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ggml-cpu-aarch64.cpp
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#define GGML_COMMON_IMPL_CPP
#define GGML_COMMON_DECL_CPP
#include "ggml-common.h"
#include "ggml-backend-impl.h"
#include "ggml-quants.h"
#include "ggml-impl.h"
#include "ggml-cpu.h"
#include "ggml-cpu-impl.h"
#include "ggml-cpu-traits.h"
#include <cmath>
#include <cstring>
#include <cassert>
#include <cfloat>
#include <cstdlib> // for qsort
#include <cstdio> // for GGML_ASSERT
#include "ggml-cpu-aarch64.h"
// TODO: move to include file?
template <int K> constexpr int QK_0() {
if constexpr (K == 4) {
return QK4_0;
}
if constexpr (K == 8) {
return QK8_0;
}
return -1;
}
template <int K, int N> struct block {
ggml_half d[N]; // deltas for N qK_0 blocks
int8_t qs[(QK_0<K>() * N * K) / 8]; // quants for N qK_0 blocks
};
// control size
static_assert(sizeof(block<4, 4>) == 4 * sizeof(ggml_half) + QK8_0 * 2, "wrong block<4,4> size/padding");
static_assert(sizeof(block<4, 8>) == 8 * sizeof(ggml_half) + QK8_0 * 4, "wrong block<4,8> size/padding");
static_assert(sizeof(block<8, 4>) == 4 * sizeof(ggml_half) + QK8_0 * 4, "wrong block<8,4> size/padding");
static_assert(sizeof(block<8, 8>) == 8 * sizeof(ggml_half) + QK8_0 * 8, "wrong block<8,8> size/padding");
using block_q4_0x4 = block<4, 4>;
using block_q4_0x8 = block<4, 8>;
using block_q8_0x4 = block<8, 4>;
using block_q8_0x8 = block<8, 8>;
struct block_q4_Kx8 {
ggml_half d[8]; // super-block scale for quantized scales
ggml_half dmin[8]; // super-block scale for quantized mins
uint8_t scales[96]; // scales and mins, quantized with 6 bits
uint8_t qs[1024]; // 4--bit quants
};
static_assert(sizeof(block_q4_Kx8) == sizeof(ggml_half) * 16 + K_SCALE_SIZE * 8 + QK_K * 4, "wrong q4_K block size/padding");
struct block_q8_Kx4 {
float d[4]; // delta
int8_t qs[QK_K * 4]; // quants
int16_t bsums[QK_K / 4]; // sum of quants in groups of 16
};
static_assert(sizeof(block_q8_Kx4) == sizeof(float) * 4 + QK_K * 4 + (QK_K / 4) * sizeof(int16_t), "wrong q8_K block size/padding");
struct block_iq4_nlx4 {
ggml_half d[4]; // deltas for 4 iq4_nl blocks
uint8_t qs[QK4_NL * 2]; // nibbles / quants for 4 iq4_nl blocks
};
static_assert(sizeof(block_iq4_nlx4) == 4 * sizeof(ggml_half) + QK4_NL * 2, "wrong iq4_nlx4 block size/padding");
#if defined(__GNUC__)
#pragma GCC diagnostic ignored "-Woverlength-strings"
#elif defined(_MSC_VER)
#pragma warning(disable: 4244 4267) // possible loss of data
#endif
#define UNUSED GGML_UNUSED
static inline int nearest_int(float fval) {
assert(fabsf(fval) <= 4194303.f);
float val = fval + 12582912.f;
int i; memcpy(&i, &val, sizeof(int));
return (i & 0x007fffff) - 0x00400000;
}
// Functions to create the interleaved data layout formats
// interleave 4 block_q4_0s in blocks of blck_size_interleave
// returns an interleaved block_q4_0x4
// in the interleaved block_q4_0x4, place deltas for 4 block_q4_0 blocks
// first, then interleave quants from 4 block_q4_0s in blocks of blck_size_interleave
//
// - in : an array of block_q4_0 pointers
// - blck_size_interleave : the block_q4_0 quants bytes are interleaved in blocks of
// blck_size_interleave bytes
// - xor_mask : the mask to convert the nibbles in block_q4_0 quants bytes
// from bias offset form to pure sign form (this saves subtract
// operations durin unpacking)
//
#if defined(__AVX__)
#if defined(__F16C__)
#if defined(__AVX512F__)
#define GGML_F32Cx8x2_LOAD(x, y) _mm512_cvtph_ps(_mm256_set_m128i(_mm_loadu_si128((const __m128i *)(y)), _mm_loadu_si128((const __m128i *)(x))))
#define GGML_F32Cx16_REPEAT_LOAD(x) _mm512_cvtph_ps(_mm256_set_m128i(x, x))
#endif
// the _mm256_cvt intrinsics require F16C
#define GGML_F32Cx8_LOAD(x) _mm256_cvtph_ps(_mm_loadu_si128((const __m128i *)(x)))
#define GGML_F32Cx8_REPEAT_LOAD(x, loadMask) _mm256_cvtph_ps(_mm_shuffle_epi32(_mm_maskload_epi32((int const*)(x), loadMask), 68))
#define GGML_F32Cx8_REARRANGE_LOAD(x, arrangeMask) _mm256_cvtph_ps(_mm_shuffle_epi8(_mm_loadu_si128((const __m128i *) x), arrangeMask))
#else
#if defined(__AVX512F__)
static inline __m512 __avx512_f32cx8x2_load(ggml_fp16_t *x, ggml_fp16_t *y) {
float tmp[16];
for (int i = 0; i < 8; i++) {
tmp[i] = GGML_FP16_TO_FP32(x[i]);
}
for (int i = 0; i < 8; i++) {
tmp[i + 8] = GGML_FP16_TO_FP32(y[i]);
}
return _mm512_loadu_ps(tmp);
}
static inline __m512 __avx512_repeat_f32cx16_load(__m128i x) {
