diff options
Diffstat (limited to 'ggml/src')
| -rw-r--r-- | ggml/src/ggml-quants.c | 1 | ||||
| -rw-r--r-- | ggml/src/ggml.c | 26 | ||||
| -rw-r--r-- | ggml/src/iqk/iqk_mul_mat.cpp | 194 | ||||
| -rw-r--r-- | ggml/src/iqk/iqk_quantize.cpp | 97 | ||||
| -rw-r--r-- | ggml/src/iqk/iqk_quantize.h | 6 |
5 files changed, 324 insertions, 0 deletions
diff --git a/ggml/src/ggml-quants.c b/ggml/src/ggml-quants.c index 1953fb7e..94950a36 100644 --- a/ggml/src/ggml-quants.c +++ b/ggml/src/ggml-quants.c @@ -15199,6 +15199,7 @@ bool ggml_validate_row_data(enum ggml_type type, const void * data, size_t nbyte case GGML_TYPE_IQ4_NL_X4: break; case GGML_TYPE_Q4_0_R4: break; case GGML_TYPE_Q5_0_R4: break; + case GGML_TYPE_Q6_0_R4: break; case GGML_TYPE_Q8_0_R4: break; case GGML_TYPE_Q4_0_4_4: case GGML_TYPE_Q4_0_4_8: diff --git a/ggml/src/ggml.c b/ggml/src/ggml.c index 0eb76a07..203b1b57 100644 --- a/ggml/src/ggml.c +++ b/ggml/src/ggml.c @@ -1313,6 +1313,23 @@ static const ggml_type_traits_t type_traits[GGML_TYPE_COUNT] = { .nrows = 1, .row_meta_size = 0, }, + [GGML_TYPE_Q6_0_R4] = { + .type_name = "q6_0_r4", + .blck_size = QK6_0, + .type_size = sizeof(block_q6_0), + .is_quantized = true, + .to_float = (ggml_to_float_t) dequantize_row_q6_0_r4, + .from_float = quantize_row_q6_0_r4, + .from_float_ref = (ggml_from_float_t)quantize_row_q6_0_r4_ref, + .vec_dot = vec_dot_q6_0_r4_q8_0, +#if GGML_USE_IQK_MULMAT && defined __AVX2__ + .vec_dot_type = GGML_TYPE_Q8_1, +#else + .vec_dot_type = GGML_TYPE_Q8_0, +#endif + .nrows = 1, + .row_meta_size = 0, + }, }; // For internal test use @@ -3974,6 +3991,7 @@ enum ggml_type ggml_ftype_to_ggml_type(enum ggml_ftype ftype) { case GGML_FTYPE_MOSTLY_IQ4_NL_X4: wtype = GGML_TYPE_IQ4_NL_X4;break; case GGML_FTYPE_MOSTLY_Q4_0_R4: wtype = GGML_TYPE_Q4_0_R4; break; case GGML_FTYPE_MOSTLY_Q5_0_R4: wtype = GGML_TYPE_Q5_0_R4; break; + case GGML_FTYPE_MOSTLY_Q6_0_R4: wtype = GGML_TYPE_Q6_0_R4; break; case GGML_FTYPE_MOSTLY_Q8_0_R4: wtype = GGML_TYPE_Q8_0_R4; break; case GGML_FTYPE_MOSTLY_IQ4_XS: wtype = GGML_TYPE_IQ4_XS; break; case GGML_FTYPE_MOSTLY_IQ4_KS: wtype = GGML_TYPE_IQ4_KS; break; @@ -10501,6 +10519,7 @@ static void ggml_compute_forward_add( case GGML_TYPE_IQ4_NL_X4: case GGML_TYPE_Q4_0_R4: case GGML_TYPE_Q5_0_R4: + case GGML_TYPE_Q6_0_R4: case GGML_TYPE_Q8_0_R4: case GGML_TYPE_IQ4_XS: case GGML_TYPE_IQ4_KS: @@ -10947,6 +10966,7 @@ static void ggml_compute_forward_add1( case GGML_TYPE_IQ4_NL_X4: case GGML_TYPE_Q4_0_R4: