vec_B[x]);
__builtin_mma_xvi8ger4pp(&acc_1, vec_A[x+8], vec_B[x]);
}
for (int I = 0; I<8; I++) {
for (int J = 0; J<4; J++) {
*((float*)&vs[I]+J) = (unhalf((A+((ii+I)*lda)+l)->d) * unhalf((B+((jj+J)*ldb)+l)->d));
}
}
if (!isAblock_q4) {
auto aoffset = A+(ii*lda)+l;
for (int i = 0; i < 8; i++) {
comparray[i] = 0;
int ca = 0;
auto *at = aoffset->qs;
for (int j = 0; j < 32; j++)
ca += (int)*at++;
comparray[i] = ca;
aoffset += lda;
}
}
compute<8>(&acc_0, 0, 0, comparray, vs, fin_res);
compute<8>(&acc_1, 4, 4, comparray, vs, fin_res);
}
save_res(ii, jj, 0, fin_res);
save_res(ii+4, jj, 4, fin_res);
}
void KERNEL_8x8(int64_t ii, int64_t jj) {
vec_t vec_A[16], vec_B[16] = {0};
acc_t acc_0, acc_1, acc_2, acc_3;
std::array<int, 8> comparray {};
vector float fin_res[16] = {0};
vector float vs[16] = {0};
bool isAblock_q4 = std::is_same_v<TA, block_q4_0>;
for (int l = 0; l < k; l++) {
__builtin_mma_xxsetaccz(&acc_0);
__builtin_mma_xxsetaccz(&acc_1);
__builtin_mma_xxsetaccz(&acc_2);
__builtin_mma_xxsetaccz(&acc_3);
if (std::is_same_v<TA, block_q4_0>) {
packNormalInt4<8>((A+(ii*lda)+l), lda, 8, 4, (int8_t*)vec_A, comparray);
} else {
packNormal<int8_t, vector signed char>((const block_q8_0*)(A+(ii*lda)+l), lda, 8, 8, (int8_t*)vec_A, false);
}
packNormal<uint8_t, vector unsigned char>((B+(jj*ldb)+l), ldb, 8, 8, (uint8_t*)vec_B, true);
for(int x = 0; x < 8; x++) {
__builtin_mma_xvi8ger4pp(&acc_0, vec_A[x], vec_B[x]);
__builtin_mma_xvi8ger4pp(&acc_1, vec_A[x+8], vec_B[x]);
__builtin_mma_xvi8ger4pp(&acc_2, vec_A[x], vec_B[x+8]);
__builtin_mma_xvi8ger4pp(&acc_3, vec_A[x+8], vec_B[x+8]);
}
for (int I = 0; I<8; I++) {
for (int J = 0; J<4; J++) {
*((float*)&vs[I]+J) = (unhalf((A+((ii+I)*lda)+l)->d) * unhalf((B+((jj+J)*ldb)+l)->d));
*((float*)&vs[I+8]+J) = (unhalf((A+((ii+I)*lda)+l)->d) * unhalf((B+((jj+J+4)*ldb)+l)->d));
}
}
if (!isAblock_q4) {
auto aoffset = A+(ii*lda)+l;
for (int i = 0; i < 8; i++) {
comparray[i] = 0;
int ca = 0;
auto *at = aoffset->qs;
for (int j = 0; j < 32; j++)
ca += (int)*at++;
comparray[i] = ca;
aoffset += lda;
}
}
compute<8>(&acc_0, 0, 0, comparray, vs, fin_res);
compute<8>(&acc_1, 4, 4, comparray, vs, fin_res);
compute<8>(&acc_2, 0, 8, comparray, vs, fin_res);
compute<8>(&acc_3, 4, 12, comparray, vs, fin_res);
}
save_res(ii, jj, 0, fin_res);
save_res(ii+4, jj, 4, fin_res);
save_res(ii, jj+4, 8, fin_res);
save_res(ii+4, jj+4, 12, fin_res);
}
void gemm_small(int64_t m0, int64_t m, int64_t n0, int64_t n, int RM, int RN) {
int64_t ytiles = (m - m0) / RM;
int64_t xtiles = (n - n0) / RN;
int64_t tiles = xtiles * ytiles;
int64_t duty = (tiles + nth - 1) / nth;
int64_t start = duty * ith;
