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koboldcpp/ggml/src/ggml-cpu/arch/wasm/quants.c
xctan f470bc36be
ggml-cpu : split arch-specific implementations (#13892) 
* move ggml-cpu-aarch64 to repack

* split quantize_row_q8_0/1

* split helper functions

* split ggml_vec_dot_q4_0_q8_0

* split ggml_vec_dot_q4_1_q8_1

* split ggml_vec_dot_q5_0_q8_0

* split ggml_vec_dot_q5_1_q8_1

* split ggml_vec_dot_q8_0_q8_0

* split ggml_vec_dot_tq1_0_q8_K

* split ggml_vec_dot_tq2_0_q8_K

* split ggml_vec_dot_q2_K_q8_K

* split ggml_vec_dot_q3_K_q8_K

* split ggml_vec_dot_q4_K_q8_K

* split ggml_vec_dot_q5_K_q8_K

* split ggml_vec_dot_q6_K_q8_K

* split ggml_vec_dot_iq2_xxs_q8_K

* split ggml_vec_dot_iq2_xs_q8_K

* split ggml_vec_dot_iq2_s_q8_K

* split ggml_vec_dot_iq3_xxs_q8_K

* split ggml_vec_dot_iq3_s_q8_K

* split ggml_vec_dot_iq1_s_q8_K

* split ggml_vec_dot_iq1_m_q8_K

* split ggml_vec_dot_iq4_nl_q8_0

* split ggml_vec_dot_iq4_xs_q8_K

* fix typos

* fix missing prototypes

* rename ggml-cpu-quants.c

* rename ggml-cpu-traits

* rename arm folder

* move cpu-feats-x86.cpp

* rename ggml-cpu-hbm

* update arm detection macro in quants.c

* move iq quant tables

* split ggml_quantize_mat_q8_0/K

* split ggml_gemv_*

* split ggml_gemm_*

* rename namespace aarch64 to repack

* use weak aliases to replace test macros

* rename GGML_CPU_AARCH64 to GGML_CPU_REPACK

* rename more aarch64 to repack

* clean up rebase leftover

* fix compilation errors

* remove trailing spaces

* try to fix clang compilation errors

* try to fix clang compilation errors again

* try to fix clang compilation errors, 3rd attempt

* try to fix clang compilation errors, 4th attempt

* try to fix clang compilation errors, 5th attempt

* try to fix clang compilation errors, 6th attempt

* try to fix clang compilation errors, 7th attempt

* try to fix clang compilation errors, 8th attempt

* try to fix clang compilation errors, 9th attempt

* more cleanup

* fix compilation errors

* fix apple targets

* fix a typo in arm version of ggml_vec_dot_q4_K_q8_K

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
2025-06-09 16:47:13 +02:00

1480 lines
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#define GGML_COMMON_IMPL_C
#include "ggml-common.h"
#include "ggml-quants.h"
#include "ggml-impl.h"
#include "ggml-cpu.h"
#include "../../quants.h"
#include "../../ggml-cpu-impl.h"
#include <math.h>
#include <string.h>
#include <assert.h>
#include <float.h>
#include <stdlib.h> // for qsort
#include <stdio.h> // for GGML_ASSERT
#define GROUP_MAX_EPS 1e-15f
#define GROUP_MAX_EPS_IQ3_XXS 1e-8f
#define GROUP_MAX_EPS_IQ2_S 1e-8f
#define GROUP_MAX_EPS_IQ1_M 1e-7f
#define GROUP_MAX_EPS_IQ1_S 1e-12f
#define UNUSED GGML_UNUSED
#if defined(__wasm_simd128__)
#define B1(c,s,n) 0x ## n ## c , 0x ## n ## s
#define B2(c,s,n) B1(c,s,n ## c), B1(c,s,n ## s)
#define B3(c,s,n) B2(c,s,n ## c), B2(c,s,n ## s)
#define B4(c,s,n) B3(c,s,n ## c), B3(c,s,n ## s)
#define B5(c,s,n) B4(c,s,n ## c), B4(c,s,n ## s)
#define B6(c,s,n) B5(c,s,n ## c), B5(c,s,n ## s)
#define B7(c,s,n) B6(c,s,n ## c), B6(c,s,n ## s)
#define B8(c,s ) B7(c,s, c), B7(c,s, s)
// precomputed tables for expanding 8bits to 8 bytes:
static const uint64_t table_b2b_0[1 << 8] = { B8(00, 10) }; // ( b) << 4
static const uint64_t table_b2b_1[1 << 8] = { B8(10, 00) }; // (!b) << 4
#endif
void quantize_row_q8_0(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_0 * GGML_RESTRICT y = vy;
#if defined __wasm_simd128__
for (int i = 0; i < nb; i++) {
v128_t srcv [8];
v128_t asrcv[8];
v128_t amaxv[8];
for (int j = 0; j < 8; j++) srcv[j] = wasm_v128_load(x + i*32 + 4*j);
for (int j = 0; j < 8; j++) asrcv[j] = wasm_f32x4_abs(srcv[j]);
for (int j = 0; j < 4; j++) amaxv[2*j] = wasm_f32x4_max(asrcv[2*j], asrcv[2*j+1]);
for (int j = 0; j < 2; j++) amaxv[4*j] = wasm_f32x4_max(amaxv[4*j], amaxv[4*j+2]);
for (int j = 0; j < 1; j++) amaxv[8*j] = wasm_f32x4_max(amaxv[8*j], amaxv[8*j+4]);
const float amax = MAX(MAX(wasm_f32x4_extract_lane(amaxv[0], 0),
wasm_f32x4_extract_lane(amaxv[0], 1)),
MAX(wasm_f32x4_extract_lane(amaxv[0], 2),
wasm_f32x4_extract_lane(amaxv[0], 3)));
const float d = amax / ((1 << 7) - 1);
const float id = d ? 1.0f/d : 0.0f;
y[i].d = GGML_FP32_TO_FP16(d);
for (int j = 0; j < 8; j++) {
const v128_t v = wasm_f32x4_mul(srcv[j], wasm_f32x4_splat(id));
const v128_t vi = wasm_i32x4_trunc_sat_f32x4(v);
y[i].qs[4*j + 0] = wasm_i32x4_extract_lane(vi, 0);
y[i].qs[4*j + 1] = wasm_i32x4_extract_lane(vi, 1);
y[i].qs[4*j + 2] = wasm_i32x4_extract_lane(vi, 2);
y[i].qs[4*j + 3] = wasm_i32x4_extract_lane(vi, 3);
}
}
#else
GGML_UNUSED(nb);
// scalar
quantize_row_q8_0_ref(x, y, k);
#endif
}
void quantize_row_q8_1(const float * GGML_RESTRICT x, void * GGML_RESTRICT vy, int64_t k) {
assert(k % QK8_1 == 0);
const int nb = k / QK8_1;
block_q8_1 * GGML_RESTRICT y = vy;
#if defined __wasm_simd128__
for (int i = 0; i < nb; i++) {
v128_t srcv [8];
v128_t asrcv[8];
v128_t amaxv[8];
for (int j = 0; j < 8; j++) srcv[j] = wasm_v128_load(x + i*32 + 4*j);
for (int j = 0; j < 8; j++) asrcv[j] = wasm_f32x4_abs(srcv[j]);
for (int j = 0; j < 4; j++) amaxv[2*j] = wasm_f32x4_max(asrcv[2*j], asrcv[2*j+1]);
for (int j = 0; j < 2; j++) amaxv[4*j] = wasm_f32x4_max(amaxv[4*j], amaxv[4*j+2]);
for (int j = 0; j < 1; j++) amaxv[8*j] = wasm_f32x4_max(amaxv[8*j], amaxv[8*j+4]);
const float amax = MAX(MAX(wasm_f32x4_extract_lane(amaxv[0], 0),
wasm_f32x4_extract_lane(amaxv[0], 1)),
MAX(wasm_f32x4_extract_lane(amaxv[0], 2),
wasm_f32x4_extract_lane(amaxv[0], 3)));
const float d = amax / ((1 << 7) - 1);