case GGML_TYPE_Q5_0_R4: + case GGML_TYPE_Q6_0_R4: case GGML_TYPE_Q8_0_R4: case GGML_TYPE_IQ4_XS: case GGML_TYPE_IQ4_KS: @@ -11090,6 +11110,7 @@ static void ggml_compute_forward_acc( case GGML_TYPE_IQ4_NL_X4: case GGML_TYPE_Q4_0_R4: case GGML_TYPE_Q5_0_R4: + case GGML_TYPE_Q6_0_R4: case GGML_TYPE_Q8_0_R4: case GGML_TYPE_IQ4_XS: case GGML_TYPE_IQ4_KS: @@ -14279,6 +14300,7 @@ static void ggml_compute_forward_out_prod( case GGML_TYPE_IQ4_NL_X4: case GGML_TYPE_Q4_0_R4: case GGML_TYPE_Q5_0_R4: + case GGML_TYPE_Q6_0_R4: case GGML_TYPE_Q8_0_R4: case GGML_TYPE_IQ4_XS: case GGML_TYPE_IQ4_KS: @@ -14662,6 +14684,7 @@ static void ggml_compute_forward_set( case GGML_TYPE_IQ4_NL_X4: case GGML_TYPE_Q4_0_R4: case GGML_TYPE_Q5_0_R4: + case GGML_TYPE_Q6_0_R4: case GGML_TYPE_Q8_0_R4: case GGML_TYPE_IQ4_XS: case GGML_TYPE_IQ4_KS: @@ -14939,6 +14962,7 @@ static void ggml_compute_forward_get_rows( case GGML_TYPE_IQ4_NL_X4: case GGML_TYPE_Q4_0_R4: case GGML_TYPE_Q5_0_R4: + case GGML_TYPE_Q6_0_R4: case GGML_TYPE_Q8_0_R4: case GGML_TYPE_IQ4_XS: case GGML_TYPE_IQ4_KS: @@ -15543,6 +15567,7 @@ static void ggml_compute_forward_clamp( case GGML_TYPE_IQ4_NL_X4: case GGML_TYPE_Q4_0_R4: case GGML_TYPE_Q5_0_R4: + case GGML_TYPE_Q6_0_R4: case GGML_TYPE_Q8_0_R4: case GGML_TYPE_IQ4_XS: case GGML_TYPE_IQ4_KS: @@ -22373,6 +22398,7 @@ size_t ggml_quantize_chunk( case GGML_TYPE_IQ4_NL_X4: result = quantize_iq4_nl_x4(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break; case GGML_TYPE_Q4_0_R4: result = quantize_q4_0_r4(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break; case GGML_TYPE_Q5_0_R4: result = quantize_q5_0_r4(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break; + case GGML_TYPE_Q6_0_R4: result = quantize_q6_0_r4(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break; case GGML_TYPE_Q8_0_R4: result = quantize_q8_0_r4(src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break; case GGML_TYPE_IQ4_XS: result = quantize_iq4_xs (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break; case GGML_TYPE_IQ4_KS: result = quantize_iq4_ks (src + start, (char *) dst + start_row * row_size, nrows, n_per_row, imatrix); break; diff --git a/ggml/src/iqk/iqk_mul_mat.cpp b/ggml/src/iqk/iqk_mul_mat.cpp index 4cdc1a08..f827e460 100644 --- a/ggml/src/iqk/iqk_mul_mat.cpp +++ b/ggml/src/iqk/iqk_mul_mat.cpp @@ -2400,6 +2400,128 @@ static void mul_mat_q5_0_r4_q8_1(int n, const void * vx, size_t bx, const DataIn } #endif +template <int nrc_y> +static void