int64_t end = start + duty;
vec_t vec_A[8] = {0}, vec_B[8] = {0};
vector signed int vec_C[4];
acc_t acc_0;
bool isAblock_q4 = std::is_same_v<TA, block_q4_0>;
if (end > tiles)
end = tiles;
for (int64_t job = start; job < end; ++job) {
int64_t ii = m0 + job / xtiles * RM;
int64_t jj = n0 + job % xtiles * RN;
std::array<int, 4> comparray{};
vector float res[4] = {0};
vector float fin_res[4] = {0};
vector float vs[4] = {0};
vector float CA[4] = {0};
__builtin_prefetch((A+(ii*lda)+0)->qs, 0, 1); // prefetch first value
__builtin_prefetch((B+(jj*ldb)+0)->qs, 0, 1); // prefetch first value
for (int l = 0; l < k; l++) {
__builtin_prefetch((A+(ii*lda)+(l+1))->qs, 0, 1); // prefetch one loop ahead
__builtin_prefetch((B+(jj*ldb)+(l+1))->qs, 0, 1); // prefetch one loop ahead
__builtin_mma_xxsetaccz(&acc_0);
if (isAblock_q4) {
packNormalInt4<4>((A+(ii*lda)+l), lda, RM, 4, (int8_t*)vec_A, comparray);
} else {
packNormal<int8_t, vector signed char>((const block_q8_0*)(A+(ii*lda)+l), lda, RM, 8, (int8_t*)vec_A, false);
}
packNormal<uint8_t, vector unsigned char>((B+(jj*ldb)+l), ldb, RN, 8, (uint8_t*)vec_B, true);
for(int x = 0; x < 8; x+=4) {
__builtin_mma_xvi8ger4pp(&acc_0, vec_A[x], vec_B[x]);
__builtin_mma_xvi8ger4pp(&acc_0, vec_A[x+1], vec_B[x+1]);
__builtin_mma_xvi8ger4pp(&acc_0, vec_A[x+2], vec_B[x+2]);
__builtin_mma_xvi8ger4pp(&acc_0, vec_A[x+3], vec_B[x+3]);
}
for (int I = 0; I<RM; I++) {
for (int J = 0; J<RN; J++) {
*((float*)&vs[I]+J) = (unhalf((A+((ii+I)*lda)+l)->d) * unhalf((B+((jj+J)*ldb)+l)->d));
}
}
__builtin_mma_disassemble_acc(vec_C, &acc_0);
if (!isAblock_q4) {
auto aoffset = A+(ii*lda)+l;
for (int i = 0; i < RM; i++) {
comparray[i] = 0;
int ca = 0;
auto *at = aoffset->qs;
for (int j = 0; j < 32; j++)
ca += (int)*at++;
comparray[i] = ca;
aoffset += lda;
}
}
for (int i = 0; i < RM; i++) {
CA[i] = vec_splats((float)(((double)comparray[i]) * -128.0));
res[i] = vec_add(vec_ctf(vec_C[i], 0), CA[i]);
fin_res[i] = vec_madd(res[i], vs[i], fin_res[i]);
}
}
save_res(ii, jj, 0, fin_res, RM, RN);
}
}
template<int RM, int RN>
inline void kernel(int64_t ii, int64_t jj) {
if constexpr(RM == 4 && RN == 8) {
KERNEL_4x8(ii,jj);
} else if constexpr(RM == 8 && RN == 4) {
KERNEL_8x4(ii,jj);
} else if constexpr(RM == 8 && RN == 8) {
KERNEL_8x8(ii,jj);
} else {
assert(false && "RN/RM values not supported");
}
}
template <int RM, int RN>
NOINLINE void gemm(int64_t m0, int64_t m, int64_t n0, int64_t n) {
int64_t ytiles = (m - m0) / RM;
int64_t xtiles = (n - n0) / RN;
int64_t tiles = xtiles * ytiles;
int64_t duty = (tiles + nth - 1) / nth;
int64_t start = duty * ith;
int64_t end = start + duty;
