diff options
author | Kawrakow <48489457+ikawrakow@users.noreply.github.com> | 2024-07-27 07:55:01 +0200 |
---|---|---|
committer | GitHub <noreply@github.com> | 2024-07-27 07:55:01 +0200 |
commit | 154e0d75fccf1784fe9ff6fd76a630b66563da3d (patch) | |
tree | 81ce6dbb5b1900c1aa78a879f0593c694cab9d27 /ggml-sycl/dmmv.cpp | |
parent | 0684c3e9c70d49323b4fc517128cbe222cab7f96 (diff) |
Merge mainline llama.cpp (#3)
* Merging mainline - WIP
* Merging mainline - WIP
AVX2 and CUDA appear to work.
CUDA performance seems slightly (~1-2%) lower as it is so often
the case with llama.cpp/ggml after some "improvements" have been made.
* Merging mainline - fix Metal
* Remove check
---------
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
Diffstat (limited to 'ggml-sycl/dmmv.cpp')
-rw-r--r-- | ggml-sycl/dmmv.cpp | 1022 |
1 files changed, 0 insertions, 1022 deletions
diff --git a/ggml-sycl/dmmv.cpp b/ggml-sycl/dmmv.cpp deleted file mode 100644 index 3a87d3ef..00000000 --- a/ggml-sycl/dmmv.cpp +++ /dev/null @@ -1,1022 +0,0 @@ -#include "convert.hpp" -#include "dmmv.hpp" -#include "dequantize.hpp" -#include "presets.hpp" - -static void convert_f16(const void * vx, const int ib, const int iqs, dfloat2 & v){ - const sycl::half *x = (const sycl::half *)vx; - - // automatic half -> float type cast if dfloat == float - v.x() = x[ib + iqs + 0]; - v.y() = x[ib + iqs + 1]; -} - -static void convert_f32(const void * vx, const int ib, const int iqs, dfloat2 & v){ - const float * x = (const float *) vx; - - // automatic half -> float type cast if dfloat == float - v.x() = x[ib + iqs + 0]; - v.y() = x[ib + iqs + 1]; -} - -template <int qk, int qr, dequantize_kernel_t dequantize_kernel> -static void dequantize_mul_mat_vec(const void * __restrict__ vx, const dfloat * __restrict__ y, float * __restrict__ dst, const int ncols, const int nrows, - const sycl::nd_item<3> &item_ct1) { - // qk = quantized weights per x block - // qr = number of quantized weights per data value in x block - const int row = item_ct1.get_group(2) * item_ct1.get_local_range(1) + - item_ct1.get_local_id(1); - - if (row >= nrows) { - return; - } - - const int tid = item_ct1.get_local_id(2); - - const int iter_stride = 2*GGML_SYCL_DMMV_X; - const int vals_per_iter = iter_stride / WARP_SIZE; // num quantized vals per thread and i iter - const int y_offset = qr == 1 ? 1 : qk/2; - -// partial sum for each thread -#ifdef GGML_SYCL_F16 - sycl::half2 tmp = {0.0f, 0.0f}; // two sums for f16 to take advantage of half2 intrinsics -#else - float tmp = 0.0f; -#endif // GGML_SYCL_F16 - - for (int i = 0; i < ncols; i += iter_stride) { - const int col = i + vals_per_iter*tid; - const int ib = (row*ncols + col)/qk; // x block index - const int iqs = (col%qk)/qr; // x quant index - const int iybs = col - col%qk; // y block start index - -// processing >2 values per i iter is faster for fast GPUs -#pragma unroll - for (int j = 0; j < vals_per_iter; j += 2) { - // process 2 vals per j iter - - // dequantize - // for qr = 2 the iqs needs to increase by 1 per j iter because 2 weights per data val - dfloat2 v; - dequantize_kernel(vx, ib, iqs + j/qr, v); - - // matrix multiplication - // for qr = 2 the y index needs to increase by 1 per j iter because