float tmp[16];
uint16_t tmphalf[8];
_mm_storeu_si128((__m128i*)tmphalf, x);
for (int i = 0; i < 4; i++) {
tmp[i] = GGML_FP16_TO_FP32(tmphalf[i]);
tmp[i + 4] = GGML_FP16_TO_FP32(tmphalf[i]);
tmp[i + 8] = GGML_FP16_TO_FP32(tmphalf[i]);
tmp[i + 12] = GGML_FP16_TO_FP32(tmphalf[i]);
}
return _mm512_loadu_ps(tmp);
}
#endif
static inline __m256 __avx_f32cx8_load(ggml_fp16_t *x) {
float tmp[8];
for (int i = 0; i < 8; i++) {
tmp[i] = GGML_FP16_TO_FP32(x[i]);
}
return _mm256_loadu_ps(tmp);
}
static inline __m256 __avx_repeat_f32cx8_load(ggml_fp16_t *x) {
float tmp[8];
for (int i = 0; i < 4; i++) {
tmp[i] = GGML_FP16_TO_FP32(x[i]);
tmp[i + 4] = GGML_FP16_TO_FP32(x[i]);
}
return _mm256_loadu_ps(tmp);
}
static inline __m256 __avx_rearranged_f32cx8_load(ggml_fp16_t *x, __m128i arrangeMask) {
uint16_t tmphalf[8];
float tmp[8];
_mm_storeu_si128((__m128i*)tmphalf, _mm_shuffle_epi8(_mm_loadu_si128((const __m128i *) x), arrangeMask));
for (int i = 0; i < 8; i++) {
tmp[i] = GGML_FP16_TO_FP32(tmphalf[i]);
}
return _mm256_loadu_ps(tmp);
}
#define GGML_F32Cx8_LOAD(x) __avx_f32cx8_load(x)
#define GGML_F32Cx8_REPEAT_LOAD(x, loadMask) __avx_repeat_f32cx8_load(x)
#define GGML_F32Cx8_REARRANGE_LOAD(x, arrangeMask) __avx_rearranged_f32cx8_load(x, arrangeMask)
#if defined(__AVX512F__)
#define GGML_F32Cx8x2_LOAD(x, y) __avx512_f32cx8x2_load(x, y)
#define GGML_F32Cx16_REPEAT_LOAD(x) __avx512_repeat_f32cx16_load(x)
#endif
#endif
#endif
#if defined(__AVX2__) || defined(__AVX512F__)
#if defined(__AVX512F__)
// add int16_t pairwise and return as 512 bit int vector, then add the accumulator
static inline __m512i sum_i16_pairs_acc_int32x16(const __m512i acc, const __m512i x) {
const __m512i ones = _mm512_set1_epi16(1);
return _mm512_add_epi32(acc, _mm512_madd_epi16(ones, x));
}
static inline __m512i mul_sum_us8_pairs_acc_int32x16(const __m512i acc, const __m512i ax, const __m512i sy) {
#if defined(__AVX512VNNI__)
return _mm512_dpbusd_epi32(acc, ax, sy);
#else
// Perform multiplication and create 16-bit values
const __m512i dot = _mm512_maddubs_epi16(ax, sy);
return sum_i16_pairs_acc_int32x16(acc, dot);
#endif
}
// multiply int8_t, add results pairwise twice and return as 512 bit int vector,then add the accumulator
static inline __m512i mul_sum_i8_pairs_acc_int32x16(const __m512i acc, const __m512i x, const __m512i y) {
const __m512i zero = _mm512_setzero_si512();
// Get absolute values of x vectors
const __m512i ax = _mm512_abs_epi8(x);
// Sign the values of the y vectors
__mmask64 blt0 = _mm512_movepi8_mask(x);
const __m512i sy = _mm512_mask_sub_epi8(y, blt0, zero, y);
return mul_sum_us8_pairs_acc_int32x16(acc, ax, sy);
}
#endif
// add int16_t pairwise and return as 256 bit int vector, then add the accumulator
static inline __m256i sum_i16_pairs_acc_int32x8(const __m256i acc, const __m256i x) {
const __m256i ones = _mm256_set1_epi16(1);
return _mm256_add_epi32(acc, _mm256_madd_epi16(ones, x));
}
static inline __m256i mul_sum_us8_pairs_acc_int32x8(const __m256i acc, const __m256i ax, const __m256i sy) {
#if defined(__AVX512VNNI__) && defined(__AVX512VL__)
return _mm256_dpbusd_epi32(acc, ax, sy);
#elif defined(__AVXVNNI__)
return _mm256_dpbusd_avx_epi32(acc, ax, sy);
#else
// Perform multiplication and create 16-bit values
const __m256i dot = _mm256_maddubs_epi16(ax, sy);
return sum_i16_pairs_acc_int32x8(acc, dot);
#endif
}
// Integer variant of the function defined in ggml-quants.c
// multiply int8_t, add results pairwise twice and return as 256 bit int vector, then add the accumulator
static inline __m256i mul_sum_i8_pairs_acc_int32x8(const __m256i acc, const __m256i x, const __m256i y) {
#if defined(__AVXVNNIINT8__)
return _mm256_dpbssd_epi32(acc, x, y);
#else
// Get absolute values of x vectors
const __m256i ax = _mm256_sign_epi8(x, x);
// Sign the values of the y vectors
const __m256i sy = _mm256_sign_epi8(y, x);
return mul_sum_us8_pairs_acc_int32x8(acc, ax, sy);
#endif
}
#endif
static const int8_t kvalues_iq4nl[16] = {-127, -104, -83, -65, -49, -35, -22, -10, 1, 13, 25, 38, 53, 69, 89, 113};
static void ggml_quantize_mat_q8_0_4x4(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, int64_t k) {
assert(QK8_0 == 32);
assert(k % QK8_0 == 0);
const int nb = k / QK8_0;
block_q8_0x4 * GGML_RESTRICT y = (block_q8_0x4 *) vy;
#if defined(__ARM_NEON)
float32x4_t srcv[4][8];
float id[4];
for (int i = 0; i < nb; i++) {
float32x4_t asrcv[8];