if (end > tiles)
end = tiles;
for (int64_t job = start; job < end; ++job) {
int64_t ii = m0 + job / xtiles * RM;
int64_t jj = n0 + job % xtiles * RN;
kernel<RM, RN>(ii, jj);
}
}
const TA *const A;
const block_q8_0 *const B;
float *C;
const int64_t k;
const int64_t lda;
const int64_t ldb;
const int64_t ldc;
const int ith;
const int nth;
};
class tinyBLAS_PPC {
public:
tinyBLAS_PPC(int64_t k,
const float *A, int64_t lda,
const float *B, int64_t ldb,
float *C, int64_t ldc,
int ith, int nth)
: A(A), B(B), C(C), k(k), lda(lda), ldb(ldb), ldc(ldc), ith(ith), nth(nth) {
}
void matmul(int64_t m, int64_t n) {
mnpack(0, m, 0, n);
}
private:
void (tinyBLAS_PPC::*kernel)(int64_t, int64_t);
inline void vector_permute_store_4(vector float *src, float *vecOffset) {
vector float t1, t2, t3, t4, t5, t6, t7, t8;
t1 = vec_mergeh(src[0], src[1]);
t2 = vec_mergeh(src[2], src[3]);
t3 = vec_mergel(src[0], src[1]);
t4 = vec_mergel(src[2], src[3]);
t5 = vec_xxpermdi(t1, t2, 0);
t6 = vec_xxpermdi(t1, t2, 3);
t7 = vec_xxpermdi(t3, t4, 0);
t8 = vec_xxpermdi(t3, t4, 3);
vec_xst(t5, 0, vecOffset);
vec_xst(t6, 0, vecOffset + 4);
vec_xst(t7, 0, vecOffset + 8);
vec_xst(t8, 0, vecOffset + 12);
}
inline void vector_permute_store_8(vector float *src, float *vecOffset) {
vector float t1, t2, t3, t4, t5, t6, t7, t8;
t1 = vec_mergeh(src[0], src[1]);
t2 = vec_mergeh(src[2], src[3]);
t3 = vec_mergeh(src[4], src[5]);
t4 = vec_mergeh(src[6], src[7]);
t5 = vec_xxpermdi(t1, t2, 0);
t6 = vec_xxpermdi(t3, t4, 0);
t7 = vec_xxpermdi(t1, t2, 3);
t8 = vec_xxpermdi(t3, t4, 3);
vec_xst(t5, 0, vecOffset);
vec_xst(t6, 0, vecOffset + 4);
vec_xst(t7, 0, vecOffset + 8);
vec_xst(t8, 0, vecOffset + 12);
t1 = vec_mergel(src[0], src[1]);
t2 = vec_mergel(src[2], src[3]);
t3 = vec_mergel(src[4], src[5]);
t4 = vec_mergel(src[6], src[7]);
t5 = vec_xxpermdi(t1, t2, 0);
t6 = vec_xxpermdi(t3, t4, 0);
t7 = vec_xxpermdi(t1, t2, 3);
t8 = vec_xxpermdi(t3, t4, 3);
vec_xst(t5, 0, vecOffset + 16);
vec_xst(t6, 0, vecOffset + 20);
vec_xst(t7, 0, vecOffset + 24);
vec_xst(t8, 0, vecOffset + 28);
}
void packTranspose(const float* a, int64_t lda, int rows, int cols, float* vec) {
int64_t i, j;
float * aoffsets[8];
float *aoffset = NULL, *boffset = NULL;
__vector_pair arr[8];
vector float c[8][2] = {0};
vector float c1[8] = {0};
vector float c2[8] = {0};
aoffset = const_cast<float*>(a);
boffset = vec;
j = (rows >> 3);
if (j > 0) {
do {
aoffsets[0] = aoffset;
for (int it = 1; it< 8; it++)
aoffsets[it] = aoffsets[it-1] + lda;
aoffset += 8 * lda;
i = (cols >> 3);
if (i > 0) {
do {
for (int it = 0; it< 8; it++) {
arr[it] = __builtin_vsx_lxvp(0, (__vector_pair*)aoffsets[it]);