mul_mat_q6_0_r4_q8_1_avx2(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + GGML_ASSERT(nrc_x%8 == 0); + Q8<nrc_y, block_q8_1_x4> q8(info); + auto m4 = _mm256_set1_epi8(0xf); + auto m6 = _mm256_set1_epi8(0x30); +#ifndef HAVE_FANCY_SIMD + auto m1 = _mm256_set1_epi16(1); +#endif + int nb = n / QK6_0; + GGML_ASSERT(nb%4 == 0); + __m256 acc[nrc_y] = {}; + for (int ix = 0; ix < nrc_x; ix += 4) { + const block_q6_0_r4 * iq6 = (const block_q6_0_r4 *)((const char *)vx + ix*bx); + for (int ib4 = 0; ib4 < nb/4; ++ib4) { + for (int k = 0; k < 4; ++k) { + auto scales128 = _mm_cvtph_ps(_mm_loadl_epi64((const __m128i *)iq6[4*ib4+k].d)); + auto scales = _mm256_set_m128(scales128, scales128); + auto scales_m = _mm256_mul_ps(scales, _mm256_set1_ps(-16.f)); + auto bits1 = _mm256_loadu_si256((const __m256i *)iq6[4*ib4+k].qs+0); + auto bits2 = _mm256_loadu_si256((const __m256i *)iq6[4*ib4+k].qs+1); + auto hbits = _mm256_loadu_si256((const __m256i *)iq6[4*ib4+k].qh); + auto q1 = _mm256_and_si256(bits1, m4) | _mm256_and_si256(_mm256_slli_epi16(hbits, 4), m6); + auto q2 = _mm256_and_si256(bits2, m4) | _mm256_and_si256(_mm256_slli_epi16(hbits, 2), m6); + auto q3 = _mm256_and_si256(_mm256_srli_epi16(bits1, 4), m4) | _mm256_and_si256(hbits, m6); + auto q4 = _mm256_and_si256(_mm256_srli_epi16(bits2, 4), m4) | _mm256_and_si256(_mm256_srli_epi16(hbits, 2), m6);; + for (int iy = 0; iy < nrc_y; ++iy) { + auto y = _mm256_loadu_si256((const __m256i*)q8.y[iy][ib4].qs+k); +#ifdef HAVE_FANCY_SIMD + auto sumi = _mm256_dpbusd_epi32(_mm256_setzero_si256(), q1, _mm256_shuffle_epi32(y, 0x00)); + sumi = _mm256_dpbusd_epi32(sumi, q2, _mm256_shuffle_epi32(y, 0x55)); + sumi = _mm256_dpbusd_epi32(sumi, q3, _mm256_shuffle_epi32(y, 0xaa)); + sumi = _mm256_dpbusd_epi32(sumi, q4, _mm256_shuffle_epi32(y, 0xff)); +#else + auto sumi1 = _mm256_add_epi16(_mm256_maddubs_epi16(q1, _mm256_shuffle_epi32(y, 0x00)), + _mm256_maddubs_epi16(q2, _mm256_shuffle_epi32(y, 0x55))); + auto sumi2 = _mm256_add_epi16(_mm256_maddubs_epi16(q3, _mm256_shuffle_epi32(y, 0xaa)), + _mm256_maddubs_epi16(q4, _mm256_shuffle_epi32(y, 0xff))); + auto sumi = _mm256_add_epi32(_mm256_madd_epi16(m1, sumi1), _mm256_madd_epi16(m1, sumi2)); +#endif + auto d4d8 = _mm256_mul_ps(scales, _mm256_set1_ps(GGML_FP16_TO_FP32(q8.y[iy][ib4].d[k]))); + acc[iy] = _mm256_fmadd_ps(d4d8, _mm256_cvtepi32_ps(sumi), acc[iy]); + acc[iy] = _mm256_fmadd_ps(scales_m, _mm256_set1_ps(GGML_FP16_TO_FP32(q8.y[iy][ib4].d[k+4])), acc[iy]); + } + } + } + for (int iy = 0; iy < nrc_y; ++iy) { + auto sum = _mm_add_ps(_mm256_castps256_ps128(acc[iy]), _mm256_extractf128_ps(acc[iy], 1)); + info.store(ix, iy, sum); + acc[iy] = _mm256_setzero_ps(); + } + } +} + +#ifdef HAVE_FANCY_SIMD +template <int nrc_y> +static void mul_mat_q6_0_r4_q8_1(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + if constexpr (nrc_y == 1) { + mul_mat_q6_0_r4_q8_1_avx2<1>(n, vx, bx, info, nrc_x); + } else { + GGML_ASSERT(nrc_x%8 == 0); + Q8<nrc_y, block_q8_1_x4> q8(info); + auto m4 = _mm512_set1_epi8(0xf); + auto m6 = _mm512_set1_epi8(0x30); + int nb = n / QK6_0; + GGML_ASSERT(nb%4 == 0); + __m512 acc[2*nrc_y] = {}; + __m512i qx[4]; + for (int ix = 0; ix < nrc_x; ix += 8) { + const block_q6_0_r4 * iq6l = (const block_q6_0_r4 *)((const char *)vx + (ix+0)*bx); + const block_q6_0_r4 * iq6h = (const block_q6_0_r4 *)((const char *)vx + (ix+4)*bx); + for (int ib4 = 0; ib4 < nb/4; ++ib4) { + for (int k = 0; k < 4; ++k) { + auto scales128 = _mm_cvtph_ps(_mm_loadl_epi64((const __m128i *)iq6l[4*ib4+k].d)); + auto scales1 = _mm256_set_m128(scales128, scales128); + scales128 = _mm_cvtph_ps(_mm_loadl_epi64((const __m128i *)iq6h[4*ib4+k].d)); + auto scales2 = _mm256_set_m128(scales128, scales128); + auto scales = _mm512_insertf32x8(_mm512_castps256_ps512(scales1), scales2, 1); + auto scales_m = _mm512_mul_ps(scales, _mm512_set1_ps(-16.f)); + auto bits1 = _mm512_inserti32x8(_mm512_castsi256_si512(_mm256_loadu_si256((const __m256i *)iq6l[4*ib4+k].qs+0)), + _mm256_loadu_si256((const __m256i *)iq6h[4*ib4+k].qs+0), 1); + auto bits2 = _mm512_inserti32x8(_mm512_castsi256_si512(_mm256_loadu_si256((const __m256i *)iq6l[4*ib4+k].qs+1)), + _mm256_loadu_si256((const __m256i *)iq6h[4*ib4+k].qs+1), 1); + auto hbits1 = _mm256_loadu_si256((const __m256i *)iq6l[4*ib4+k].qh); + auto hbits2 = _mm256_loadu_si256((const __m256i *)iq6h[4*ib4+k].qh); + auto hb = _mm512_inserti32x8(_mm512_castsi256_si512(hbits1), hbits2, 1); + qx[0] = _mm512_and_si512(bits1, m4) | _mm512_and_si512(_mm512_slli_epi16(hb, 4), m6); + qx[1] = _mm512_and_si512(bits2, m4) | _mm512_and_si512(_mm512_slli_epi16(hb, 2), m6);; + qx[2] = _mm512_and_si512(_mm512_srli_epi16(bits1, 4), m4) | _mm512_and_si512(hb, m6); + qx[3] = _mm512_and_si512(_mm512_srli_epi16(bits2, 4), m4) | _mm512_and_si512(_mm512_srli_epi16(hb, 2), m6); + for (int iy = 0; iy < nrc_y; ++iy) { + auto y8 = _mm256_loadu_si256((const __m256i*)q8.y[iy][ib4].qs+k); + auto y = _mm512_inserti32x8(_mm512_castsi256_si512(y8), y8, 