const float id = d ? 1.0f/d : 0.0f;
y[i].d = GGML_FP32_TO_FP16(d);
v128_t accv = wasm_i32x4_splat(0);
for (int j = 0; j < 8; j++) {
const v128_t v = wasm_f32x4_mul(srcv[j], wasm_f32x4_splat(id));
const v128_t vi = wasm_i32x4_trunc_sat_f32x4(v);
y[i].qs[4*j + 0] = wasm_i32x4_extract_lane(vi, 0);
y[i].qs[4*j + 1] = wasm_i32x4_extract_lane(vi, 1);
y[i].qs[4*j + 2] = wasm_i32x4_extract_lane(vi, 2);
y[i].qs[4*j + 3] = wasm_i32x4_extract_lane(vi, 3);
accv = wasm_i32x4_add(accv, vi);
}
y[i].s = GGML_FP32_TO_FP16(
d * (wasm_i32x4_extract_lane(accv, 0) +
wasm_i32x4_extract_lane(accv, 1) +
wasm_i32x4_extract_lane(accv, 2) +
wasm_i32x4_extract_lane(accv, 3)));
}
#else
GGML_UNUSED(nb);
// scalar
quantize_row_q8_1_ref(x, y, k);
#endif
}
//===================================== Q8_K ==============================================
void quantize_row_q8_K(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k) {
#ifdef __wasm_simd128__
assert(k % QK_K == 0);
const int64_t nb = k / QK_K;
block_q8_K * GGML_RESTRICT yc = y; // Cast to proper type
for (int i = 0; i < nb; i++) {
const float * x_block = x + i * QK_K;
v128_t min_vec = wasm_v128_load(x_block);
v128_t max_vec = min_vec;
for (int j = 4; j < QK_K; j += 4) {
v128_t x_vec = wasm_v128_load(x_block + j);
max_vec = wasm_f32x4_pmax(max_vec, x_vec);
min_vec = wasm_f32x4_pmin(min_vec, x_vec);
}
max_vec = wasm_f32x4_pmax(max_vec, wasm_i32x4_shuffle(max_vec, max_vec, 2, 3, 0, 1));
max_vec = wasm_f32x4_pmax(max_vec, wasm_i32x4_shuffle(max_vec, max_vec, 1, 0, 3, 2));
min_vec = wasm_f32x4_pmin(min_vec, wasm_i32x4_shuffle(min_vec, min_vec, 2, 3, 0, 1));
min_vec = wasm_f32x4_pmin(min_vec, wasm_i32x4_shuffle(min_vec, min_vec, 1, 0, 3, 2));
float max = wasm_f32x4_extract_lane(max_vec, 0);
float min = wasm_f32x4_extract_lane(min_vec, 0);
float amax = -min > max ? min : max;
if (amax == 0.0f) {
yc[i].d = 0.0f;
const v128_t zero = wasm_i8x16_splat(0);
for (int j = 0; j < QK_K; j += 16) {
wasm_v128_store(yc[i].qs + j, zero);
}
continue;
}
const float iscale = -127.0f / amax;
const v128_t scale_vec = wasm_f32x4_splat(iscale);
// Process 16 elements per iteration
for (int j = 0, jb = 0; j < QK_K; j += 16, jb++) {
// Load and quantize 16 floats
v128_t x0 = wasm_v128_load(x_block + j);
v128_t x1 = wasm_v128_load(x_block + j + 4);
v128_t x2 = wasm_v128_load(x_block + j + 8);
v128_t x3 = wasm_v128_load(x_block + j + 12);
v128_t q0 = wasm_f32x4_nearest(wasm_f32x4_mul(x0, scale_vec));
v128_t q1 = wasm_f32x4_nearest(wasm_f32x4_mul(x1, scale_vec));
v128_t q2 = wasm_f32x4_nearest(wasm_f32x4_mul(x2, scale_vec));
v128_t q3 = wasm_f32x4_nearest(wasm_f32x4_mul(x3, scale_vec));
// Convert to i32 with saturation
v128_t i0 = wasm_i32x4_trunc_sat_f32x4(q0);
v128_t i1 = wasm_i32x4_trunc_sat_f32x4(q1);
v128_t i2 = wasm_i32x4_trunc_sat_f32x4(q2);
v128_t i3 = wasm_i32x4_trunc_sat_f32x4(q3);
// Pack into 16 i8 values
v128_t i8 = wasm_i8x16_narrow_i16x8(
wasm_i16x8_narrow_i32x4(i0, i1),
wasm_i16x8_narrow_i32x4(i2, i3)
);
wasm_v128_store(yc[i].qs + j, i8);
// Calculate bsums using SIMD
v128_t sum16 = wasm_i16x8_add(
wasm_i16x8_extend_low_i8x16(i8),
wasm_i16x8_extend_high_i8x16(i8)
);
v128_t sum32 = wasm_i32x4_add(
wasm_i32x4_extend_low_i16x8(sum16),
wasm_i32x4_extend_high_i16x8(sum16)
);
sum32 = wasm_i32x4_add(sum32, wasm_i32x4_shuffle(sum32, sum32, 2, 3, 0, 1));
sum32 = wasm_i32x4_add(sum32, wasm_i32x4_shuffle(sum32, sum32, 1, 0, 3, 2));
yc[i].bsums[jb] = wasm_i32x4_extract_lane(sum32, 0);
}
yc[i].d = 1.0f / iscale;
}
#else
quantize_row_q8_K_ref(x, y, k);
#endif
}
//===================================== Dot products =================================
void ggml_vec_dot_q4_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc) {
const int qk = QK8_0;
const int nb = n / qk;
assert(n % qk == 0);
assert(nrc == 1);
UNUSED(nrc);
UNUSED(bx);
UNUSED(by);
UNUSED(bs);
const block_q4_0 * GGML_RESTRICT x = vx;
const block_q8_0 * GGML_RESTRICT y = vy;
int ib = 0;
float sumf = 0;
#if defined __wasm_simd128__
v128_t sumv = wasm_f32x4_splat(0.0f);
const v128_t m4b = wasm_i8x16_splat(0x0F);
const v128_t s8b = wasm_i8x16_splat(0x8);
for (; ib + 1 < nb; ib += 2) {
const block_q4_0 * GGML_RESTRICT x0 = &x[ib];
const block_q4_0 * GGML_RESTRICT x1 = &x[ib + 1];
const block_q8_0 * GGML_RESTRICT y0 = &y[ib];
const block_q8_0 * GGML_RESTRICT y1 = &y[ib + 1];
// Load and process x0
v128_t v0_0 = wasm_v128_load(x0->qs);
v128_t v0_0l = wasm_v128_and(v0_0, m4b);
v128_t v0_0h = wasm_u8x16_shr(v0_0, 4);
v128_t v0_0ls = wasm_i8x16_sub(v0_0l, s8b);
v128_t v0_0hs = wasm_i8x16_sub(v0_0h, s8b);
// Load y0 vectors
v128_t y0_l = wasm_v128_load(y0->qs);
v128_t y0_h = wasm_v128_load(y0->qs + 16);
// Extend to i16x8 and compute dot products
v128_t dx0l = wasm_i16x8_extend_low_i8x16(v0_0ls);
v128_t dx0h = wasm_i16x8_extend_high_i8x16(v0_0ls);
v128_t dx0hl = wasm_i16x8_extend_low_i8x16(v0_0hs);
v128_t dx0hh = wasm_i16x8_extend_high_i8x16(v0_0hs);
v128_t dy0ll = wasm_i16x8_extend_low_i8x16(y0_l);
v128_t dy0lh = wasm_i16x8_extend_high_i8x16(y0_l);
v128_t dy0hl = wasm_i16x8_extend_low_i8x16(y0_h);
v128_t dy0hh = wasm_i16x8_extend_high_i8x16(y0_h);
v128_t dp0 = wasm_i32x4_add(
wasm_i32x4_add(
wasm_i32x4_dot_i16x8(dx0l, dy0ll),
wasm_i32x4_dot_i16x8(dx0h, dy0lh)
),
wasm_i32x4_add(
wasm_i32x4_dot_i16x8(dx0hl, dy0hl),
wasm_i32x4_dot_i16x8(dx0hh, dy0hh)
)
);
// Load and process x1
v128_t v0_1 = wasm_v128_load(x1->qs);
v128_t v0_1l = wasm_v128_and(v0_1, m4b);
v128_t v0_1h = wasm_u8x16_shr(v0_1, 4);
v128_t v0_1ls = wasm_i8x16_sub(v0_1l, s8b);
v128_t v0_1hs = wasm_i8x16_sub(v0_1h, s8b);
// Load y1 vectors
v128_t y1_l = wasm_v128_load(y1->qs);