__builtin_vsx_disassemble_pair(c[it], &arr[it]);
c1[it] = c[it][0];
c2[it] = c[it][1];
}
vector_permute_store_8(c1, boffset);
vector_permute_store_8(c2, boffset+32);
for (int it = 0; it < 4; it++)
aoffsets[it] = aoffsets[it] + 8*lda;
boffset += 64;
i--;
} while(i > 0);
}
if (cols & 4) {
for (int it = 0; it < 8 ; it++)
c1[it] = vec_xl(0, aoffsets[it]);
vector_permute_store_8(c1, boffset);
}
j--;
} while(j > 0);
}
if (rows & 4) {
aoffsets[0] = aoffset;
for (int it = 1; it < 4; it++)
aoffsets[it] = aoffsets[it-1] + lda;
aoffset += 4 * lda;
i = (cols >> 3);
if (i > 0) {
do {
for (int it = 0; it < 4; it++) {
arr[it] = __builtin_vsx_lxvp(0, (__vector_pair*)aoffsets[it]);
__builtin_vsx_disassemble_pair(c[it], &arr[it]);
c1[it] = c[it][0];
c2[it] = c[it][1];
}
vector_permute_store_4(c1, boffset);
vector_permute_store_4(c2, boffset+16);
for (int it = 0; it < 4; it++)
aoffsets[it] += 8*lda;
boffset += 32;
i--;
} while(i > 0);
}
if (cols & 4) {
for (int it = 0; it < 4; it++)
c1[it] = vec_xl(0, aoffsets[it]);
vector_permute_store_4(c1, boffset);
}
}
if (rows & 3) {
aoffsets[0] = aoffset;
for (int it = 1; it < 3; it++)
aoffsets[it] = aoffsets[it-1] + lda;
if (cols & 4) {
for (int it = 0; it < 3; it++)
c1[it] = vec_xl(0, aoffsets[it]);
vector_permute_store_4(c1, boffset);
}
}
}
void KERNEL_4x4(int64_t ii, int64_t jj) {
vec_t vec_A[4], vec_B[4], vec_C[4];
acc_t acc_0;
__builtin_mma_xxsetaccz(&acc_0);
for (int l = 0; l < k; l+=4) {
packTranspose(A+(ii*lda)+l, lda, 4, 4, (float*)vec_A);
packTranspose(B+(jj*ldb)+l, ldb, 4, 4, (float*)vec_B);
__builtin_mma_xvf32gerpp(&acc_0, vec_A[0], vec_B[0]);
__builtin_mma_xvf32gerpp(&acc_0, vec_A[1], vec_B[1]);
__builtin_mma_xvf32gerpp(&acc_0, vec_A[2], vec_B[2]);
__builtin_mma_xvf32gerpp(&acc_0, vec_A[3], vec_B[3]);
}
SAVE_ACC(&acc_0, ii, jj);
}
void KERNEL_4x8(int64_t ii, int64_t jj) {
vec_t vec_A[4], vec_B[8], vec_C[4];
acc_t acc_0, acc_1;
__builtin_mma_xxsetaccz(&acc_0);
__builtin_mma_xxsetaccz(&acc_1);
for (int64_t l = 0; l < k; l+=4) {
packTranspose(A+(ii*lda)+l, lda, 4, 4, (float*)vec_A);
packTranspose(B+(jj*ldb)+l, ldb, 8, 4, (float*)vec_B);
__builtin_mma_xvf32gerpp(&acc_0, vec_A[0], (vec_t)vec_B[0]);
__builtin_mma_xvf32gerpp(&acc_1, vec_A[0], (vec_t)vec_B[1]);
__builtin_mma_xvf32gerpp(&acc_0, vec_A[1], (vec_t)vec_B[2]);
__builtin_mma_xvf32gerpp(&acc_1, vec_A[1], (vec_t)vec_B[3]);
__builtin_mma_xvf32gerpp(&acc_0, vec_A[2], (vec_t)vec_B[4]);
__builtin_mma_xvf32gerpp(&acc_1, vec_A[2], (vec_t)vec_B[5]);
__builtin_mma_xvf32gerpp(&acc_0, vec_A[3], (vec_t)vec_B[6]);
__builtin_mma_xvf32gerpp(&acc_1, vec_A[3], (vec_t)vec_B[7]);
}
SAVE_ACC(&acc_0, ii, jj);