1); + auto sumi = _mm512_setzero_si512(); + sumi = _mm512_dpbusd_epi32(sumi, qx[0], _mm512_shuffle_epi32(y, _MM_PERM_ENUM(0x00))); + sumi = _mm512_dpbusd_epi32(sumi, qx[1], _mm512_shuffle_epi32(y, _MM_PERM_ENUM(0x55))); + sumi = _mm512_dpbusd_epi32(sumi, qx[2], _mm512_shuffle_epi32(y, _MM_PERM_ENUM(0xaa))); + sumi = _mm512_dpbusd_epi32(sumi, qx[3], _mm512_shuffle_epi32(y, _MM_PERM_ENUM(0xff))); + auto dy = _mm512_set1_ps(GGML_FP16_TO_FP32(q8.y[iy][ib4].d[k])); + acc[2*iy+0] = _mm512_fmadd_ps(_mm512_mul_ps(scales, dy), _mm512_cvtepi32_ps(sumi), acc[2*iy+0]); + acc[2*iy+1] = _mm512_fmadd_ps(scales_m, _mm512_set1_ps(GGML_FP16_TO_FP32(q8.y[iy][ib4].d[k+4])), acc[2*iy+1]); + } + } + } + for (int iy = 0; iy < nrc_y; ++iy) { + auto sum512 = _mm512_add_ps(acc[2*iy+0], acc[2*iy+1]); + acc[2*iy+0] = acc[2*iy+1] = _mm512_setzero_ps(); + auto sum1 = _mm_add_ps(_mm512_extractf32x4_ps(sum512, 0), _mm512_extractf32x4_ps(sum512, 1)); + auto sum2 = _mm_add_ps(_mm512_extractf32x4_ps(sum512, 2), _mm512_extractf32x4_ps(sum512, 3)); + info.store(ix+0, iy, sum1); + info.store(ix+4, iy, sum2); + } + } + } +} +#else +template <int nrc_y> +static void mul_mat_q6_0_r4_q8_1(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + mul_mat_q6_0_r4_q8_1_avx2<nrc_y>(n, vx, bx, info, nrc_x); +} +#endif + #ifdef HAVE_FANCY_SIMD template <int nrc_y> static void mul_mat_q8_0_r4_q8_1(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { @@ -4527,6 +4649,18 @@ bool MulMat::prepare(int typeA, int typeB, int ne00, MulMat& mm, int Ny) { mm.funcs[7] = mul_mat_q5_0_r4_q8_1<8>; expected_typeB = GGML_TYPE_Q8_1; break; + case GGML_TYPE_Q6_0_R4: + assert (ne00 % QK4_NL == 0); + mm.funcs[0] = mul_mat_q6_0_r4_q8_1<1>; + mm.funcs[1] = mul_mat_q6_0_r4_q8_1<2>; + mm.funcs[2] = mul_mat_q6_0_r4_q8_1<3>; + mm.funcs[3] = mul_mat_q6_0_r4_q8_1<4>; + mm.funcs[4] = mul_mat_q6_0_r4_q8_1<5>; + mm.funcs[5] = mul_mat_q6_0_r4_q8_1<6>; + mm.funcs[6] = mul_mat_q6_0_r4_q8_1<7>; + mm.funcs[7] = mul_mat_q6_0_r4_q8_1<8>; + expected_typeB = GGML_TYPE_Q8_1; + break; case GGML_TYPE_Q8_0_R4: assert (ne00 % QK4_NL == 0); mm.funcs[0] = mul_mat_q8_0_r4_q8_1<1>; @@ -7130,6 +7264,55 @@ void mul_mat_q5_0_r4_q8_0(int n, const void * vx, size_t bx, const DataInfo& inf } template <int nrc_y> +void mul_mat_q6_0_r4_q8_0(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { + GGML_ASSERT(nrc_x%4 == 0); + Q8<nrc_y, block_q8_0_x4> q8(info); + auto m4 = vdupq_n_u8(0x0f); + auto m6 = vdupq_n_u8(0x30); + auto