float32x4_t amaxv[8];
for (int row_iter = 0; row_iter < 4; row_iter++) {
for (int j = 0; j < 8; j++) srcv[row_iter][j] = vld1q_f32(x + row_iter * k + i * 32 + 4 * j);
for (int j = 0; j < 8; j++) asrcv[j] = vabsq_f32(srcv[row_iter][j]);
for (int j = 0; j < 4; j++) amaxv[2 * j] = vmaxq_f32(asrcv[2 * j], asrcv[2 * j + 1]);
for (int j = 0; j < 2; j++) amaxv[4 * j] = vmaxq_f32(amaxv[4 * j], amaxv[4 * j + 2]);
for (int j = 0; j < 1; j++) amaxv[8 * j] = vmaxq_f32(amaxv[8 * j], amaxv[8 * j + 4]);
const float amax = vmaxvq_f32(amaxv[0]);
const float d = amax / ((1 << 7) - 1);
id[row_iter] = d ? 1.0f / d : 0.0f;
y[i].d[row_iter] = GGML_FP32_TO_FP16(d);
}
for (int j = 0; j < 8; j++) {
float32x4_t v = vmulq_n_f32(srcv[0][j], id[0]);
int32x4_t vi = vcvtnq_s32_f32(v);
y[i].qs[16 * j + 0] = vgetq_lane_s32(vi, 0);
y[i].qs[16 * j + 1] = vgetq_lane_s32(vi, 1);
y[i].qs[16 * j + 2] = vgetq_lane_s32(vi, 2);
y[i].qs[16 * j + 3] = vgetq_lane_s32(vi, 3);
v = vmulq_n_f32(srcv[1][j], id[1]);
vi = vcvtnq_s32_f32(v);
y[i].qs[16 * j + 4] = vgetq_lane_s32(vi, 0);
y[i].qs[16 * j + 5] = vgetq_lane_s32(vi, 1);
y[i].qs[16 * j + 6] = vgetq_lane_s32(vi, 2);
y[i].qs[16 * j + 7] = vgetq_lane_s32(vi, 3);
v = vmulq_n_f32(srcv[2][j], id[2]);
vi = vcvtnq_s32_f32(v);
y[i].qs[16 * j + 8] = vgetq_lane_s32(vi, 0);
y[i].qs[16 * j + 9] = vgetq_lane_s32(vi, 1);
y[i].qs[16 * j + 10] = vgetq_lane_s32(vi, 2);
y[i].qs[16 * j + 11] = vgetq_lane_s32(vi, 3);
v = vmulq_n_f32(srcv[3][j], id[3]);
vi = vcvtnq_s32_f32(v);
y[i].qs[16 * j + 12] = vgetq_lane_s32(vi, 0);
y[i].qs[16 * j + 13] = vgetq_lane_s32(vi, 1);
y[i].qs[16 * j + 14] = vgetq_lane_s32(vi, 2);
y[i].qs[16 * j + 15] = vgetq_lane_s32(vi, 3);
}
}
#else
// scalar
const int blck_size_interleave = 4;
float srcv[4][QK8_0];
float id[4];
for (int i = 0; i < nb; i++) {
for (int row_iter = 0; row_iter < 4; row_iter++) {
float amax = 0.0f; // absolute max
for (int j = 0; j < QK8_0; j++) {
srcv[row_iter][j] = x[row_iter * k + i * QK8_0 + j];
amax = MAX(amax, fabsf(srcv[row_iter][j]));
}
const float d = amax / ((1 << 7) - 1);
id[row_iter] = d ? 1.0f / d : 0.0f;
y[i].d[row_iter] = GGML_FP32_TO_FP16(d);
}
for (int j = 0; j < QK8_0 * 4; j++) {
int src_offset = (j / (4 * blck_size_interleave)) * blck_size_interleave;
int src_id = (j % (4 * blck_size_interleave)) / blck_size_interleave;
src_offset += (j % blck_size_interleave);
float x0 = srcv[src_id][src_offset] * id[src_id];
y[i].qs[j] = roundf(x0);
}
}
#endif
}
static void ggml_quantize_mat_q8_0_4x8(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, int64_t k) {
assert(QK8_0 == 32);
assert(k % QK8_0 == 0);
const int nb = k / QK8_0;
block_q8_0x4 * GGML_RESTRICT y = (block_q8_0x4 *) vy;
#if defined(__ARM_NEON)
float32x4_t srcv[4][8];
float id[4];
for (int i = 0; i < nb; i++) {
float32x4_t asrcv[8];
float32x4_t amaxv[8];
for (int row_iter = 0; row_iter < 4; row_iter++) {
for (int j = 0; j < 8; j++) srcv[row_iter][j] = vld1q_f32(x + row_iter * k + i * 32 + 4 * j);
for (int j = 0; j < 8; j++) asrcv[j] = vabsq_f32(srcv[row_iter][j]);
for (int j = 0; j < 4; j++) amaxv[2 * j] = vmaxq_f32(asrcv[2 * j], asrcv[2 * j + 1]);
for (int j = 0; j < 2; j++) amaxv[4 * j] = vmaxq_f32(amaxv[4 * j], amaxv[4 * j + 2]);
for (int j = 0; j < 1; j++) amaxv[8 * j] = vmaxq_f32(amaxv[8 * j], amaxv[8 * j + 4]);
const float amax = vmaxvq_f32(amaxv[0]);
const float d = amax / ((1 << 7) - 1);
id[row_iter] = d ? 1.0f / d : 0.0f;
y[i].d[row_iter] = GGML_FP32_TO_FP16(d);
}
for (int j = 0; j < 4; j++) {
float32x4_t v = vmulq_n_f32(srcv[0][2 * j], id[0]);
int32x4_t vi = vcvtnq_s32_f32(v);
y[i].qs[32 * j + 0] = vgetq_lane_s32(vi, 0);
y[i].qs[32 * j + 1] = vgetq_lane_s32(vi, 1);
y[i].qs[32 * j + 2] = vgetq_lane_s32(vi, 2);
y[i].qs[32 * j + 3] = vgetq_lane_s32(vi, 3);
v = vmulq_n_f32(srcv[0][2 * j + 1], id[0]);
vi = vcvtnq_s32_f32(v);
y[i].qs[32 * j + 4] = vgetq_lane_s32(vi, 0);
y[i].qs[32 * j + 5] = vgetq_lane_s32(vi, 1);
y[i].qs[32 * j + 6] = vgetq_lane_s32(vi, 2);
y[i].qs[32 * j + 7] = vgetq_lane_s32(vi, 3);
v = vmulq_n_f32(srcv[1][2 * j], id[1]);
vi = vcvtnq_s32_f32(v);
y[i].qs[32 * j + 8] = vgetq_lane_s32(vi, 0);
y[i].qs[32 * j + 9] = vgetq_lane_s32(vi, 1);
y[i].qs[32 * j + 10] = vgetq_lane_s32(vi, 2);
y[i].qs[32 * j + 11] = vgetq_lane_s32(vi, 3);
v = vmulq_n_f32(srcv[1][2 * j + 1], id[1]);
vi = vcvtnq_s32_f32(v);
y[i].qs[32 * j + 12] = vgetq_lane_s32(vi, 0);
y[i].qs[32 * j + 13] = vgetq_lane_s32(vi, 1);