SAVE_ACC(&acc_1, ii, jj+4);
}
void KERNEL_8x4(int64_t ii, int64_t jj) {
vec_t vec_A[8], vec_B[4], vec_C[4];
acc_t acc_0, acc_1;
__builtin_mma_xxsetaccz(&acc_0);
__builtin_mma_xxsetaccz(&acc_1);
for (int64_t l = 0; l < k; l+=4) {
packTranspose(A+(ii*lda)+l, lda, 8, 4, (float*)vec_A);
packTranspose(B+(jj*ldb)+l, ldb, 4, 4, (float*)vec_B);
__builtin_mma_xvf32gerpp(&acc_0, (vec_t)vec_A[0], vec_B[0]);
__builtin_mma_xvf32gerpp(&acc_1, (vec_t)vec_A[1], vec_B[0]);
__builtin_mma_xvf32gerpp(&acc_0, (vec_t)vec_A[2], vec_B[1]);
__builtin_mma_xvf32gerpp(&acc_1, (vec_t)vec_A[3], vec_B[1]);
__builtin_mma_xvf32gerpp(&acc_0, (vec_t)vec_A[4], vec_B[2]);
__builtin_mma_xvf32gerpp(&acc_1, (vec_t)vec_A[5], vec_B[2]);
__builtin_mma_xvf32gerpp(&acc_0, (vec_t)vec_A[6], vec_B[3]);
__builtin_mma_xvf32gerpp(&acc_1, (vec_t)vec_A[7], vec_B[3]);
}
SAVE_ACC(&acc_0, ii, jj);
SAVE_ACC(&acc_1, ii+4, jj);
}
void KERNEL_8x8(int64_t ii, int64_t jj) {
vec_t vec_A[16], vec_B[16], vec_C[4];
acc_t acc_0, acc_1, acc_2, acc_3;
__builtin_mma_xxsetaccz(&acc_0);
__builtin_mma_xxsetaccz(&acc_1);
__builtin_mma_xxsetaccz(&acc_2);
__builtin_mma_xxsetaccz(&acc_3);
for (int l = 0; l < k; l+=8) {
packTranspose(A+(ii*lda)+l, lda, 8, 8, (float*)vec_A);
packTranspose(B+(jj*ldb)+l, ldb, 8, 8, (float*)vec_B);
for(int x = 0; x < 16; x+=2) {
__builtin_mma_xvf32gerpp(&acc_0, (vec_t)vec_A[x], vec_B[x]);
__builtin_mma_xvf32gerpp(&acc_1, (vec_t)vec_A[x], vec_B[x+1]);
__builtin_mma_xvf32gerpp(&acc_2, (vec_t)vec_A[x+1], vec_B[x]);
__builtin_mma_xvf32gerpp(&acc_3, (vec_t)vec_A[x+1], vec_B[x+1]);
}
}
SAVE_ACC(&acc_0, ii, jj);
SAVE_ACC(&acc_1, ii, jj+4);
SAVE_ACC(&acc_2, ii+4, jj);
SAVE_ACC(&acc_3, ii+4, jj+4);
}
void mnpack(int64_t m0, int64_t m, int64_t n0, int64_t n) {
int m_rem = MIN(m - m0, 8);
int n_rem = MIN(n - n0, 8);
int mc = 0, nc = 0;
if (m_rem >= 8 && n_rem >= 8) {
mc = 8;
nc = 8;
gemm<8, 8>(m0, m, n0, n);
} else if (m_rem >= 4 && n_rem >= 8) {
mc = 4;
nc = 8;
gemm<4, 8>(m0, m, n0, n);
} else if (m_rem >= 8 && n_rem >= 4) {
mc = 8;
nc = 4;
gemm<8, 4>(m0, m, n0, n);
} else if (m_rem >= 4 && n_rem >= 4) {
mc = 4;
nc = 4;
gemm<4, 4>(m0, m, n0, n);
} else {
mc = (m_rem >= 4) ? 4 : m_rem;
nc = (n_rem >= 4) ? 4 : n_rem;
if (mc == 0 || nc == 0)
return;
gemm_small(m0, m, n0, n, mc, nc);
}
int64_t mp = m0 + ((m - m0) / mc) * mc;
int64_t np = n0 + ((n - n0) / nc) * nc;
mnpack(mp, m, n0, np);
mnpack(m0, m, np, n);
}
void gemm_small(int64_t m0, int64_t m, int64_t n0, int64_t n, int RM, int RN) {
int64_t ytiles = (m - m0) / RM;
int64_t xtiles = (n - n0) / RN;
int64_t tiles = xtiles * ytiles;
int64_t duty = (tiles + nth - 1) / nth;
int64_t start = duty * ith;