v128_t y1_h = wasm_v128_load(y1->qs + 16);
// Extend to i16x8 and compute dot products
v128_t dx1l = wasm_i16x8_extend_low_i8x16(v0_1ls);
v128_t dx1h = wasm_i16x8_extend_high_i8x16(v0_1ls);
v128_t dx1hl = wasm_i16x8_extend_low_i8x16(v0_1hs);
v128_t dx1hh = wasm_i16x8_extend_high_i8x16(v0_1hs);
v128_t dy1ll = wasm_i16x8_extend_low_i8x16(y1_l);
v128_t dy1lh = wasm_i16x8_extend_high_i8x16(y1_l);
v128_t dy1hl = wasm_i16x8_extend_low_i8x16(y1_h);
v128_t dy1hh = wasm_i16x8_extend_high_i8x16(y1_h);
v128_t dp1 = wasm_i32x4_add(
wasm_i32x4_add(
wasm_i32x4_dot_i16x8(dx1l, dy1ll),
wasm_i32x4_dot_i16x8(dx1h, dy1lh)
),
wasm_i32x4_add(
wasm_i32x4_dot_i16x8(dx1hl, dy1hl),
wasm_i32x4_dot_i16x8(dx1hh, dy1hh)
)
);
// Accumulate results with scaling
float scale0 = GGML_FP16_TO_FP32(x0->d) * GGML_FP16_TO_FP32(y0->d);
float scale1 = GGML_FP16_TO_FP32(x1->d) * GGML_FP16_TO_FP32(y1->d);
sumv = wasm_f32x4_add(sumv, wasm_f32x4_mul(wasm_f32x4_convert_i32x4(dp0), wasm_f32x4_splat(scale0)));
sumv = wasm_f32x4_add(sumv, wasm_f32x4_mul(wasm_f32x4_convert_i32x4(dp1), wasm_f32x4_splat(scale1)));
}
sumf = wasm_f32x4_extract_lane(sumv, 0) + wasm_f32x4_extract_lane(sumv, 1) +
wasm_f32x4_extract_lane(sumv, 2) + wasm_f32x4_extract_lane(sumv, 3);
#endif
for (; ib < nb; ++ib) {
int sumi0 = 0;
int sumi1 = 0;
for (int j = 0; j < qk/2; ++j) {
const int v0 = (x[ib].qs[j] & 0x0F) - 8;
const int v1 = (x[ib].qs[j] >> 4) - 8;
sumi0 += (v0 * y[ib].qs[j]);
sumi1 += (v1 * y[ib].qs[j + qk/2]);
}
int sumi = sumi0 + sumi1;
sumf += sumi*GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d);
}
*s = sumf;
}
void ggml_vec_dot_q5_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc) {
const int qk = QK8_0;
const int nb = n / qk;
int ib = 0;
float sumf = 0;
assert(n % qk == 0);
assert(qk == QK5_0);
assert(nrc == 1);
UNUSED(nrc);
UNUSED(bx);
UNUSED(by);
UNUSED(bs);
const block_q5_0 * GGML_RESTRICT x = vx;
const block_q8_0 * GGML_RESTRICT y = vy;
#if defined __wasm_simd128__
v128_t sumv = wasm_f32x4_splat(0.0f);
uint32_t qh_;
uint64_t tmp[4];
// TODO: check if unrolling this is better
for (; ib < nb; ++ib) {
const block_q5_0 * GGML_RESTRICT x0 = &x[ib];
const block_q8_0 * GGML_RESTRICT y0 = &y[ib];
const v128_t m4b = wasm_i8x16_splat(0x0F);
// extract the 5th bit
memcpy(&qh_, x0->qh, sizeof(qh_));
tmp[0] = table_b2b_1[(qh_ >> 0) & 0xFF];
tmp[1] = table_b2b_1[(qh_ >> 8) & 0xFF];
tmp[2] = table_b2b_1[(qh_ >> 16) & 0xFF];
tmp[3] = table_b2b_1[(qh_ >> 24) ];
const v128_t qhl = wasm_v128_load(tmp + 0);
const v128_t qhh = wasm_v128_load(tmp + 2);
const v128_t v0 = wasm_v128_load(x0->qs);
// 4-bit -> 8-bit
const v128_t v0l = wasm_v128_and (v0, m4b);
const v128_t v0h = wasm_u8x16_shr(v0, 4);
// add high bit and sub 16 (equivalent to sub 0x10 when bit is zero)
const v128_t v0lf = wasm_i8x16_sub(v0l, qhl);
const v128_t v0hf = wasm_i8x16_sub(v0h, qhh);
// load y
const v128_t v1l = wasm_v128_load(y0->qs);
const v128_t v1h = wasm_v128_load(y0->qs + 16);
// int8x16 -> int16x8
const v128_t v0lfl = wasm_i16x8_extend_low_i8x16 (v0lf);
const v128_t v0lfh = wasm_i16x8_extend_high_i8x16(v0lf);
const v128_t v0hfl = wasm_i16x8_extend_low_i8x16 (v0hf);
const v128_t v0hfh = wasm_i16x8_extend_high_i8x16(v0hf);
const v128_t v1ll = wasm_i16x8_extend_low_i8x16 (v1l);
const v128_t v1lh = wasm_i16x8_extend_high_i8x16(v1l);
const v128_t v1hl = wasm_i16x8_extend_low_i8x16 (v1h);
const v128_t v1hh = wasm_i16x8_extend_high_i8x16(v1h);
// dot product
sumv = wasm_f32x4_add(sumv, wasm_f32x4_mul(wasm_f32x4_convert_i32x4(
wasm_i32x4_add(
wasm_i32x4_add(wasm_i32x4_dot_i16x8(v0lfl, v1ll),
wasm_i32x4_dot_i16x8(v0lfh, v1lh)),
wasm_i32x4_add(wasm_i32x4_dot_i16x8(v0hfl, v1hl),
wasm_i32x4_dot_i16x8(v0hfh, v1hh)))),
wasm_f32x4_splat(GGML_FP16_TO_FP32(x0->d) * GGML_FP16_TO_FP32(y0->d))));
}
sumf = wasm_f32x4_extract_lane(sumv, 0) + wasm_f32x4_extract_lane(sumv, 1) +
wasm_f32x4_extract_lane(sumv, 2) + wasm_f32x4_extract_lane(sumv, 3);
#endif
for (; ib < nb; ++ib) {
uint32_t qh;
memcpy(&qh, x[ib].qh, sizeof(qh));
int sumi0 = 0;
int sumi1 = 0;
for (int j = 0; j < qk/2; ++j) {
const uint8_t xh_0 = ((qh & (1u << (j + 0 ))) >> (j + 0 )) << 4;
const uint8_t xh_1 = ((qh & (1u << (j + 16))) >> (j + 12));
const int32_t x0 = (int8_t)(((x[ib].qs[j] & 0x0F) | xh_0) - 16);
const int32_t x1 = (int8_t)(((x[ib].qs[j] >> 4) | xh_1) - 16);
sumi0 += (x0 * y[ib].qs[j]);
sumi1 += (x1 * y[ib].qs[j + qk/2]);
}
int sumi = sumi0 + sumi1;
sumf += (GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d)) * sumi;
}
*s = sumf;
}
void ggml_vec_dot_q5_1_q8_1(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc) {
const int qk = QK8_1;
const int nb = n / qk;
int ib = 0;
float sumf = 0;
assert(n % qk == 0);
assert(qk == QK5_1);
assert(nrc == 1);
UNUSED(nrc);
UNUSED(bx);
UNUSED(by);
UNUSED(bs);
const block_q5_1 * GGML_RESTRICT x = vx;
const block_q8_1 * GGML_RESTRICT y = vy;
#if defined __wasm_simd128__
v128_t sumv = wasm_f32x4_splat(0.0f);
float summs = 0.0f;
uint32_t qh_;
uint64_t tmp[4];
// TODO: check if unrolling this is better
for (; ib < nb; ++ib) {
const block_q5_1 * GGML_RESTRICT x0 = &x[ib];
const block_q8_1 * GGML_RESTRICT y0 = &y[ib];
summs += GGML_FP16_TO_FP32(x0->m) * GGML_FP16_TO_FP32(y0->s);
const v128_t m4b = wasm_i8x16_splat(0x0F);
// extract the 5th bit
memcpy(&qh_, x0->qh, sizeof(qh_));
tmp[0] = table_b2b_0[(qh_ >> 0) & 0xFF];
tmp[1] = table_b2b_0[(qh_ >> 8) & 0xFF];
tmp[2] = table_b2b_0[(qh_ >> 16) & 0xFF];
tmp[3] = table_b2b_0[(qh_ >> 24) ];
const v128_t qhl = wasm_v128_load(tmp + 0);
const v128_t qhh = wasm_v128_load(tmp + 2);
const v128_t v0 = wasm_v128_load(x0->qs);
// 4-bit -> 8-bit