y[i].qs[32 * j + 14] = vgetq_lane_s32(vi, 2);
y[i].qs[32 * j + 15] = vgetq_lane_s32(vi, 3);
v = vmulq_n_f32(srcv[2][2 * j], id[2]);
vi = vcvtnq_s32_f32(v);
y[i].qs[32 * j + 16] = vgetq_lane_s32(vi, 0);
y[i].qs[32 * j + 17] = vgetq_lane_s32(vi, 1);
y[i].qs[32 * j + 18] = vgetq_lane_s32(vi, 2);
y[i].qs[32 * j + 19] = vgetq_lane_s32(vi, 3);
v = vmulq_n_f32(srcv[2][2 * j + 1], id[2]);
vi = vcvtnq_s32_f32(v);
y[i].qs[32 * j + 20] = vgetq_lane_s32(vi, 0);
y[i].qs[32 * j + 21] = vgetq_lane_s32(vi, 1);
y[i].qs[32 * j + 22] = vgetq_lane_s32(vi, 2);
y[i].qs[32 * j + 23] = vgetq_lane_s32(vi, 3);
v = vmulq_n_f32(srcv[3][2 * j], id[3]);
vi = vcvtnq_s32_f32(v);
y[i].qs[32 * j + 24] = vgetq_lane_s32(vi, 0);
y[i].qs[32 * j + 25] = vgetq_lane_s32(vi, 1);
y[i].qs[32 * j + 26] = vgetq_lane_s32(vi, 2);
y[i].qs[32 * j + 27] = vgetq_lane_s32(vi, 3);
v = vmulq_n_f32(srcv[3][2 * j + 1], id[3]);
vi = vcvtnq_s32_f32(v);
y[i].qs[32 * j + 28] = vgetq_lane_s32(vi, 0);
y[i].qs[32 * j + 29] = vgetq_lane_s32(vi, 1);
y[i].qs[32 * j + 30] = vgetq_lane_s32(vi, 2);
y[i].qs[32 * j + 31] = vgetq_lane_s32(vi, 3);
}
}
#elif defined(__AVX2__) || defined(__AVX__)
float id[4];
__m256 srcv[4][4];
__m256 idvec[4];
for (int i = 0; i < nb; i++) {
for (int row_iter = 0; row_iter < 4; row_iter++) {
// Load elements into 4 AVX vectors
__m256 v0 = _mm256_loadu_ps( x + row_iter * k + i * 32 );
__m256 v1 = _mm256_loadu_ps( x + row_iter * k + i * 32 + 8 );
__m256 v2 = _mm256_loadu_ps( x + row_iter * k + i * 32 + 16 );
__m256 v3 = _mm256_loadu_ps( x + row_iter * k + i * 32 + 24 );
// Compute max(abs(e)) for the block
const __m256 signBit = _mm256_set1_ps( -0.0f );
__m256 maxAbs = _mm256_andnot_ps( signBit, v0 );
maxAbs = _mm256_max_ps( maxAbs, _mm256_andnot_ps( signBit, v1 ) );
maxAbs = _mm256_max_ps( maxAbs, _mm256_andnot_ps( signBit, v2 ) );
maxAbs = _mm256_max_ps( maxAbs, _mm256_andnot_ps( signBit, v3 ) );
__m128 max4 = _mm_max_ps( _mm256_extractf128_ps( maxAbs, 1 ), _mm256_castps256_ps128( maxAbs ) );
max4 = _mm_max_ps( max4, _mm_movehl_ps( max4, max4 ) );
max4 = _mm_max_ss( max4, _mm_movehdup_ps( max4 ) );
const float maxScalar = _mm_cvtss_f32( max4 );
// Divided by 127.f to mirror results in quantize_row_q8_0
const float d = maxScalar / 127.f;
id[row_iter] = ( maxScalar != 0.0f ) ? 127.f / maxScalar : 0.0f; //d ? 1.0f / d : 0.0f;
// Store the scale for the individual block
y[i].d[row_iter] = GGML_FP32_TO_FP16(d);
// Store the values in blocks of eight values - Aim is to use these later for block interleaving
srcv[row_iter][0] = v0;
srcv[row_iter][1] = v1;
srcv[row_iter][2] = v2;
srcv[row_iter][3] = v3;
idvec[row_iter] = _mm256_set1_ps(id[row_iter]);
}
// The loop iterates four times - The aim is to get 4 corresponding chunks of eight bytes from the original weight blocks that are interleaved
for (int j = 0; j < 4; j++) {
// Apply the multiplier
__m256 v0 = _mm256_mul_ps(srcv[0][j], idvec[0]);
__m256 v1 = _mm256_mul_ps(srcv[1][j], idvec[1]);
__m256 v2 = _mm256_mul_ps(srcv[2][j], idvec[2]);
__m256 v3 = _mm256_mul_ps(srcv[3][j], idvec[3]);
// Round to nearest integer
v0 = _mm256_round_ps( v0, _MM_ROUND_NEAREST );
v1 = _mm256_round_ps( v1, _MM_ROUND_NEAREST );
v2 = _mm256_round_ps( v2, _MM_ROUND_NEAREST );
v3 = _mm256_round_ps( v3, _MM_ROUND_NEAREST );
// Convert floats to integers
__m256i i0 = _mm256_cvtps_epi32( v0 );
__m256i i1 = _mm256_cvtps_epi32( v1 );
__m256i i2 = _mm256_cvtps_epi32( v2 );
__m256i i3 = _mm256_cvtps_epi32( v3 );
#if defined(__AVX2__)
// Convert int32 to int16
i0 = _mm256_packs_epi32( i0, i1 );
i2 = _mm256_packs_epi32( i2, i3 );
// Convert int16 to int8
i0 = _mm256_packs_epi16( i0, i2 );
// Permute and store the quantized weights in the required order after the pack instruction
const __m256i perm = _mm256_setr_epi32( 0, 4, 1, 5, 2, 6, 3, 7 );
i0 = _mm256_permutevar8x32_epi32( i0, perm );
_mm256_storeu_si256((__m256i *)(y[i].qs + 32 * j), i0);
#else
// Since we don't have in AVX some necessary functions,
// we split the registers in half and call AVX2 analogs from SSE
__m128i ni0 = _mm256_castsi256_si128( i0 );
__m128i ni1 = _mm256_extractf128_si256( i0, 1);
__m128i ni2 = _mm256_castsi256_si128( i1 );
__m128i ni3 = _mm256_extractf128_si256( i1, 1);
__m128i ni4 = _mm256_castsi256_si128( i2 );
__m128i ni5 = _mm256_extractf128_si256( i2, 1);
__m128i ni6 = _mm256_castsi256_si128( i3 );
__m128i ni7 = _mm256_extractf128_si256( i3, 1);
// Convert int32 to int16