int64_t end = start + duty;
if (end > tiles)
end = tiles;
for (int64_t job = start; job < end; ++job) {
int64_t ii = m0 + job / xtiles * RM;
int64_t jj = n0 + job % xtiles * RN;
vec_t vec_C[4];
acc_t acc_0;
__builtin_mma_xxsetaccz(&acc_0);
vec_t vec_A[4] {0}, vec_B[4] = {0};
for (int l=0; l<k; l+=4) {
/* 'GEMV Forwarding' concept is used in first two conditional loops.
* when one of the matrix has a single row/column, the elements are
* broadcasted, instead of using packing routine to prepack the
* matrix elements.
*/
if (RM == 1) {
float* a = const_cast<float*>(A+(ii)*lda+l);
packTranspose(B+(jj*ldb)+l, ldb, RN, 4, (float*)vec_B);
vec_A[0] = (vec_t)vec_xl(0,a);
vec_A[1] = (vec_t)vec_splats(*((float*)&vec_A+1));
vec_A[2] = (vec_t)vec_splats(*((float*)&vec_A+2));
vec_A[3] = (vec_t)vec_splats(*((float*)&vec_A+3));
} else if (RN == 1) {
packTranspose(A+(ii*lda)+l, lda, RM, 4, (float*)vec_A);
float* b = const_cast<float*>(B+(jj)*ldb+l);
vec_B[0] = (vec_t)vec_xl(0,b);
vec_B[1] = (vec_t)vec_splats(*((float*)&vec_B+1));
vec_B[2] = (vec_t)vec_splats(*((float*)&vec_B+2));
vec_B[3] = (vec_t)vec_splats(*((float*)&vec_B+3));
} else {
packTranspose(A+(ii*lda)+l, lda, RM, 4, (float*)vec_A);
packTranspose(B+(jj*ldb)+l, ldb, RN, 4, (float*)vec_B);
}
__builtin_mma_xvf32gerpp(&acc_0, vec_A[0], vec_B[0]);
__builtin_mma_xvf32gerpp(&acc_0, vec_A[1], vec_B[1]);
__builtin_mma_xvf32gerpp(&acc_0, vec_A[2], vec_B[2]);
__builtin_mma_xvf32gerpp(&acc_0, vec_A[3], vec_B[3]);
}
__builtin_mma_disassemble_acc(vec_C, &acc_0);
for (int I = 0; I < RM; I++) {
for (int J = 0; J < RN; J++) {
*((float*)(C+ii+((jj+J)*ldc)+I)) = *((float*)&vec_C[I]+J);
}
}
}
}
template <int RM, int RN>
NOINLINE void gemm(int64_t m0, int64_t m, int64_t n0, int64_t n) {
int64_t ytiles = (m - m0) / RM;
int64_t xtiles = (n - n0) / RN;
int64_t tiles = xtiles * ytiles;
int64_t duty = (tiles + nth - 1) / nth;
int64_t start = duty * ith;
int64_t end = start + duty;
if (RM == 4 && RN == 4) {
kernel = &tinyBLAS_PPC::KERNEL_4x4;
} else if (RM == 4 && RN == 8) {
kernel = &tinyBLAS_PPC::KERNEL_4x8;
} else if (RM == 8 && RN == 4) {
kernel = &tinyBLAS_PPC::KERNEL_8x4;
} else if (RM == 8 && RN == 8) {
kernel = &tinyBLAS_PPC::KERNEL_8x8;
}
if (end > tiles)
end = tiles;
for (int64_t job = start; job < end; ++job) {
int64_t ii = m0 + job / xtiles * RM;
int64_t jj = n0 + job % xtiles * RN;
(this->*kernel)(ii, jj);
}
}
const float *const A;
const float *const B;
float *C;
const int64_t k;
const int64_t lda;
const int64_t ldb;
const int64_t ldc;
const int ith;
const int nth;
};
#endif
} // namespace
/**
* Performs optimized matrix multiplication on CPU.