const v128_t v0l = wasm_v128_and (v0, m4b);
const v128_t v0h = wasm_u8x16_shr(v0, 4);
// add high bit
const v128_t v0lf = wasm_v128_or(v0l, qhl);
const v128_t v0hf = wasm_v128_or(v0h, qhh);
// load y
const v128_t v1l = wasm_v128_load(y0->qs);
const v128_t v1h = wasm_v128_load(y0->qs + 16);
// int8x16 -> int16x8
const v128_t v0lfl = wasm_i16x8_extend_low_i8x16 (v0lf);
const v128_t v0lfh = wasm_i16x8_extend_high_i8x16(v0lf);
const v128_t v0hfl = wasm_i16x8_extend_low_i8x16 (v0hf);
const v128_t v0hfh = wasm_i16x8_extend_high_i8x16(v0hf);
const v128_t v1ll = wasm_i16x8_extend_low_i8x16 (v1l);
const v128_t v1lh = wasm_i16x8_extend_high_i8x16(v1l);
const v128_t v1hl = wasm_i16x8_extend_low_i8x16 (v1h);
const v128_t v1hh = wasm_i16x8_extend_high_i8x16(v1h);
// dot product
sumv = wasm_f32x4_add(sumv,
wasm_f32x4_mul(wasm_f32x4_convert_i32x4(wasm_i32x4_add(
wasm_i32x4_add(wasm_i32x4_dot_i16x8(v0lfl, v1ll),
wasm_i32x4_dot_i16x8(v0lfh, v1lh)),
wasm_i32x4_add(wasm_i32x4_dot_i16x8(v0hfl, v1hl),
wasm_i32x4_dot_i16x8(v0hfh, v1hh)))),
wasm_f32x4_splat(GGML_FP16_TO_FP32(x0->d) * GGML_FP16_TO_FP32(y0->d))));
}
sumf = wasm_f32x4_extract_lane(sumv, 0) + wasm_f32x4_extract_lane(sumv, 1) +
wasm_f32x4_extract_lane(sumv, 2) + wasm_f32x4_extract_lane(sumv, 3) + summs;
#endif
for (; ib < nb; ++ib) {
uint32_t qh;
memcpy(&qh, x[ib].qh, sizeof(qh));
int sumi0 = 0;
int sumi1 = 0;
for (int j = 0; j < qk/2; ++j) {
const uint8_t xh_0 = ((qh >> (j + 0)) << 4) & 0x10;
const uint8_t xh_1 = ((qh >> (j + 12)) ) & 0x10;
const int32_t x0 = (x[ib].qs[j] & 0xF) | xh_0;
const int32_t x1 = (x[ib].qs[j] >> 4) | xh_1;
sumi0 += (x0 * y[ib].qs[j]);
sumi1 += (x1 * y[ib].qs[j + qk/2]);
}
int sumi = sumi0 + sumi1;
sumf += (GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d))*sumi + GGML_FP16_TO_FP32(x[ib].m)*GGML_FP16_TO_FP32(y[ib].s);
}
*s = sumf;
}
void ggml_vec_dot_q8_0_q8_0(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc) {
const int qk = QK8_0;
const int nb = n / qk;
assert(n % qk == 0);
assert(nrc == 1);
UNUSED(nrc);
UNUSED(bx);
UNUSED(by);
UNUSED(bs);
const block_q8_0 * GGML_RESTRICT x = vx;
const block_q8_0 * GGML_RESTRICT y = vy;
int ib = 0;
float sumf = 0;
#if defined __wasm_simd128__
v128_t sumv = wasm_f32x4_splat(0.0f);
for (; ib < nb; ++ib) {
const block_q8_0 * GGML_RESTRICT x0 = &x[ib];
const block_q8_0 * GGML_RESTRICT y0 = &y[ib];
const v128_t x0_0 = wasm_v128_load(x0->qs);
const v128_t x0_1 = wasm_v128_load(x0->qs + 16);
const v128_t y0_0 = wasm_v128_load(y0->qs);
const v128_t y0_1 = wasm_v128_load(y0->qs + 16);
// Extend 8-bit to 16-bit
const v128_t x0_0l = wasm_i16x8_extend_low_i8x16(x0_0);
const v128_t x0_0h = wasm_i16x8_extend_high_i8x16(x0_0);
const v128_t x0_1l = wasm_i16x8_extend_low_i8x16(x0_1);
const v128_t x0_1h = wasm_i16x8_extend_high_i8x16(x0_1);
const v128_t y0_0l = wasm_i16x8_extend_low_i8x16(y0_0);
const v128_t y0_0h = wasm_i16x8_extend_high_i8x16(y0_0);
const v128_t y0_1l = wasm_i16x8_extend_low_i8x16(y0_1);
const v128_t y0_1h = wasm_i16x8_extend_high_i8x16(y0_1);
// Compute dot products
const v128_t dx0_0 = wasm_i32x4_dot_i16x8(x0_0l, y0_0l);
const v128_t dx0_1 = wasm_i32x4_dot_i16x8(x0_0h, y0_0h);
const v128_t dx1_0 = wasm_i32x4_dot_i16x8(x0_1l, y0_1l);
const v128_t dx1_1 = wasm_i32x4_dot_i16x8(x0_1h, y0_1h);
// Sum all dot products
const v128_t sum_dots = wasm_i32x4_add(wasm_i32x4_add(dx0_0, dx0_1), wasm_i32x4_add(dx1_0, dx1_1));
// Convert to float and accumulate
const float scale = GGML_FP16_TO_FP32(x0->d) * GGML_FP16_TO_FP32(y0->d);
sumv = wasm_f32x4_add(sumv, wasm_f32x4_mul(wasm_f32x4_convert_i32x4(sum_dots), wasm_f32x4_splat(scale)));
}
sumf = wasm_f32x4_extract_lane(sumv, 0) + wasm_f32x4_extract_lane(sumv, 1) +
wasm_f32x4_extract_lane(sumv, 2) + wasm_f32x4_extract_lane(sumv, 3);
#endif
for (; ib < nb; ++ib) {
int sumi = 0;
for (int j = 0; j < qk; j++) {
sumi += x[ib].qs[j]*y[ib].qs[j];
}
sumf += sumi*(GGML_FP16_TO_FP32(x[ib].d)*GGML_FP16_TO_FP32(y[ib].d));
}
*s = sumf;
}
void ggml_vec_dot_q2_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc) {
assert(nrc == 1);
UNUSED(nrc);
UNUSED(bx);
UNUSED(by);
UNUSED(bs);
const block_q2_K * GGML_RESTRICT x = vx;
const block_q8_K * GGML_RESTRICT y = vy;
const int nb = n / QK_K;
#if defined __wasm_simd128__
float sumf = 0;
for (int i = 0; i < nb; ++i) {
const uint8_t * q2 = x[i].qs;
const int8_t * q8 = y[i].qs;
const uint8_t * sc = x[i].scales;
// Vectorized summs calculation
v128_t summs_vec = wasm_i32x4_splat(0);
{
v128_t sc_vec = wasm_v128_load(sc);
v128_t sc_upper = wasm_u8x16_shr(sc_vec, 4);
v128_t sc_low = wasm_u16x8_extend_low_u8x16(sc_upper);
v128_t sc_high = wasm_u16x8_extend_high_u8x16(sc_upper);
v128_t bsums1 = wasm_v128_load(&y[i].bsums[0]);
v128_t bsums2 = wasm_v128_load(&y[i].bsums[8]);
summs_vec = wasm_i32x4_add(
wasm_i32x4_add(wasm_i32x4_dot_i16x8(sc_low, bsums1),
wasm_i32x4_dot_i16x8(sc_high, bsums2)),
summs_vec
);
summs_vec = wasm_i32x4_add(summs_vec, wasm_i32x4_shuffle(summs_vec, summs_vec, 2, 3, 0, 1));
summs_vec = wasm_i32x4_add(summs_vec, wasm_i32x4_shuffle(summs_vec, summs_vec, 1, 0, 3, 2));
}
int32_t summs = wasm_i32x4_extract_lane(summs_vec, 0);
// Vectorized isum calculation
int32_t isum = 0;
const uint8_t * sc_ptr = sc;
const int k_iters = QK_K/128;
for (int k = 0; k < k_iters; ++k) {
v128_t isum_vec = wasm_i32x4_splat(0);
int shift = 0;
for (int j = 0; j < 4; ++j) {
const int d0 = (sc_ptr[0] & 0xF);
const int d1 = (sc_ptr[1] & 0xF);
sc_ptr += 2;
// Process first 16 elements
v128_t q2_0 = wasm_v128_load(q2);
v128_t q8_0 = wasm_v128_load(q8);
v128_t q2_shift_0 = wasm_u8x16_shr(q2_0, shift);