ni0 = _mm_packs_epi32( ni0, ni1 );
ni2 = _mm_packs_epi32( ni2, ni3 );
ni4 = _mm_packs_epi32( ni4, ni5 );
ni6 = _mm_packs_epi32( ni6, ni7 );
// Convert int16 to int8
ni0 = _mm_packs_epi16( ni0, ni2 );
ni4 = _mm_packs_epi16( ni4, ni6 );
_mm_storeu_si128((__m128i *)(y[i].qs + 32 * j), ni0);
_mm_storeu_si128((__m128i *)(y[i].qs + 32 * j + 16), ni4);
#endif
}
}
#else
// scalar
const int blck_size_interleave = 8;
float srcv[4][QK8_0];
float id[4];
for (int i = 0; i < nb; i++) {
for (int row_iter = 0; row_iter < 4; row_iter++) {
float amax = 0.0f; // absolute max
for (int j = 0; j < QK8_0; j++) {
srcv[row_iter][j] = x[row_iter * k + i * QK8_0 + j];
amax = MAX(amax, fabsf(srcv[row_iter][j]));
}
const float d = amax / ((1 << 7) - 1);
id[row_iter] = d ? 1.0f / d : 0.0f;
y[i].d[row_iter] = GGML_FP32_TO_FP16(d);
}
for (int j = 0; j < QK8_0 * 4; j++) {
int src_offset = (j / (4 * blck_size_interleave)) * blck_size_interleave;
int src_id = (j % (4 * blck_size_interleave)) / blck_size_interleave;
src_offset += (j % blck_size_interleave);
float x0 = srcv[src_id][src_offset] * id[src_id];
y[i].qs[j] = roundf(x0);
}
}
#endif
}
static void ggml_quantize_mat_q8_K_4x8(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, int64_t k) {
assert(QK_K == 256);
assert(k % QK_K == 0);
const int nb = k / QK_K;
block_q8_Kx4 * GGML_RESTRICT y = (block_q8_Kx4 *) vy;
#if defined(__AVX2__)
float iscale[4];
__m256 srcv[4][32];
__m256 iscale_vec[4];
for (int i = 0; i < nb; i++) {
for (int row_iter = 0; row_iter < 4; row_iter++) {
// Load elements into 4 AVX vectors
__m256 v0 = _mm256_loadu_ps( x + row_iter * k + i * 256 );
__m256 v1 = _mm256_loadu_ps( x + row_iter * k + i * 256 + 8 );
__m256 v2 = _mm256_loadu_ps( x + row_iter * k + i * 256 + 16 );
__m256 v3 = _mm256_loadu_ps( x + row_iter * k + i * 256 + 24 );
// Compute max(abs(e)) for the block
const __m256 signBit = _mm256_set1_ps( -0.0f );
__m256 abs0 = _mm256_andnot_ps( signBit, v0 );
__m256 abs1 = _mm256_andnot_ps( signBit, v1 );
__m256 abs2 = _mm256_andnot_ps( signBit, v2 );
__m256 abs3 = _mm256_andnot_ps( signBit, v3 );
__m256 maxAbs = _mm256_max_ps( abs0, abs1 );
maxAbs = _mm256_max_ps( maxAbs, abs2 );
maxAbs = _mm256_max_ps( maxAbs, abs3 );
__m256 mask0 = _mm256_cmp_ps( maxAbs, v0, _CMP_EQ_OQ );
__m256 mask1 = _mm256_cmp_ps( maxAbs, v1, _CMP_EQ_OQ );
__m256 mask2 = _mm256_cmp_ps( maxAbs, v2, _CMP_EQ_OQ );
__m256 mask3 = _mm256_cmp_ps( maxAbs, v3, _CMP_EQ_OQ );
__m256 maskAbs = _mm256_or_ps(_mm256_or_ps(mask0, mask1),_mm256_or_ps(mask2, mask3));
srcv[row_iter][0] = v0;
srcv[row_iter][1] = v1;
srcv[row_iter][2] = v2;
srcv[row_iter][3] = v3;
for (int sb = 1; sb < 8; sb++) {
// Temporarily stores absolute quant values
__m256 tempAbs = maxAbs;
// Load elements into 4 AVX vectors
__m256 v0 = _mm256_loadu_ps( x + row_iter * k + i * 256 + sb * 32);
__m256 v1 = _mm256_loadu_ps( x + row_iter * k + i * 256 + sb * 32 + 8 );
__m256 v2 = _mm256_loadu_ps( x + row_iter * k + i * 256 + sb * 32 + 16 );
__m256 v3 = _mm256_loadu_ps( x + row_iter * k + i * 256 + sb * 32 + 24 );
// Compute max(abs(e)) for the block
__m256 abs0 = _mm256_andnot_ps( signBit, v0 );
__m256 abs1 = _mm256_andnot_ps( signBit, v1 );
__m256 abs2 = _mm256_andnot_ps( signBit, v2 );
__m256 abs3 = _mm256_andnot_ps( signBit, v3 );
maxAbs = _mm256_max_ps( maxAbs, abs0 );
maxAbs = _mm256_max_ps( maxAbs, abs1 );
maxAbs = _mm256_max_ps( maxAbs, abs2 );
maxAbs = _mm256_max_ps( maxAbs, abs3 );
__m256 mask_prev = _mm256_cmp_ps( tempAbs, maxAbs, _CMP_EQ_OQ );
maskAbs = _mm256_and_ps( maskAbs, mask_prev );
mask0 = _mm256_cmp_ps( maxAbs, v0, _CMP_EQ_OQ );
mask1 = _mm256_cmp_ps( maxAbs, v1, _CMP_EQ_OQ );
mask2 = _mm256_cmp_ps( maxAbs, v2, _CMP_EQ_OQ );
mask3 = _mm256_cmp_ps( maxAbs, v3, _CMP_EQ_OQ );
__m256 mask_curr = _mm256_or_ps(_mm256_or_ps(mask0, mask1),_mm256_or_ps(mask2, mask3));
maskAbs = _mm256_or_ps(maskAbs, mask_curr);
srcv[row_iter][sb * 4] = v0;
srcv[row_iter][sb * 4 + 1] = v1;
srcv[row_iter][sb * 4 + 2] = v2;
srcv[row_iter][sb * 4 + 3] = v3;
}
__m128 max4 = _mm_max_ps( _mm256_extractf128_ps( maxAbs, 1 ), _mm256_castps256_ps128( maxAbs ) );
max4 = _mm_max_ps( max4, _mm_movehl_ps( max4, max4 ) );
max4 = _mm_max_ss( max4, _mm_movehdup_ps( max4 ) );
const float maxScalar = _mm_cvtss_f32( max4 );