*
* This subroutine may compute C = Aᵀ * B with column major ordering.
* Despite its name, this isn't a generalized implementation. Work is
* only performed when a handwritten kernel is written and available.
* Otherwise the caller should fall back to a general matmul routine.
*
* For example, for single-threaded single-precision GEMM you can say
*
* llamafile_sgemm(m, n, k, A, lda, B, ldb, C, ldc,
* 0, 1,
* GGML_TYPE_F32, GGML_TYPE_F32, GGML_TYPE_F32);
*
* @param m is rows in `A` and `C`
* @param n is cols in `B` and `C`
* @param k is cols in `A` and rows in `B`
* @param A is first input matrix (always transposed)
* @param lda is row stride of `A`
* @param B is second input matrix (never transposed)
* @param ldb is row stride of `B`
* @param C is input/output array of output matrices
* @param ldc is row stride of `C`
* @param ith is thread id (must be less than `nth`)
* @param nth is number of threads (must be greater than zero)
* @param Atype is GGML data type of `A`
* @param Btype is GGML data type of `B`
* @param Ctype is GGML data type of `C`
* @return true if this function was able to service the matmul request
*/
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);
assert(k >= 0);
assert(lda >= k);
assert(ldb >= k);
assert(ldc >= m);
assert(params->nth > 0);
assert(params->ith < params->nth);
// only enable sgemm for prompt processing
#if !defined(__MMA__)
if (n < 2)
return false;
#endif
if (Ctype != GGML_TYPE_F32)
return false;
switch (Atype) {
case GGML_TYPE_F32: {
if (Btype != GGML_TYPE_F32)
return false;
#if defined(__AVX512F__)
tinyBLAS<16, __m512, __m512, float, float, float> tb{ params,
k, (const float *)A, lda,
(const float *)B, ldb,
(float *)C, ldc};
return tb.matmul(m, n);
#elif defined(__AVX__) || defined(__AVX2__)
tinyBLAS<8, __m256, __m256, float, float, float> tb{ params,
k, (const float *)A, lda,
(const float *)B, ldb,
(float *)C, ldc};
return tb.matmul(m, n);
#elif defined(__ARM_NEON)
if (n < 4)
return false;
tinyBLAS<4, float32x4_t, float32x4_t, float, float, float> tb{ params,
k, (const float *)A, lda,
(const float *)B, ldb,
(float *)C, ldc};
return tb.matmul(m, n);
#elif defined(__VXE__) || defined(__VXE2__)
if (n < 4)
return false;
tinyBLAS<4, float32x4_t, float32x4_t, float, float, float> tb{ params,
k, (const float *)A, lda,
(const float *)B, ldb,
(float *)C, ldc};
return tb.matmul(m, n);
#elif defined(__MMA__)
if (k % 8)
return false;
tinyBLAS_PPC tb{
k, (const float *)A, lda,
(const float *)B, ldb,
(float *)C, ldc,
params->ith, params->nth};
tb.matmul(m, n);
return true;
#else
return false;
#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);
}
#elif defined(__MMA__)
if ((k % 8))
return false;
if(Btype == GGML_TYPE_BF16) {
tinyBLAS_BF16_PPC<ggml_bf16_t, ggml_bf16_t, float> tb{ k,
(const ggml_bf16_t *)A, lda,
(const ggml_bf16_t *)B, ldb,
(float *)C, ldc,
params->ith, params->nth};
tb.matmul(m, n);
return true;
}
#endif
return false;
}
case GGML_TYPE_F16: {
#if defined(__AVX512F__)
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 (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 (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 (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);
}
#elif defined(__VXE__) || defined(__VXE2__)
if (n < 4)
return false;
if (Btype == GGML_TYPE_F16) {
tinyBLAS<4, float32x4_t, float32x4_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);
}
#endif
return false;
}
case GGML_TYPE_Q8_0: {
if (Btype != GGML_TYPE_Q8_0)
return false;
#if defined(__AVX2__) || defined(__AVX512F__) || defined(__AVX__)
tinyBLAS_Q0_AVX<block_q8_0, block_q8_0, float> tb{
k, (const block_q8_0 *)A, lda,
(const block_q8_0 *)B, ldb,
(float *)C, ldc,
params->ith, params->nth};
tb.matmul(m, n);
return true;
#elif defined(__ARM_FEATURE_DOTPROD)
tinyBLAS_Q0_ARM<block_q8_0> tb{
k, (const block_q8_0 *)A, lda,
(const block_q8_0 *)B, ldb,
(float *)C, ldc,
params->ith, params->nth};
tb.matmul(m, n);
return true;
#elif defined(__MMA__)
//TO-DO: Remove this condition once gemv forwarding is enabled.