v128_t q2_bits_0 = wasm_v128_and(q2_shift_0, wasm_i8x16_splat(0x03));
// Process next 16 elements
v128_t q2_1 = wasm_v128_load(q2 + 16);
v128_t q8_1 = wasm_v128_load(q8 + 16);
v128_t q2_shift_1 = wasm_u8x16_shr(q2_1, shift);
v128_t q2_bits_1 = wasm_v128_and(q2_shift_1, wasm_i8x16_splat(0x03));
// Calculate dot products
v128_t p0 = wasm_i32x4_dot_i16x8(
wasm_i16x8_extend_low_i8x16(q8_0),
wasm_i16x8_extend_low_i8x16(q2_bits_0)
);
v128_t p1 = wasm_i32x4_dot_i16x8(
wasm_i16x8_extend_high_i8x16(q8_0),
wasm_i16x8_extend_high_i8x16(q2_bits_0)
);
v128_t p2 = wasm_i32x4_dot_i16x8(
wasm_i16x8_extend_low_i8x16(q8_1),
wasm_i16x8_extend_low_i8x16(q2_bits_1)
);
v128_t p3 = wasm_i32x4_dot_i16x8(
wasm_i16x8_extend_high_i8x16(q8_1),
wasm_i16x8_extend_high_i8x16(q2_bits_1)
);
// Accumulate scaled results
v128_t scaled = wasm_i32x4_add(
wasm_i32x4_mul(wasm_i32x4_add(p0, p1), wasm_i32x4_splat(d0)),
wasm_i32x4_mul(wasm_i32x4_add(p2, p3), wasm_i32x4_splat(d1))
);
isum_vec = wasm_i32x4_add(isum_vec, scaled);
q8 += 32;
shift += 2;
}
q2 += 32;
// Horizontal sum of isum_vec
isum_vec = wasm_i32x4_add(isum_vec, wasm_i32x4_shuffle(isum_vec, isum_vec, 2, 3, 0, 1));
isum_vec = wasm_i32x4_add(isum_vec, wasm_i32x4_shuffle(isum_vec, isum_vec, 1, 0, 3, 2));
isum += wasm_i32x4_extract_lane(isum_vec, 0);
}
const float dall = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const float dmin = GGML_FP16_TO_FP32(x[i].dmin) * y[i].d;
sumf += dall * isum - dmin * summs;
}
*s = sumf;
#else
float sumf = 0;
for (int i = 0; i < nb; ++i) {
const uint8_t * q2 = x[i].qs;
const int8_t * q8 = y[i].qs;
const uint8_t * sc = x[i].scales;
int summs = 0;
for (int j = 0; j < 16; ++j) {
summs += y[i].bsums[j] * (sc[j] >> 4);
}
const float dall = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_FP16_TO_FP32(x[i].dmin);
int isum = 0;
int is = 0;
int d;
for (int k = 0; k < QK_K/128; ++k) {
int shift = 0;
for (int j = 0; j < 4; ++j) {
d = sc[is++] & 0xF;
int isuml = 0;
for (int l = 0; l < 16; ++l) isuml += q8[l] * ((q2[l] >> shift) & 3);
isum += d * isuml;
d = sc[is++] & 0xF;
isuml = 0;
for (int l = 16; l < 32; ++l) isuml += q8[l] * ((q2[l] >> shift) & 3);
isum += d * isuml;
shift += 2;
q8 += 32;
}
q2 += 32;
}
sumf += dall * isum - dmin * summs;
}
*s = sumf;
#endif
}
void ggml_vec_dot_q3_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc) {
assert(n % QK_K == 0);
assert(nrc == 1);
UNUSED(nrc);
UNUSED(bx);
UNUSED(by);
UNUSED(bs);
const uint32_t kmask1 = 0x03030303;
const uint32_t kmask2 = 0x0f0f0f0f;
const block_q3_K * GGML_RESTRICT x = vx;
const block_q8_K * GGML_RESTRICT y = vy;
const int nb = n / QK_K;
#if defined __wasm_simd128__
int8_t aux8[QK_K];
float sums[8] = {0};
uint32_t auxs[4];
float sumf = 0;
for (int i = 0; i < nb; ++i) {
const uint8_t * GGML_RESTRICT q3 = x[i].qs;
const uint8_t * GGML_RESTRICT hm = x[i].hmask;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
// Process blocks with SIMD
int8_t * a = aux8;
uint8_t m = 1;
for (int j = 0; j < QK_K; j += 128) {
for (int shift = 0; shift <= 6; shift += 2) {
v128_t v_m = wasm_i8x16_splat(m);
for (int l = 0; l < 32; l += 16) {
v128_t v_q3 = wasm_v128_load(q3 + l);
v128_t v_shift = wasm_i8x16_shr(v_q3, shift);
v128_t v_low2 = wasm_v128_and(v_shift, wasm_i8x16_splat(0x03));
v128_t v_hm = wasm_v128_load(hm + l);
v128_t v_mask = wasm_v128_and(v_hm, v_m);
v_mask = wasm_i8x16_ne(v_mask, wasm_i8x16_splat(0));
v_low2 = wasm_i8x16_sub(v_low2, wasm_v128_and(wasm_i8x16_splat(4), wasm_v128_not(v_mask)));
wasm_v128_store(a + l, v_low2);
}
a += 32;
m <<= 1;
}
q3 += 32;
}
// Extract scales
memcpy(auxs, x[i].scales, 12);
uint32_t tmp = auxs[2];
auxs[2] = ((auxs[0] >> 4) & kmask2) | (((tmp >> 4) & kmask1) << 4);
auxs[3] = ((auxs[1] >> 4) & kmask2) | (((tmp >> 6) & kmask1) << 4);
auxs[0] = (auxs[0] & kmask2) | (((tmp >> 0) & kmask1) << 4);
auxs[1] = (auxs[1] & kmask2) | (((tmp >> 2) & kmask1) << 4);
const int8_t * scales = (const int8_t *)auxs;
// SIMD dot product with register accumulators
v128_t v_acc0 = wasm_i32x4_splat(0);
v128_t v_acc1 = wasm_i32x4_splat(0);
a = aux8;
for (int j = 0; j < QK_K/16; ++j) {
const v128_t v_scale = wasm_i16x8_splat(scales[j] - 32);
// Process 16 elements per iteration
for (int k = 0; k < 2; ++k) {
const v128_t v_q8 = wasm_i16x8_load8x8(q8);
const v128_t v_a = wasm_i16x8_load8x8(a);
v128_t v_prod = wasm_i16x8_mul(v_q8, v_a);
v_prod = wasm_i16x8_mul(v_prod, v_scale);
v_acc0 = wasm_i32x4_add(v_acc0, wasm_i32x4_extend_low_i16x8(v_prod));
v_acc1 = wasm_i32x4_add(v_acc1, wasm_i32x4_extend_high_i16x8(v_prod));
q8 += 8;
a += 8;
}
}
// Accumulate results
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
const v128_t v_d = wasm_f32x4_splat(d);
v128_t v_sum = wasm_f32x4_add(
wasm_f32x4_mul(wasm_f32x4_convert_i32x4(v_acc0), v_d),
wasm_f32x4_mul(wasm_f32x4_convert_i32x4(v_acc1), v_d)
);
// Accumulate into sums vector
wasm_v128_store(sums, wasm_f32x4_add(wasm_v128_load(sums), v_sum));
}
// Horizontal sum
v128_t v_sum = wasm_f32x4_add(wasm_v128_load(sums), wasm_v128_load(sums + 4));
sumf = wasm_f32x4_extract_lane(v_sum, 0) +
wasm_f32x4_extract_lane(v_sum, 1) +
wasm_f32x4_extract_lane(v_sum, 2) +
wasm_f32x4_extract_lane(v_sum, 3);
*s = sumf;
#else
// scalar version
// This function is written like this so the compiler can manage to vectorize most of it
// Using -Ofast, GCC and clang manage to produce code that is within a factor of 2 or so from the
// manually vectorized version above. Every other version I tried would run at least 4 times slower.
// The ideal situation would be if we could just write the code once, and the compiler would
