#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 #include #include #include #include // for qsort #include // 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 }