if (n < 8 && n != 4)
return false;
if (m < 8 && m != 4)
return false;
tinyBLAS_Q0_PPC<block_q8_0> tb{
k, (const block_q8_0 *)A, lda,
(const block_q8_0 *)B, ldb,
(float *)C, ldc,
params->ith, params->nth};
tb.matmul(m, n);
return true;
#else
return false;
#endif
}
case GGML_TYPE_Q4_0: {
if (Btype != GGML_TYPE_Q8_0)
return false;
#if defined(__AVX2__) || defined(__AVX512F__) || defined(__AVX__)
tinyBLAS_Q0_AVX<block_q4_0, block_q8_0, float> tb{
k, (const block_q4_0 *)A, lda,
(const block_q8_0 *)B, ldb,
(float *)C, ldc,
params->ith, params->nth};
tb.matmul(m, n);
return true;
#elif defined(__ARM_FEATURE_DOTPROD)
tinyBLAS_Q0_ARM<block_q4_0> tb{
k, (const block_q4_0 *)A, lda,
(const block_q8_0 *)B, ldb,
(float *)C, ldc,
params->ith, params->nth};
tb.matmul(m, n);
return true;
#elif defined(__MMA__)
//TO-DO: Remove this condition once gemv forwarding is enabled.
if (n < 8 && n != 4)
return false;
if (m < 8 && m != 4)
return false;
tinyBLAS_Q0_PPC<block_q4_0> tb{
k, (const block_q4_0 *)A, lda,
(const block_q8_0 *)B, ldb,
(float *)C, ldc,
params->ith, params->nth};
tb.matmul(m, n);
return true;
#else
return false;
#endif
}
case GGML_TYPE_Q5_0: {
if (Btype != GGML_TYPE_Q8_0)
return false;
#if defined(__AVX2__) || defined(__AVX512F__) || defined(__AVX__)
tinyBLAS_Q0_AVX<block_q5_0, block_q8_0, float> tb{
k, (const block_q5_0 *)A, lda,
(const block_q8_0 *)B, ldb,
(float *)C, ldc,
params->ith, params->nth};
tb.matmul(m, n);
return true;
#else
return false;
#endif
}
case GGML_TYPE_IQ4_NL: {
if (Btype != GGML_TYPE_Q8_0)
return false;
#if defined(__AVX2__) || defined(__AVX512F__) || defined(__AVX__)
tinyBLAS_Q0_AVX<block_iq4_nl, block_q8_0, float> tb{
k, (const block_iq4_nl *)A, lda,
(const block_q8_0 *)B, ldb,
(float *)C, ldc,
params->ith, params->nth};
tb.matmul(m, n);
return true;
#else
return false;
#endif
}
default:
return false;
}
(void)params;
(void)m;
(void)n;
(void)k;
(void)A;
(void)lda;
(void)B;
(void)ldb;
(void)C;
(void)ldc;
(void)Atype;
(void)Btype;
(void)Ctype;
}