// automatically produce the best possible set of machine instructions, instead of us having to manually
// write vectorized versions for AVX, ARM_NEON, etc.
int8_t aux8[QK_K];
int16_t aux16[8];
float sums [8];
int32_t aux32[8];
memset(sums, 0, 8*sizeof(float));
uint32_t auxs[4];
const int8_t * scales = (const int8_t*)auxs;
float sumf = 0;
for (int i = 0; i < nb; ++i) {
const uint8_t * GGML_RESTRICT q3 = x[i].qs;
const uint8_t * GGML_RESTRICT hm = x[i].hmask;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
memset(aux32, 0, 8*sizeof(int32_t));
int8_t * GGML_RESTRICT a = aux8;
uint8_t m = 1;
for (int j = 0; j < QK_K; j += 128) {
for (int l = 0; l < 32; ++l) a[l] = q3[l] & 3;
for (int l = 0; l < 32; ++l) a[l] -= (hm[l] & m ? 0 : 4);
a += 32; m <<= 1;
for (int l = 0; l < 32; ++l) a[l] = (q3[l] >> 2) & 3;
for (int l = 0; l < 32; ++l) a[l] -= (hm[l] & m ? 0 : 4);
a += 32; m <<= 1;
for (int l = 0; l < 32; ++l) a[l] = (q3[l] >> 4) & 3;
for (int l = 0; l < 32; ++l) a[l] -= (hm[l] & m ? 0 : 4);
a += 32; m <<= 1;
for (int l = 0; l < 32; ++l) a[l] = (q3[l] >> 6) & 3;
for (int l = 0; l < 32; ++l) a[l] -= (hm[l] & m ? 0 : 4);
a += 32; m <<= 1;
q3 += 32;
}
a = aux8;
memcpy(auxs, x[i].scales, 12);
uint32_t tmp = auxs[2];
auxs[2] = ((auxs[0] >> 4) & kmask2) | (((tmp >> 4) & kmask1) << 4);
auxs[3] = ((auxs[1] >> 4) & kmask2) | (((tmp >> 6) & kmask1) << 4);
auxs[0] = (auxs[0] & kmask2) | (((tmp >> 0) & kmask1) << 4);
auxs[1] = (auxs[1] & kmask2) | (((tmp >> 2) & kmask1) << 4);
for (int j = 0; j < QK_K/16; ++j) {
for (int l = 0; l < 8; ++l) aux16[l] = q8[l] * a[l];
for (int l = 0; l < 8; ++l) aux32[l] += (scales[j] - 32) * aux16[l];
q8 += 8; a += 8;
for (int l = 0; l < 8; ++l) aux16[l] = q8[l] * a[l];
for (int l = 0; l < 8; ++l) aux32[l] += (scales[j] - 32) * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
*s = sumf;
#endif
}
void ggml_vec_dot_q4_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc) {
assert(n % QK_K == 0);
assert(nrc == 1);
UNUSED(nrc);
UNUSED(bx);
UNUSED(by);
UNUSED(bs);
const block_q4_K * GGML_RESTRICT x = vx;
const block_q8_K * GGML_RESTRICT y = vy;
const int nb = n / QK_K;
static const uint32_t kmask1 = 0x3f3f3f3f;
static const uint32_t kmask2 = 0x0f0f0f0f;
static const uint32_t kmask3 = 0x03030303;
uint32_t utmp[4];
#if defined __wasm_simd128__
const uint8_t * scales = (const uint8_t*)&utmp[0];
float sumf = 0;
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_FP16_TO_FP32(x[i].dmin); // Corrected sign
const uint8_t * GGML_RESTRICT q4 = x[i].qs;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
// Process scales and mins
memcpy(utmp, x[i].scales, 12);
utmp[3] = ((utmp[2] >> 4) & kmask2) | (((utmp[1] >> 6) & kmask3) << 4);
const uint32_t uaux = utmp[1] & kmask1;
utmp[1] = (utmp[2] & kmask2) | (((utmp[0] >> 6) & kmask3) << 4);
utmp[2] = uaux;
utmp[0] &= kmask1;
// Sum mins * q8sums
int32_t sumi = 0;
const int16_t * GGML_RESTRICT q8sums = y[i].bsums;
const uint8_t * m = (const uint8_t *)&utmp[2];
for (int j = 0; j < 16; j += 2) {
sumi += (q8sums[j] + q8sums[j+1]) * m[j/2];
}
sumf -= dmin * sumi;
int32_t sumi1 = 0;
int32_t sumi2 = 0;
for (int j = 0; j < QK_K/64; ++j) {
// Load 64 4-bit weights (32 bytes)
const v128_t q4x0 = wasm_v128_load(q4);
const v128_t q4x1 = wasm_v128_load(q4 + 16);
q4 += 32;
// Split into low/high nibbles
const v128_t q4l0 = wasm_v128_and(q4x0, wasm_i8x16_splat(0x0F));
const v128_t q4h0 = wasm_u8x16_shr(q4x0, 4);
const v128_t q4l1 = wasm_v128_and(q4x1, wasm_i8x16_splat(0x0F));
const v128_t q4h1 = wasm_u8x16_shr(q4x1, 4);
// Load 64 8-bit values (64 bytes)
const v128_t q8x0 = wasm_v128_load(q8);
const v128_t q8x1 = wasm_v128_load(q8 + 16);
const v128_t q8x2 = wasm_v128_load(q8 + 32);
const v128_t q8x3 = wasm_v128_load(q8 + 48);
q8 += 64;
// Low nibble products
v128_t vacc1 = wasm_i32x4_dot_i16x8(
wasm_i16x8_extend_low_i8x16(q4l0),
wasm_i16x8_extend_low_i8x16(q8x0)
);
vacc1 = wasm_i32x4_add(vacc1, wasm_i32x4_dot_i16x8(
wasm_i16x8_extend_high_i8x16(q4l0),
wasm_i16x8_extend_high_i8x16(q8x0)
));
vacc1 = wasm_i32x4_add(vacc1, wasm_i32x4_dot_i16x8(
wasm_i16x8_extend_low_i8x16(q4l1),
wasm_i16x8_extend_low_i8x16(q8x1)
));
vacc1 = wasm_i32x4_add(vacc1, wasm_i32x4_dot_i16x8(
wasm_i16x8_extend_high_i8x16(q4l1),
wasm_i16x8_extend_high_i8x16(q8x1)
));
// High nibble products
v128_t vacc2 = wasm_i32x4_dot_i16x8(
wasm_i16x8_extend_low_i8x16(q4h0),
wasm_i16x8_extend_low_i8x16(q8x2)
);
vacc2 = wasm_i32x4_add(vacc2, wasm_i32x4_dot_i16x8(
wasm_i16x8_extend_high_i8x16(q4h0),
wasm_i16x8_extend_high_i8x16(q8x2)
));
vacc2 = wasm_i32x4_add(vacc2, wasm_i32x4_dot_i16x8(
wasm_i16x8_extend_low_i8x16(q4h1),
wasm_i16x8_extend_low_i8x16(q8x3)
));
vacc2 = wasm_i32x4_add(vacc2, wasm_i32x4_dot_i16x8(
wasm_i16x8_extend_high_i8x16(q4h1),
wasm_i16x8_extend_high_i8x16(q8x3)
));
// Accumulate scaled results
int32_t vacc1_sum = wasm_i32x4_extract_lane(vacc1, 0) + wasm_i32x4_extract_lane(vacc1, 1) +
wasm_i32x4_extract_lane(vacc1, 2) + wasm_i32x4_extract_lane(vacc1, 3);
sumi1 += vacc1_sum * scales[2*j];
int32_t vacc2_sum = wasm_i32x4_extract_lane(vacc2, 0) + wasm_i32x4_extract_lane(vacc2, 1) +
wasm_i32x4_extract_lane(vacc2, 2) + wasm_i32x4_extract_lane(vacc2, 3);
sumi2 += vacc2_sum * scales[2*j+1];
}
sumf += d * (sumi1 + sumi2);
}
*s = sumf;
#else
const uint8_t * scales = (const uint8_t*)&utmp[0];
const uint8_t * mins = (const uint8_t*)&utmp[2];
int8_t aux8[QK_K];
int16_t aux16[8];
float sums [8];
int32_t aux32[8];
memset(sums, 0, 8*sizeof(float));
float sumf = 0;
for (int i = 0; i < nb; ++i) {
const uint8_t * GGML_RESTRICT q4 = x[i].qs;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
memset(aux32, 0, 8*sizeof(int32_t));