of y_offset = qk/2 -#ifdef GGML_SYCL_F16 - dfloat2 t1{y[iybs + iqs + j / qr + 0], - y[iybs + iqs + j / qr + y_offset]}; - - tmp += v * t1; -#else - tmp += v.x() * y[iybs + iqs + j / qr + 0]; - tmp += v.y() * y[iybs + iqs + j / qr + y_offset]; -#endif // GGML_SYCL_F16 - } - } - - // sum up partial sums and write back result -#pragma unroll - for (int mask = 16; mask > 0; mask >>= 1) { - tmp += - dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask); - } - - if (tid == 0) { -#ifdef GGML_SYCL_F16 - dst[row] = tmp.x() + tmp.y(); -#else - dst[row] = tmp; -#endif // GGML_SYCL_F16 - } -} - -static void convert_mul_mat_vec_f16_sycl(const void *vx, const dfloat *y, - float *dst, const int ncols, - const int nrows, - dpct::queue_ptr stream) { - GGML_ASSERT(ncols % GGML_SYCL_DMMV_X == 0); - const int block_num_y = (nrows + GGML_SYCL_MMV_Y - 1) / GGML_SYCL_MMV_Y; - const sycl::range<3> block_nums(1, 1, block_num_y); - const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, WARP_SIZE); - { - dpct::has_capability_or_fail(stream->get_device(), - {sycl::aspect::fp16}); - - stream->parallel_for( - sycl::nd_range<3>(block_nums * block_dims, block_dims), - [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(32)]] { - dequantize_mul_mat_vec<1, 1, convert_f16>(vx, y, dst, ncols, - nrows, item_ct1); - }); - } -} - -/* -DPCT1110:4: The total declared local variable size in device function -dequantize_mul_mat_vec_q2_k exceeds 128 bytes and may cause high register -pressure. Consult with your hardware vendor to find the total register size -available and adjust the code, or use smaller sub-group size to avoid high -register pressure. -*/ -static void dequantize_mul_mat_vec_q2_k(const void *__restrict__ vx, - const float *__restrict__ yy, - float *__restrict__ dst, - const int ncols, int nrows, - const sycl::nd_item<3> &item_ct1) { - - static_assert(16%K_QUANTS_PER_ITERATION == 0, "16 must be divisible by K_QUANTS_PER_ITERATION"); - - const int row = item_ct1.get_group(2) * item_ct1.get_local_range(1) + - item_ct1.get_local_id(1); - if (row > nrows) return; - - const int num_blocks_per_row = ncols / QK_K; - const int ib0 = row*num_blocks_per_row; - - const block_q2_K * x = (const block_q2_K *)vx + ib0; - - float tmp = 0; // partial sum for thread in warp - -#if QK_K == 256 - const int tid = - item_ct1.get_local_id(2) / K_QUANTS_PER_ITERATION; // 0...31 or 0...15 - const int ix = - item_ct1.get_local_id(2) % K_QUANTS_PER_ITERATION; // 0 or 0,1 - - const int step = 16/K_QUANTS_PER_ITERATION; - - const int im = tid/step; // 0 or 1. 0 computes 0..., 1 computes 128... - const int in = tid - step*im; // 0...15 or 0...7 - - const int l0 = K_QUANTS_PER_ITERATION*in; // 0...15 or 0...14 in steps of 2 - const int q_offset = 32*im + l0; - const int s_offset = 8*im; - const int y_offset = 128*im + l0; - - uint32_t aux[4]; - const uint8_t * d = (const uint8_t *)aux; - const uint8_t * m = (const uint8_t *)(aux + 2); - - for (int i = ix; i < num_blocks_per_row; i += K_QUANTS_PER_ITERATION) { - - const float * y = yy + i * QK_K + y_offset; - const uint8_t * q = x[i].qs + q_offset; - - const float dall = x[i].dm[0]; - const float dmin = x[i].dm[1]; - - const uint32_t * a = (const uint32_t *)(x[i].scales + s_offset); - aux[0] = a[0] & 0x0f0f0f0f; - aux[1] = a[1] & 0x0f0f0f0f; - aux[2] = (a[0] >> 4) & 0x0f0f0f0f; - aux[3] = (a[1] >> 4) & 0x0f0f0f0f; - - float sum1 = 0, sum2 = 0; - for (int l = 0; l < K_QUANTS_PER_ITERATION; ++l) { - sum1 += y[l+ 0] * d[0] * ((q[l+ 0] >> 0) & 3) - + y[l+32] * d[2] * ((q[l+ 0] >> 2) & 3) - + y[l+64] * d[4] * ((q[l+ 0] >> 4) & 3) - + y[l+96] * d[6] * ((q[l+ 0] >> 6) & 3) - + y[l+16] * d[1] * ((q[l+16] >> 0) & 3) - + y[l+48] * d[3] * ((q[l+16] >> 2) & 3) - + y[l+80] * d[5] * ((q[l+16] >> 4) & 3) - +y[l+112] * d[7] * ((q[l+16] >> 6) & 3); - sum2 += y[l+ 0] * m[0] + y[l+32] * m[2] + y[l+64] * m[4] + y[ l+96] * m[6] - + y[l+16] * m[1] + y[l+48] * m[3] + y[l+80] * m[5] + y[l+112] * m[7]; - - } - tmp += dall * sum1 - dmin * sum2; - - } -#else - const int tid = item_ct1.get_local_id(2) / - (2 * K_QUANTS_PER_ITERATION); // 0...15 or 0...7 - const int ix = item_ct1.get_local_id(2) % - (2 * K_QUANTS_PER_ITERATION); // 0....1 or 0...3 - const int offset = tid * K_QUANTS_PER_ITERATION; - - uint32_t uaux[2]; - const uint8_t * d = (const uint8_t *)uaux; - - - for (int i = ix; i < num_blocks_per_row; i += 2*K_QUANTS_PER_ITERATION) { - - const float * y = yy + i * QK_K + offset; - const uint8_t * q = x[i].qs + offset; - const uint32_t * s = (const uint32_t *)x[i].scales; - - uaux[0] = s[0] & 0x0f0f0f0f; - uaux[1] = (s[0] >> 4) & 0x0f0f0f0f; - - const sycl::float2 dall = - x[i].dm.convert<float, sycl::rounding_mode::automatic>(); - - float sum1 = 0, sum2 = 0; - for (int l = 0; l < K_QUANTS_PER_ITERATION; ++l) { - const uint8_t ql = q[l]; - sum1 += y[l+ 0] * d[0] * ((ql >> 0) & 3) - + y[l+16] * d[1] * ((ql >> 2) & 3) - + y[l+32] * d[2] * ((ql >> 4) & 3) - + y[l+48] * d[3] * ((ql >> 6) & 3); - sum2 += y[l+0] * d[4] + y[l+16] * d[5] + y[l+32] * d[6] + y[l+48] * d[7]; - } - tmp += dall.x() * sum1 - dall.y() * sum2; - } - -#endif - - // sum up partial sums and write back result -#pragma unroll - for (int mask = 16; mask > 0; mask >>= 1) { - tmp += - dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask); - } - - if (item_ct1.get_local_id(2) == 0) { - dst[row] = tmp; - } -} - -/* -DPCT1110:5: The total declared local variable size in device function -dequantize_mul_mat_vec_q3_k exceeds 128 bytes and may cause high register -pressure. Consult with your hardware vendor to find the total register size -available and adjust the code, or use smaller sub-group size to avoid high -register pressure. -*/ -static void dequantize_mul_mat_vec_q3_k(const void *__restrict__ vx, - const float *__restrict__ yy, - float *__restrict__ dst, - const int ncols, int nrows, - const sycl::nd_item<3> &item_ct1) { - - const int row = item_ct1.get_group(2) * item_ct1.get_local_range(1) + - item_ct1.get_local_id(1); - if (row > nrows) return; - - const int num_blocks_per_row = ncols / QK_K; - const int ib0 = row*num_blocks_per_row; - - const block_q3_K * x = (const block_q3_K *)vx + ib0; - - float tmp = 0; // partial sum for thread in warp - -#if QK_K == 256 - - const uint16_t kmask1 = 0x0303; - const uint16_t kmask2 = 0x0f0f; - - const int tid = - item_ct1.get_local_id(2) / K_QUANTS_PER_ITERATION; // 0...31 or 0...16 - const int ix = - item_ct1.get_local_id(2) % K_QUANTS_PER_ITERATION; // 0 or 0,1 - - const int n = K_QUANTS_PER_ITERATION; // iterations in the inner loop - const int step = 16/K_QUANTS_PER_ITERATION; - const int im = tid/step; // 0 or 1. 