m32 = vdupq_n_s8(-32); + int nb = n / QK6_0; + GGML_ASSERT(nb%4 == 0); + int8x16_t qx[8]; + float32x4_t acc[nrc_y] = {}; + for (int ix = 0; ix < nrc_x; ix += 4) { + const block_q6_0_r4 * iq6 = (const block_q6_0_r4 *)((const char *)vx + ix*bx); + for (int ib4 = 0; ib4 < nb/4; ++ib4) { + for (int k = 0; k < 4; ++k) { + auto scales = vcvt_f32_f16(vld1_f16((const float16_t *)iq6[4*ib4+k].d)); + auto lbits = vld1q_u8_x4(iq6[4*ib4+k].qs); + auto hbits = vld1q_u8_x2(iq6[4*ib4+k].qh); + qx[0] = vaddq_s8(vandq_u8(lbits.val[0], m4) | vandq_u8(vshlq_n_u8(hbits.val[0], 4), m6), m32); // 0...3 + qx[1] = vaddq_s8(vandq_u8(lbits.val[1], m4) | vandq_u8(vshlq_n_u8(hbits.val[1], 4), m6), m32); // 16..19 + qx[2] = vaddq_s8(vandq_u8(lbits.val[2], m4) | vandq_u8(vshlq_n_u8(hbits.val[0], 2), m6), m32); // 4...7 + qx[3] = vaddq_s8(vandq_u8(lbits.val[3], m4) | vandq_u8(vshlq_n_u8(hbits.val[1], 2), m6), m32); // 20..23 + qx[4] = vaddq_s8(vshrq_n_u8(lbits.val[0], 4)| vandq_u8(hbits.val[0], m6), m32); // 8..11 + qx[5] = vaddq_s8(vshrq_n_u8(lbits.val[1], 4)| vandq_u8(hbits.val[1], m6), m32); // 24..27 + qx[6] = vaddq_s8(vshrq_n_u8(lbits.val[2], 4)| vandq_u8(vshrq_n_u8(hbits.val[0], 2), m6), m32); // 12..15 + qx[7] = vaddq_s8(vshrq_n_u8(lbits.val[3], 4)| vandq_u8(vshrq_n_u8(hbits.val[1], 2), m6), m32); // 28..31 + for (int iy = 0; iy < nrc_y; ++iy) { + auto y = vld1q_s8_x2(q8.y[iy][ib4].qs+32*k); + auto sumi = vdupq_n_s32(0); + sumi = vdotq_laneq_s32(sumi, qx[0], y.val[0], 0); + sumi = vdotq_laneq_s32(sumi, qx[1], y.val[1], 0); + sumi = vdotq_laneq_s32(sumi, qx[2], y.val[0], 1); + sumi = vdotq_laneq_s32(sumi, qx[3], y.val[1], 1); + sumi = vdotq_laneq_s32(sumi, qx[4], y.val[0], 2); + sumi = vdotq_laneq_s32(sumi, qx[5], y.val[1], 2); + sumi = vdotq_laneq_s32(sumi, qx[6], y.val[0], 3); + sumi = vdotq_laneq_s32(sumi, qx[7], y.val[1], 3); + auto d4d8 = vmulq_f32(scales, vdupq_n_f32(GGML_FP16_TO_FP32(q8.y[iy][ib4].d[k]))); + acc[iy] = vfmaq_f32(acc[iy], d4d8, vcvtq_f32_s32(sumi)); + } + } + } + for (int iy = 0; iy < nrc_y; ++iy) { + info.store(ix, iy, acc[iy]); + acc[iy] = vdupq_n_f32(0.f); + } + } +} + +template <int nrc_y> void mul_mat_q8_0_r4_q8_0(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) { GGML_ASSERT(nrc_x%4 == 0); Q8<nrc_y, block_q8_0_x4> q8(info); @@ -7368,6 +7551,17 @@ bool MulMat::prepare(int typeA, int typeB, int ne00, MulMat& m, int /*Ny*/) { m.funcs[7] = mul_mat_q5_0_r4_q8_0<8>; expected_Btype = GGML_TYPE_Q8_0; break; + case GGML_TYPE_Q6_0_R4: + m.funcs[0] = mul_mat_q6_0_r4_q8_0<1>; + m.funcs[1] = mul_mat_q6_0_r4_q8_0<2>; + m.funcs[2] = mul_mat_q6_0_r4_q8_0<3>; + m.funcs[3] = mul_mat_q6_0_r4_q8_0<4>; + m.funcs[4] = mul_mat_q6_0_r4_q8_0<5>; + m.funcs[5] = mul_mat_q6_0_r4_q8_0<6>; + m.funcs[6] = mul_mat_q6_0_r4_q8_0<7>; + m.funcs[7] = mul_mat_q6_0_r4_q8_0<8>; + expected_Btype = GGML_TYPE_Q8_0; + break; case GGML_TYPE_Q8_0_R4: m.funcs[0] = mul_mat_q8_0_r4_q8_0<1>; m.funcs[1] = mul_mat_q8_0_r4_q8_0<2>; diff --git a/ggml/src/iqk/iqk_quantize.cpp b/ggml/src/iqk/iqk_quantize.cpp index eafb2887..f2e6a45e 100644 --- a/ggml/src/iqk/iqk_quantize.cpp +++ b/ggml/src/iqk/iqk_quantize.cpp @@ -3475,3 +3475,100 @@ void vec_dot_q5_0_r4_q8_0(int n, float * s, size_t bs, const void * vx, size_t b GGML_UNUSED(bx); GGML_UNUSED(by); } + +// +// ========================================= q6_0_r4 +// +void quantize_row_q6_0_r4_ref(const float * x, block_q6_0_r4 * y, int64_t k) { + // we assume we are called with 4 rows + quantize_q6_0_r4(x, (void *)y, 4, k/4, nullptr); +} + +void quantize_row_q6_0_r4(const float * x, void * y, int64_t k) { + // we assume we are called with 4 rows + quantize_q6_0_r4(x, y, 4, k/4, nullptr); +} + +static inline void convert_q6_0(const block_q6_0& x, uint8_t * L) { + + for (int j = 0; j < QK6_0/2; ++j) { + const uint8_t h = x.qh[j%(QK6_0/4)] >> 4*(j/(QK6_0/4)); + L[j ] = (x.qs[j] & 0x0F) | ((h << 4) & 0x30); + L[j + QK6_0/2] = (x.qs[j] >> 4) | ((h << 2) & 0x30); + } +} + +static void repack_q6_0(int nrows, int n_per_row, const block_q6_0 * x, block_q6_0_r4 * y) { + GGML_ASSERT(nrows%4 == 0); + GGML_ASSERT(n_per_row%QK5_0 == 0); + int nblock = n_per_row/QK6_0; + const block_q6_0 * x4[4]; + uint8_t L[QK6_0]; + for (int row = 0; row < nrows; row += 4) { + for (int k = 0; k < 4; ++k) x4[k] = x + nblock*k; + for (int ib = 0; ib < nblock; ++ib) { + std::memset(y[ib].qh, 0, QK6_0); + for (int k = 0; k < 4; ++k) { + y[ib].d[k] = x4[k][ib].d; + convert_q6_0(x4[k][ib], L); + for (int l = 0; l < 4; ++l) { + int l1 = 4*(l/2) + 16*(l%2), l2 = l1 + 8; + for (int i = 0; i < 4; ++i) { + y[ib].qs[4*k+i+16*l] = (L[i + l1] & 0xf) | ((L[i + l2] & 0xf) << 4); + y[ib].qh[4*k+i+16*(l%2)] |= ((L[i + l1] >> 4) | ((L[i + l2] >> 4) << 4)) << 2*(l/2); + } + } + } + } + x += 4*nblock; + y += nblock; + } +} + +size_t quantize_q6_0_r4(const float * src, void * dst, int64_t nrows, int64_t n_per_row, const float * imatrix) { + GGML_ASSERT(nrows%4 == 0); + auto row_size_0 = ggml_row_size(GGML_TYPE_Q6_0, n_per_row); + std::vector<char> qtmp(4*row_size_0); + char * qrow = (char *)dst; + for (int row = 0; row < nrows; row += 4) { + quantize_q6_0(src, qtmp.data(), 4, n_per_row, imatrix); + repack_q6_0(4, n_per_row, (const block_q6_0 *)qtmp.data(), (block_q6_0_r4 *)qrow); + src += 4*n_per_row; + qrow += 4*row_size_0; + } + return nrows*row_size_0; +} + +void dequantize_row_q6_0_r4(const block_q6_0_r4 * x, float * y, int64_t k) { + // we assume we are called with 4 rows + int n_per_row = k/4; + int nb = n_per_row/QK6_0; + float * yk[4]; + for (int k = 0; k < 4; ++k) yk[k] = y + k*n_per_row; + for (int ib = 0; ib < nb; ++ib) { + for (int k = 0; k < 4; ++k) { + float d = GGML_FP16_TO_FP32(x[ib].d[k]); + float m = -32*d; + for (int l = 0; l < 4; ++l) { + int ll = 16*(l%2) + 4*(l/2); + for (int i = 0; i < 4; ++i) { + yk[k][QK4_0*ib+i+ll+0] = d * ((x[ib].qs[4*k+i+16*l] & 0xf) | (((x[ib].qh[4*k+i+16*(l%2)] >> (2*(l/2)+0)) & 3) << 4)) + m; + yk[k][QK4_0*ib+i+ll+8] = d * ((x[ib].qs[4*k+i+16*l] >> 4) | (((x[ib].qh[4*k+i+16*(l%2)] >> (2*(l/2)+4)) & 3) << 4)) + m; + } + } + } + } +} + +void vec_dot_q6_0_r4_q8_0(int n, float * s, size_t bs, const void * vx, size_t bx, const void * vy, size_t by, int nrc) { +#if GGML_USE_IQK_MULMAT + if (iqk_mul_mat(1, 1, n, GGML_TYPE_Q6_0_R4, vx, 0, GGML_TYPE_Q8_0, vy, 0, s, 0, 0, 1)) { + return; + } +#endif + GGML_ASSERT(n%QK4_NL == 0); + GGML_ASSERT(nrc == 1); + GGML_UNUSED(bs); + GGML_UNUSED(bx); + GGML_UNUSED(by); +} diff --git a/ggml/src/iqk/iqk_quantize.h b/ggml/src/iqk/iqk_quantize.h index 24c241a2..3349c675 100644 --- a/ggml/src/iqk/iqk_quantize.h +++ b/ggml/src/iqk/iqk_quantize.h @@ -87,6 +87,12 @@ size_t quantize_q5_0_r4(const float * GGML_RESTRICT src, void * GGML_RESTRICT ds void dequantize_row_q5_0_r4(const block_q5_0_r4 * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k); void vec_dot_q5_0_r4_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); +void quantize_row_q6_0_r4_ref(const float * GGML_RESTRICT x, block_q6_0_r4 * GGML_RESTRICT y, int64_t k); +void quantize_row_q6_0_r4(const float * GGML_RESTRICT x, void * GGML_RESTRICT y, int64_t k); +size_t quantize_q6_0_r4(const float * GGML_RESTRICT src, void * GGML_RESTRICT dst, int64_t nrows, int64_t n_per_row, const float * imatrix); +void dequantize_row_q6_0_r4(const block_q6_0_r4 * GGML_RESTRICT x, float * GGML_RESTRICT y, int64_t k); +void vec_dot_q6_0_r4_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); + #ifdef __cplusplus } #endif |