int8_t * GGML_RESTRICT a = aux8;
for (int j = 0; j < QK_K/64; ++j) {
for (int l = 0; l < 32; ++l) a[l] = (int8_t)(q4[l] & 0xF);
a += 32;
for (int l = 0; l < 32; ++l) a[l] = (int8_t)(q4[l] >> 4);
a += 32; q4 += 32;
}
memcpy(utmp, x[i].scales, 12);
utmp[3] = ((utmp[2] >> 4) & kmask2) | (((utmp[1] >> 6) & kmask3) << 4);
const uint32_t uaux = utmp[1] & kmask1;
utmp[1] = (utmp[2] & kmask2) | (((utmp[0] >> 6) & kmask3) << 4);
utmp[2] = uaux;
utmp[0] &= kmask1;
int sumi = 0;
for (int j = 0; j < QK_K/16; ++j) sumi += y[i].bsums[j] * mins[j/2];
a = aux8;
int is = 0;
for (int j = 0; j < QK_K/32; ++j) {
int32_t scale = scales[is++];
for (int l = 0; l < 8; ++l) aux16[l] = q8[l] * a[l];
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
for (int l = 0; l < 8; ++l) aux16[l] = q8[l] * a[l];
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
for (int l = 0; l < 8; ++l) aux16[l] = q8[l] * a[l];
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
for (int l = 0; l < 8; ++l) aux16[l] = q8[l] * a[l];
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
const float dmin = GGML_FP16_TO_FP32(x[i].dmin) * y[i].d;
sumf -= dmin * sumi;
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
*s = sumf;
#endif
}
void ggml_vec_dot_q5_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc) {
assert(n % QK_K == 0);
assert(nrc == 1);
UNUSED(nrc);
UNUSED(bx);
UNUSED(by);
UNUSED(bs);
const block_q5_K * GGML_RESTRICT x = vx;
const block_q8_K * GGML_RESTRICT y = vy;
const int nb = n / QK_K;
static const uint32_t kmask1 = 0x3f3f3f3f;
static const uint32_t kmask2 = 0x0f0f0f0f;
static const uint32_t kmask3 = 0x03030303;
uint32_t utmp[4];
#if defined __wasm_simd128__
//const uint8_t * scales = (const uint8_t*)&utmp[0];
float sumf = 0;
for (int i = 0; i < nb; ++i) {
const float d = y[i].d * GGML_FP16_TO_FP32(x[i].d);
const float dmin = y[i].d * GGML_FP16_TO_FP32(x[i].dmin); // Fixed sign
const uint8_t * GGML_RESTRICT q5 = x[i].qs;
const uint8_t * GGML_RESTRICT qh = x[i].qh;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
// Process scales and mins
memcpy(utmp, x[i].scales, 12);
utmp[3] = ((utmp[2] >> 4) & kmask2) | (((utmp[1] >> 6) & kmask3) << 4);
const uint32_t uaux = utmp[1] & kmask1;
utmp[1] = (utmp[2] & kmask2) | (((utmp[0] >> 6) & kmask3) << 4);
utmp[2] = uaux;
utmp[0] &= kmask1;
// Sum mins * q8sums
int32_t sumi_mins = 0;
const int16_t * GGML_RESTRICT q8sums = y[i].bsums;
const uint8_t * m = (const uint8_t *)&utmp[2];
for (int j = 0; j < 16; j += 2) {
sumi_mins += (q8sums[j] + q8sums[j+1]) * m[j/2];
}
sumf -= dmin * sumi_mins; // Correct subtraction
v128_t qh0 = wasm_v128_load(qh);
v128_t qh1 = wasm_v128_load(qh + 16);
const uint8_t * sc = (const uint8_t *)utmp;
int32_t sumi = 0;
for (int j = 0; j < QK_K/64; ++j) {
const int shift = j * 2;
v128_t qh_shift0 = wasm_u8x16_shr(qh0, shift);
v128_t qh_shift1 = wasm_u8x16_shr(qh1, shift);
v128_t qh_low0 = wasm_i8x16_shl(wasm_v128_and(qh_shift0, wasm_i8x16_splat(0x01)), 4);
v128_t qh_high0 = wasm_i8x16_shl(wasm_v128_and(qh_shift0, wasm_i8x16_splat(0x02)), 3);
v128_t qh_low1 = wasm_i8x16_shl(wasm_v128_and(qh_shift1, wasm_i8x16_splat(0x01)), 4);
v128_t qh_high1 = wasm_i8x16_shl(wasm_v128_and(qh_shift1, wasm_i8x16_splat(0x02)), 3);
v128_t q5_0 = wasm_v128_load(q5);
v128_t q5_1 = wasm_v128_load(q5 + 16);
q5 += 32;
v128_t q5l_0 = wasm_v128_or(wasm_v128_and(q5_0, wasm_i8x16_splat(0x0F)), qh_low0);
v128_t q5h_0 = wasm_v128_or(wasm_u8x16_shr(q5_0, 4), qh_high0);
v128_t q5l_1 = wasm_v128_or(wasm_v128_and(q5_1, wasm_i8x16_splat(0x0F)), qh_low1);
v128_t q5h_1 = wasm_v128_or(wasm_u8x16_shr(q5_1, 4), qh_high1);
v128_t q8_0 = wasm_v128_load(q8);
v128_t q8_1 = wasm_v128_load(q8 + 16);
v128_t q8_2 = wasm_v128_load(q8 + 32);
v128_t q8_3 = wasm_v128_load(q8 + 48);
q8 += 64;
// Process low quants
v128_t pl0 = wasm_i32x4_dot_i16x8(
wasm_i16x8_extend_low_i8x16(q5l_0),
wasm_i16x8_extend_low_i8x16(q8_0)
);
pl0 = wasm_i32x4_add(pl0, wasm_i32x4_dot_i16x8(
wasm_i16x8_extend_high_i8x16(q5l_0),
wasm_i16x8_extend_high_i8x16(q8_0)
));
v128_t pl1 = wasm_i32x4_dot_i16x8(
wasm_i16x8_extend_low_i8x16(q5l_1),
wasm_i16x8_extend_low_i8x16(q8_1)
);
pl1 = wasm_i32x4_add(pl1, wasm_i32x4_dot_i16x8(
wasm_i16x8_extend_high_i8x16(q5l_1),
wasm_i16x8_extend_high_i8x16(q8_1)
));
v128_t sum_low = wasm_i32x4_add(pl0, pl1);
// Process high quants
v128_t ph0 = wasm_i32x4_dot_i16x8(
wasm_i16x8_extend_low_i8x16(q5h_0),
wasm_i16x8_extend_low_i8x16(q8_2)
);
ph0 = wasm_i32x4_add(ph0, wasm_i32x4_dot_i16x8(
wasm_i16x8_extend_high_i8x16(q5h_0),
wasm_i16x8_extend_high_i8x16(q8_2)
));
v128_t ph1 = wasm_i32x4_dot_i16x8(
wasm_i16x8_extend_low_i8x16(q5h_1),
wasm_i16x8_extend_low_i8x16(q8_3)
);
ph1 = wasm_i32x4_add(ph1, wasm_i32x4_dot_i16x8(
wasm_i16x8_extend_high_i8x16(q5h_1),
wasm_i16x8_extend_high_i8x16(q8_3)
));
v128_t sum_high = wasm_i32x4_add(ph0, ph1);
// Accumulate with scale factors
int32_t sl = wasm_i32x4_extract_lane(sum_low, 0) + wasm_i32x4_extract_lane(sum_low, 1) +
wasm_i32x4_extract_lane(sum_low, 2) + wasm_i32x4_extract_lane(sum_low, 3);
int32_t sh = wasm_i32x4_extract_lane(sum_high, 0) + wasm_i32x4_extract_lane(sum_high, 1) +
wasm_i32x4_extract_lane(sum_high, 2) + wasm_i32x4_extract_lane(sum_high, 3);
sumi += sl * sc[2*j] + sh * sc[2*j+1];
}
sumf += d * sumi;
}
*s = sumf;
#else
const uint8_t * scales = (const uint8_t*)&utmp[0];
const uint8_t * mins = (const uint8_t*)&utmp[2];
int8_t aux8[QK_K];
int16_t aux16[8];
float sums [8];
int32_t aux32[8];
memset(sums, 0, 8*sizeof(float));
float sumf = 0;
for (int i = 0; i < nb; ++i) {
const uint8_t * GGML_RESTRICT q4 = x[i].qs;