__m256 maxScalarVec = _mm256_set1_ps(maxScalar);
__m256 mask_next = _mm256_cmp_ps( maxScalarVec, maxAbs, _CMP_EQ_OQ );
__m256 finalMask = _mm256_and_ps(maskAbs, mask_next);
const int mask = _mm256_movemask_ps(finalMask);
iscale[row_iter] = ( maxScalar != 0.0f ) ? 127.f / maxScalar : 0.0f;
if(mask) {
iscale[row_iter] = ( maxScalar != 0.0f ) ? -127.f / maxScalar: 0.0f;
}
y[i].d[row_iter] = maxScalar ? 1/iscale[row_iter] : 0;
iscale_vec[row_iter] = _mm256_set1_ps(iscale[row_iter]);
}
__m256i quants_interleaved[32];
for (int j = 0; j < 32; j++) {
// Apply the multiplier
__m256 v0 = _mm256_mul_ps(srcv[0][j], iscale_vec[0]);
__m256 v1 = _mm256_mul_ps(srcv[1][j], iscale_vec[1]);
__m256 v2 = _mm256_mul_ps(srcv[2][j], iscale_vec[2]);
__m256 v3 = _mm256_mul_ps(srcv[3][j], iscale_vec[3]);
// Round to nearest integer
v0 = _mm256_round_ps( v0, _MM_ROUND_NEAREST );
v1 = _mm256_round_ps( v1, _MM_ROUND_NEAREST );
v2 = _mm256_round_ps( v2, _MM_ROUND_NEAREST );
v3 = _mm256_round_ps( v3, _MM_ROUND_NEAREST );
// Convert floats to integers
__m256i i0 = _mm256_cvtps_epi32( v0 );
__m256i i1 = _mm256_cvtps_epi32( v1 );
__m256i i2 = _mm256_cvtps_epi32( v2 );
__m256i i3 = _mm256_cvtps_epi32( v3 );
// Convert int32 to int16
i0 = _mm256_packs_epi32( i0, i1 );
i2 = _mm256_packs_epi32( i2, i3 );
// Convert int16 to int8
i0 = _mm256_packs_epi16( i0, i2 );
// Permute and store the quantized weights in the required order after the pack instruction
const __m256i perm = _mm256_setr_epi32( 0, 4, 1, 5, 2, 6, 3, 7 );
i0 = _mm256_permutevar8x32_epi32( i0, perm );
_mm256_storeu_si256((__m256i *)(y[i].qs + 32 * j), i0);
quants_interleaved[j] = i0;
}
// Masks to shuffle the quants of corresonding sub blocks for rearraning quants for vectorized bsums computation
__m256i shuffle_mask_sb2 = _mm256_castsi128_si256(_mm_setr_epi8(0, 1, 0, 1, 4, 5, 6, 7, 8, 9, 8, 9, 12, 13, 14, 15));
shuffle_mask_sb2 = _mm256_permute2f128_si256(shuffle_mask_sb2, shuffle_mask_sb2, 0);
__m256i shuffle_mask_sb3 = _mm256_castsi128_si256(_mm_setr_epi8(0, 1, 2, 3, 0, 1, 6, 7, 8, 9, 10, 11, 8, 9, 14, 15));
shuffle_mask_sb3 = _mm256_permute2f128_si256(shuffle_mask_sb3, shuffle_mask_sb3, 0);
__m256i shuffle_mask_sb4 = _mm256_castsi128_si256(_mm_setr_epi8(0, 1, 2, 3, 4, 5, 0, 1, 8, 9, 10, 11, 12, 13, 8, 9));
shuffle_mask_sb4 = _mm256_permute2f128_si256(shuffle_mask_sb4, shuffle_mask_sb4, 0);
for (int k = 0; k < 4; k++) {
// Quants from four different sub blocks are taken
__m256i q0 = quants_interleaved[k * 8 + 0];
__m256i q1 = quants_interleaved[k * 8 + 1];
__m256i q2 = quants_interleaved[k * 8 + 2];
__m256i q3 = quants_interleaved[k * 8 + 3];
__m256i q4 = quants_interleaved[k * 8 + 4];
__m256i q5 = quants_interleaved[k * 8 + 5];
__m256i q6 = quants_interleaved[k * 8 + 6];
__m256i q7 = quants_interleaved[k * 8 + 7];
// The below code block has the first half of different sub blocks shuffled and blended so as to process 2 values from each sub block at a time
__m256i sb2_h1_shuffled = _mm256_shuffle_epi8(q2, shuffle_mask_sb2);
__m256i sb_h1_interleaved = _mm256_blend_epi16(q0, sb2_h1_shuffled, 34);
__m256i sb3_h1_shuffled = _mm256_shuffle_epi8(q4, shuffle_mask_sb3);
sb_h1_interleaved = _mm256_blend_epi16(sb_h1_interleaved, sb3_h1_shuffled, 68);
__m256i sb4_h1_shuffled = _mm256_shuffle_epi8(q6, shuffle_mask_sb4);
sb_h1_interleaved = _mm256_blend_epi16(sb_h1_interleaved, sb4_h1_shuffled, 136);
__m256i one = _mm256_set1_epi8(1);
__m256i bsums_r1 = _mm256_maddubs_epi16(one, sb_h1_interleaved);
for (int l = 0; l < 3; l++) {
// Quants value shifted to process next two values from each sub block
q0 = _mm256_srli_epi64(q0, 16);
q2 = _mm256_srli_epi64(q2, 16);
q4 = _mm256_srli_epi64(q4, 16);
q6 = _mm256_srli_epi64(q6, 16);
sb2_h1_shuffled = _mm256_shuffle_epi8(q2, shuffle_mask_sb2);
sb_h1_interleaved = _mm256_blend_epi16(q0, sb2_h1_shuffled, 34);
sb3_h1_shuffled = _mm256_shuffle_epi8(q4, shuffle_mask_sb3);
sb_h1_interleaved = _mm256_blend_epi16(sb_h1_interleaved, sb3_h1_shuffled, 68);
sb4_h1_shuffled = _mm256_shuffle_epi8(q6, shuffle_mask_sb4);
sb_h1_interleaved = _mm256_blend_epi16(sb_h1_interleaved, sb4_h1_shuffled, 136);
bsums_r1 = _mm256_add_epi16(bsums_r1, _mm256_maddubs_epi16(one, sb_h1_interleaved));
}
// The below code block has the second half of different sub blocks shuffled and blended so as to process 2 values from each sub block at a time