const uint8_t * GGML_RESTRICT hm = x[i].qh;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
memset(aux32, 0, 8*sizeof(int32_t));
int8_t * GGML_RESTRICT a = aux8;
uint8_t m = 1;
for (int j = 0; j < QK_K/64; ++j) {
for (int l = 0; l < 32; ++l) a[l] = (int8_t)(q4[l] & 0xF);
for (int l = 0; l < 32; ++l) a[l] += (hm[l] & m ? 16 : 0);
a += 32; m <<= 1;
for (int l = 0; l < 32; ++l) a[l] = (int8_t)(q4[l] >> 4);
for (int l = 0; l < 32; ++l) a[l] += (hm[l] & m ? 16 : 0);
a += 32; m <<= 1;
q4 += 32;
}
memcpy(utmp, x[i].scales, 12);
utmp[3] = ((utmp[2] >> 4) & kmask2) | (((utmp[1] >> 6) & kmask3) << 4);
const uint32_t uaux = utmp[1] & kmask1;
utmp[1] = (utmp[2] & kmask2) | (((utmp[0] >> 6) & kmask3) << 4);
utmp[2] = uaux;
utmp[0] &= kmask1;
int sumi = 0;
for (int j = 0; j < QK_K/16; ++j) sumi += y[i].bsums[j] * mins[j/2];
a = aux8;
int is = 0;
for (int j = 0; j < QK_K/32; ++j) {
int32_t scale = scales[is++];
for (int l = 0; l < 8; ++l) aux16[l] = q8[l] * a[l];
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
for (int l = 0; l < 8; ++l) aux16[l] = q8[l] * a[l];
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
for (int l = 0; l < 8; ++l) aux16[l] = q8[l] * a[l];
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
for (int l = 0; l < 8; ++l) aux16[l] = q8[l] * a[l];
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
const float dmin = GGML_FP16_TO_FP32(x[i].dmin) * y[i].d;
sumf -= dmin * sumi;
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
*s = sumf;
#endif
}
void ggml_vec_dot_q6_K_q8_K(int n, float * GGML_RESTRICT s, size_t bs, const void * GGML_RESTRICT vx, size_t bx, const void * GGML_RESTRICT vy, size_t by, int nrc) {
assert(n % QK_K == 0);
assert(nrc == 1);
UNUSED(nrc);
UNUSED(bx);
UNUSED(by);
UNUSED(bs);
const block_q6_K * GGML_RESTRICT x = vx;
const block_q8_K * GGML_RESTRICT y = vy;
const int nb = n / QK_K;
#if defined __wasm_simd128__
int8_t aux8[QK_K] __attribute__((aligned(16)));
int32_t aux32[8] __attribute__((aligned(16))) = {0};
float sums[8] __attribute__((aligned(16))) = {0};
for (int i = 0; i < nb; ++i) {
// Unpack 6-bit quantized data into aux8 (unchanged)
const uint8_t * GGML_RESTRICT q4 = x[i].ql;
const uint8_t * GGML_RESTRICT qh = x[i].qh;
int8_t * a = aux8;
for (int j = 0; j < QK_K; j += 128) {
for (int l = 0; l < 32; ++l) {
a[l + 0] = (int8_t)((q4[l + 0] & 0xF) | (((qh[l] >> 0) & 3) << 4)) - 32;
a[l + 32] = (int8_t)((q4[l + 32] & 0xF) | (((qh[l] >> 2) & 3) << 4)) - 32;
a[l + 64] = (int8_t)((q4[l + 0] >> 4) | (((qh[l] >> 4) & 3) << 4)) - 32;
a[l + 96] = (int8_t)((q4[l + 32] >> 4) | (((qh[l] >> 6) & 3) << 4)) - 32;
}
a += 128;
q4 += 64;
qh += 32;
}
const int8_t * GGML_RESTRICT a_ptr = aux8;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
v128_t acc0 = wasm_i32x4_splat(0);
v128_t acc1 = wasm_i32x4_splat(0);
for (int j = 0; j < QK_K/16; ++j) {
const int scale = x[i].scales[j];
const v128_t vscale = wasm_i32x4_splat(scale);
// Load 16 elements from a and q8
const v128_t a_vec = wasm_v128_load(a_ptr);
const v128_t q8_vec = wasm_v128_load(q8);
// Process low 8 elements
v128_t a_low = wasm_i16x8_extend_low_i8x16(a_vec);
v128_t q8_low = wasm_i16x8_extend_low_i8x16(q8_vec);
v128_t prod_low = wasm_i16x8_mul(a_low, q8_low);
v128_t prod_lo_lo = wasm_i32x4_extend_low_i16x8(prod_low);
v128_t prod_lo_hi = wasm_i32x4_extend_high_i16x8(prod_low);
// Process high 8 elements
v128_t a_high = wasm_i16x8_extend_high_i8x16(a_vec);
v128_t q8_high = wasm_i16x8_extend_high_i8x16(q8_vec);
v128_t prod_high = wasm_i16x8_mul(a_high, q8_high);
v128_t prod_hi_lo = wasm_i32x4_extend_low_i16x8(prod_high);
v128_t prod_hi_hi = wasm_i32x4_extend_high_i16x8(prod_high);
// Scale and accumulate
prod_lo_lo = wasm_i32x4_mul(prod_lo_lo, vscale);
prod_lo_hi = wasm_i32x4_mul(prod_lo_hi, vscale);
prod_hi_lo = wasm_i32x4_mul(prod_hi_lo, vscale);
prod_hi_hi = wasm_i32x4_mul(prod_hi_hi, vscale);
acc0 = wasm_i32x4_add(acc0, wasm_i32x4_add(prod_lo_lo, prod_hi_lo));
acc1 = wasm_i32x4_add(acc1, wasm_i32x4_add(prod_lo_hi, prod_hi_hi));
a_ptr += 16;
q8 += 16;
}
// Store accumulated results
wasm_v128_store(&aux32[0], acc0);
wasm_v128_store(&aux32[4], acc1);
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) {
sums[l] += d * aux32[l];
}
}
// Sum final results
float sumf = 0;
for (int l = 0; l < 8; ++l) {
sumf += sums[l];
}
*s = sumf;
#else
int8_t aux8[QK_K];
int16_t aux16[8];
float sums [8];
int32_t aux32[8];
memset(sums, 0, 8*sizeof(float));
float sumf = 0;
for (int i = 0; i < nb; ++i) {
const uint8_t * GGML_RESTRICT q4 = x[i].ql;
const uint8_t * GGML_RESTRICT qh = x[i].qh;
const int8_t * GGML_RESTRICT q8 = y[i].qs;
memset(aux32, 0, 8*sizeof(int32_t));
int8_t * GGML_RESTRICT a = aux8;
for (int j = 0; j < QK_K; j += 128) {
for (int l = 0; l < 32; ++l) {
a[l + 0] = (int8_t)((q4[l + 0] & 0xF) | (((qh[l] >> 0) & 3) << 4)) - 32;
a[l + 32] = (int8_t)((q4[l + 32] & 0xF) | (((qh[l] >> 2) & 3) << 4)) - 32;
a[l + 64] = (int8_t)((q4[l + 0] >> 4) | (((qh[l] >> 4) & 3) << 4)) - 32;
a[l + 96] = (int8_t)((q4[l + 32] >> 4) | (((qh[l] >> 6) & 3) << 4)) - 32;
}
a += 128;
q4 += 64;
qh += 32;
}
a = aux8;
int is = 0;
for (int j = 0; j < QK_K/16; ++j) {
int scale = x[i].scales[is++];
for (int l = 0; l < 8; ++l) aux16[l] = q8[l] * a[l];
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
for (int l = 0; l < 8; ++l) aux16[l] = q8[l] * a[l];
for (int l = 0; l < 8; ++l) aux32[l] += scale * aux16[l];
q8 += 8; a += 8;
}
const float d = GGML_FP16_TO_FP32(x[i].d) * y[i].d;
for (int l = 0; l < 8; ++l) sums[l] += d * aux32[l];
}
for (int l = 0; l < 8; ++l) sumf += sums[l];
*s = sumf;
#endif
}
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