__m256i sb2_h2_shuffled = _mm256_shuffle_epi8(q3, shuffle_mask_sb2);
__m256i sb_h2_interleaved = _mm256_blend_epi16(q1, sb2_h2_shuffled, 34);
__m256i sb3_h2_shuffled = _mm256_shuffle_epi8(q5, shuffle_mask_sb3);
sb_h2_interleaved = _mm256_blend_epi16(sb_h2_interleaved, sb3_h2_shuffled, 68);
__m256i sb4_h2_shuffled = _mm256_shuffle_epi8(q7, shuffle_mask_sb4);
sb_h2_interleaved = _mm256_blend_epi16(sb_h2_interleaved, sb4_h2_shuffled, 136);
__m256i bsums_r2 = _mm256_maddubs_epi16(one, sb_h2_interleaved);
for (int l = 0; l < 3; l++) {
// Quants value shifted to process next two values from each sub block
q1 = _mm256_srli_epi64(q1, 16);
q3 = _mm256_srli_epi64(q3, 16);
q5 = _mm256_srli_epi64(q5, 16);
q7 = _mm256_srli_epi64(q7, 16);
sb2_h2_shuffled = _mm256_shuffle_epi8(q3, shuffle_mask_sb2);
sb_h2_interleaved = _mm256_blend_epi16(q1, sb2_h2_shuffled, 34);
sb3_h2_shuffled = _mm256_shuffle_epi8(q5, shuffle_mask_sb3);
sb_h2_interleaved = _mm256_blend_epi16(sb_h2_interleaved, sb3_h2_shuffled, 68);
sb4_h2_shuffled = _mm256_shuffle_epi8(q7, shuffle_mask_sb4);
sb_h2_interleaved = _mm256_blend_epi16(sb_h2_interleaved, sb4_h2_shuffled, 136);
bsums_r2 = _mm256_add_epi16(bsums_r2, _mm256_maddubs_epi16(one, sb_h2_interleaved));
}
// Overall bsums in interleaved fashion computed by adding results of both halves
__m256i bsums_r = _mm256_add_epi16(bsums_r1, bsums_r2);
_mm256_storeu_si256((__m256i *)(y[i].bsums + 16 * k), bsums_r);
}
}
#else
// scalar
const int blck_size_interleave = 8;
float srcv[4][QK_K];
float iscale[4];
for (int i = 0; i < nb; i++) {
for (int row_iter = 0; row_iter < 4; row_iter++) {
float amax = 0.0f; // absolute max
float max = 0;
for (int j = 0; j < QK_K; j++) {
srcv[row_iter][j] = x[row_iter * k + i * QK_K + j];
// Update the maximum value of the corresponding super block
if(amax < fabsf(srcv[row_iter][j])) {
amax = fabsf(srcv[row_iter][j]);
max = srcv[row_iter][j];
}
}
iscale[row_iter] = amax ? -127.f/max : 0;
y[i].d[row_iter] = amax ? 1/iscale[row_iter] : 0;
}
for (int j = 0; j < QK_K / 4; j++) {
y[i].bsums[j] = 0;
}
// Quants values are interleaved in sequence of eight bytes from corresponding super blocks
// Bsums values are interleaved in sequence of four bsums from each super block taken for interleaving
// i.e first four bsums from the first super block, followed by first four bsums from second super block and so on
for (int j = 0; j < QK_K * 4; j++) {
int src_offset = (j / (4 * blck_size_interleave)) * blck_size_interleave;
int src_id = (j % (4 * blck_size_interleave)) / blck_size_interleave;
src_offset += (j % blck_size_interleave);
int index = (((j & 31) >> 3) << 2) + ((j >> 8) << 4) + ((j >> 6) & 3);
float x0 = srcv[src_id][src_offset] * iscale[src_id];
y[i].qs[j] = nearest_int(x0);
y[i].bsums[index] += y[i].qs[j];
}
}
#endif
}
template <int64_t INTER_SIZE, ggml_type PARAM_TYPE>
void ggml_quantize_mat_t(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, int64_t nrow, int64_t n_per_row);
template <> void ggml_quantize_mat_t<4, GGML_TYPE_Q8_0>(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, int64_t nrow, int64_t n_per_row) {
assert(nrow == 4);
UNUSED(nrow);
ggml_quantize_mat_q8_0_4x4(x, vy, n_per_row);
}
template <> void ggml_quantize_mat_t<8, GGML_TYPE_Q8_0>(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, int64_t nrow, int64_t n_per_row) {
assert(nrow == 4);
UNUSED(nrow);
ggml_quantize_mat_q8_0_4x8(x, vy, n_per_row);
}
template <> void ggml_quantize_mat_t<8, GGML_TYPE_Q8_K>(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, int64_t nrow, int64_t n_per_row) {
assert(nrow == 4);
UNUSED(nrow);
ggml_quantize_mat_q8_K_4x8(x, vy, n_per_row);
}
static void ggml_gemv_q4_0_4x4_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc) {
const int qk = QK8_0;
const int nb = n / qk;
const int ncols_interleaved = 4;
const int blocklen = 4;
assert (n % qk == 0);
assert (nc % ncols_interleaved == 0);
UNUSED(s);
UNUSED(bs);
UNUSED(vx);
UNUSED(vy);
UNUSED(nr);
UNUSED(nc);
UNUSED(nb);
UNUSED(ncols_interleaved);
UNUSED(blocklen);
#if ! ((defined(_MSC_VER)) && ! defined(__clang__)) && defined(__aarch64__) && defined(__ARM_NEON) && defined(__ARM_FEATURE_DOTPROD)
if (ggml_cpu_has_neon() && ggml_cpu_has_dotprod()) {
const block_q4_0x4 * b_ptr = (const block_q4_0x4 *) vx;
for (int c = 0; c < nc; c += ncols_interleaved) {
const block_q8_0 * a_ptr = (const block_q8_0 *) vy;
float32x4_t acc = vdupq_n_f32(0);
for (int b = 0; b < nb; b++) {
int8x16_t b0 = vld1q_s8((const int8_t *) b_ptr->qs);
int8x16_t b1 = vld1q_s8((const int8_t *) b_ptr->qs + 16);
int8x16_t b2 = vld1q_s8((const int8_t *) b_ptr->qs + 32);
int8x16_t b3 = vld1q_s8((const int8_t *) b_ptr->qs + 48);
float16x4_t bd = vld1_f16((const __fp16 *) b_ptr->d);
int8x16_t a0 = vld1q_s8(a_ptr->qs);
int8x16_t a1 = vld1q_s8(a_ptr->qs + qk/2);
float16x4_t ad = vld1_dup_f16((const __fp16 *) &a_ptr->d);
int32x4_t ret = vdupq_n_s32(0);
ret = vdotq_laneq_s32(ret, b0 << 4, a0, 0);
ret = vdotq_laneq_s32(ret, b1 << 4, a0, 1);
ret = vdotq_laneq_s32(ret, b2 << 4, a0, 2);
ret = vdotq_laneq_s32(ret, b3 << 4, a0, 3);
ret = vdotq_laneq_s32(ret, b0 & 0xf0U, a1, 0);
ret = vdotq_laneq_s32(ret, b1 & 0xf0U, a1, 1);
ret = vdotq_laneq_s32(ret, b2 & 0xf0U, a1, 2);
ret = vdotq_laneq_s32(ret, b3 & 0xf0U, a1, 3);
acc = vfmaq_f32(acc, vcvtq_n_f32_s32(ret, 4),
vmulq_f32(vcvt_f32_f16(ad), vcvt_f32_f16(bd)));
a_ptr++;
b_ptr++;
}
vst1q_f32(s, acc);
s += ncols_interleaved;
}
return;
}
#endif // #if ! ((defined(_MSC_VER)) && ! defined(__clang__)) && defined(__aarch64__) && defined(__ARM_NEON) && defined(__ARM_FEATURE_DOTPROD)
float sumf[4];
int sumi;
const block_q8_0 * a_ptr = (const block_q8_0 *) vy;
for (int x = 0; x < nc / ncols_interleaved; x++) {
const block_q4_0x4 * b_ptr = (const block_q4_0x4 *) vx + (x * nb);
for (int j = 0; j < ncols_interleaved; j++) sumf[j] = 0.0;
for (int l = 0; l < nb; l++) {
for (int k = 0; k < (qk / (2 * blocklen)); k++) {
for (int j = 0; j < ncols_interleaved; j++) {
sumi = 0;
for (int i = 0; i < blocklen; ++i) {
const int v0 = (int8_t) (b_ptr[l].qs[k * ncols_interleaved * blocklen + j * blocklen + i] << 4);
const int v1 = (int8_t) (b_ptr[l].qs[k * ncols_interleaved * blocklen + j * blocklen + i] & 0xF0);
sumi += ((v0 * a_ptr[l].qs[k * blocklen + i]) + (v1 * a_ptr[l].qs[k * blocklen + i + qk / 2])) >> 4;
}
sumf[j] += sumi * GGML_FP16_TO_FP32(b_ptr[l].d[j]) * GGML_FP16_TO_FP32(a_ptr[l].d);
}
}
}
for (int j = 0; j < ncols_interleaved; j++) s[x * ncols_interleaved + j] = sumf[j];
}
}
static void ggml_gemv_q4_0_4x8_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, const void * GGML_RESTRICT vy, int nr, int nc) {
const int qk = QK8_0;
const int nb = n / qk;
const int ncols_interleaved = 4;
const int blocklen = 8;
assert (n % qk == 0);
assert (nc % ncols_interleaved == 0);
UNUSED(s);
UNUSED(bs);
UNUSED(vx);
UNUSED(vy);
UNUSED(nr);
UNUSED(nc);
UNUSED(nb);
UNUSED(ncols_interleaved);
UNUSED(blocklen);
#if ! ((defined(_MSC_VER)) && ! defined(__clang__)) && defined(__aarch64__) && defined(__ARM_NEON) && defined(__ARM_FEATURE_DOTPROD)
if (ggml_cpu_has_neon() && ggml_cpu_has_dotprod()) {
const block_q4_0x4 * b_ptr = (const block_q4_0x4 *) vx;
for (int c = 0; c < nc; c += ncols_interleaved) {
const block_q8_0 * a_ptr = (const block_q8_0 *) vy;
float32x4_t acc = vdupq_n_f32(0);
for (int b = 0; b < nb; b++) {
int8x16_t b0 = vld1q_s8((const int8_t *) b_ptr->qs);
int8x16_t b1 = vld1q_s8((const int8_t *) b_ptr->qs + 16);
int8x16_t b2 = vld1q_s8((const int8_t *) b_ptr->qs + 32);
int8x16_t b3 = vld1q_s8((const int8_t *) b_ptr->qs + 48);
float16x4_t bd = vld1_f16((const __fp16 *) b_ptr->d);
int8x16_t a0 = (int8x16_t) vld1q_dup_s64((const int64_t *) a_ptr->qs);
int8x16_t a1 = (int8x16_t) vld1q_dup_s64((const int64_t *) a_ptr->qs + 1);
int8x16_t a2 = (int8x16_t) vld1q_dup_s64((const int64_t *) a_ptr->qs + 2);
int8x16_t a3 = (int8x16_t) vld1q_dup_s64((const int64_t *) a_ptr->qs + 3);
float16x4_t ad = vld1_dup_f16((const __fp16 *) &a_ptr->d);
int32x4_t ret0 = vdupq_n_s32(0);
int32x4_t ret1 = vdupq_n_s32(0);
ret0 = vdotq_s32(ret0, b0 << 4, a0);
ret1 = vdotq_s32(ret1, b1 << 4, a0);
ret0 = vdotq_s32(ret0, b2 << 4, a1);
ret1 = vdotq_s32(ret1, b3 << 4, a1);
ret0 = vdotq_s32(ret0, b0 & 0xf0U, a2);
ret1 = vdotq_s32(ret1, b1 & 0xf0U, a2);
ret0 = vdotq_s32(ret0, b2 & 0xf0U, a3);
ret1 = vdotq_s32(ret1, b3 & 0xf0U, a3);
int32x4_t ret = vpaddq_s32(ret0, ret1);
acc = vfmaq_f32(acc, vcvtq_n_f32_s32(ret, 4),
vmulq_f32(vcvt_f32_f16(ad), vcvt_f32_f16(bd)));
a_ptr++;
b_ptr++;
}
vst1q_f32(s, acc);
s += ncols_interleaved;
}
return;
}
#endif // #if ! ((defined(_MSC_VER)) && ! defined(__clang__)) && defined(__aarch64__) && defined(__ARM_NEON) && defined(__ARM_FEATURE_DOTPROD)
float sumf[4];
int sumi;
const block_q8_0 * a_ptr = (const block_q8_0 *) vy;
for (int x = 0; x < nc / ncols_interleaved; x++) {
const block_q4_0x4 * b_ptr = (const block_q4_0x4 *) vx + (x * nb);
for (int j = 0; j < ncols_interleaved; j++) sumf[j] = 0.0;