0 computes 0..., 1 computes 128... - const int in = tid - step*im; // 0....15 or 0...7 - - const uint8_t m = 1 << (4*im); - - const int l0 = n*in; // 0...15 or 0...14 in steps of 2 - const int q_offset = 32*im + l0; - const int y_offset = 128*im + l0; - - uint16_t utmp[4]; - const int8_t * s = (const int8_t *)utmp; - - const uint16_t s_shift = 4*im; - - for (int i = ix; i < num_blocks_per_row; i += K_QUANTS_PER_ITERATION) { - - const float * y = yy + i * QK_K + y_offset; - const uint8_t * q = x[i].qs + q_offset; - const uint8_t * h = x[i].hmask + l0; - - const uint16_t * a = (const uint16_t *)x[i].scales; - utmp[0] = ((a[0] >> s_shift) & kmask2) | (((a[4] >> (s_shift + 0)) & kmask1) << 4); - utmp[1] = ((a[1] >> s_shift) & kmask2) | (((a[5] >> (s_shift + 0)) & kmask1) << 4); - utmp[2] = ((a[2] >> s_shift) & kmask2) | (((a[4] >> (s_shift + 2)) & kmask1) << 4); - utmp[3] = ((a[3] >> s_shift) & kmask2) | (((a[5] >> (s_shift + 2)) & kmask1) << 4); - - const float d = x[i].d; - - float sum = 0; - for (int l = 0; l < n; ++l) { - sum += y[l+ 0] * (s[0] - 32) * (((q[l] >> 0) & 3) - (h[l] & (m << 0) ? 0 : 4)) - + y[l+32] * (s[2] - 32) * (((q[l] >> 2) & 3) - (h[l] & (m << 1) ? 0 : 4)) - + y[l+64] * (s[4] - 32) * (((q[l] >> 4) & 3) - (h[l] & (m << 2) ? 0 : 4)) - + y[l+96] * (s[6] - 32) * (((q[l] >> 6) & 3) - (h[l] & (m << 3) ? 0 : 4)); - sum += y[l+16] * (s[1] - 32) * (((q[l+16] >> 0) & 3) - (h[l+16] & (m << 0) ? 0 : 4)) - + y[l+48] * (s[3] - 32) * (((q[l+16] >> 2) & 3) - (h[l+16] & (m << 1) ? 0 : 4)) - + y[l+80] * (s[5] - 32) * (((q[l+16] >> 4) & 3) - (h[l+16] & (m << 2) ? 0 : 4)) - + y[l+112] * (s[7] - 32) * (((q[l+16] >> 6) & 3) - (h[l+16] & (m << 3) ? 0 : 4)); - } - tmp += d * sum; - - } -#else - - const int tid = item_ct1.get_local_id(2)/(2*K_QUANTS_PER_ITERATION); // 0...15 or 0...7 - const int ix = item_ct1.get_local_id(2)%(2*K_QUANTS_PER_ITERATION); // 0....1 or 0...3 - const int offset = tid * K_QUANTS_PER_ITERATION; // 0...15 or 0...14 - const int in = offset/8; // 0 or 1 - const int im = offset%8; // 0...7 - - for (int i = ix; i < num_blocks_per_row; i += 2*K_QUANTS_PER_ITERATION) { - - const float * y = yy + i * QK_K + offset; - const uint8_t * q = x[i].qs + offset; - const uint8_t * s = x[i].scales; - - const float dall = (float)x[i].d; - - float sum = 0; - for (int l = 0; l < K_QUANTS_PER_ITERATION; ++l) { - const uint8_t hl = x[i].hmask[im+l] >> in; - const uint8_t ql = q[l]; - sum += y[l+ 0] * dall * ((s[0] & 0xF) - 8) * ((int8_t)((ql >> 0) & 3) - ((hl >> 0) & 1 ? 0 : 4)) - + y[l+16] * dall * ((s[0] >> 4) - 8) * ((int8_t)((ql >> 2) & 3) - ((hl >> 2) & 1 ? 0 : 4)) - + y[l+32] * dall * ((s[1] & 0xF) - 8) * ((int8_t)((ql >> 4) & 3) - ((hl >> 4) & 1 ? 0 : 4)) - + y[l+48] * dall * ((s[1] >> 4) - 8) * ((int8_t)((ql >> 6) & 3) - ((hl >> 6) & 1 ? 0 : 4)); - } - tmp += sum; - } -#endif - - // sum up partial sums and write back result -#pragma unroll - for (int mask = 16; mask > 0; mask >>= 1) { - tmp += - dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask); - } - - if (item_ct1.get_local_id(2) == 0) { - dst[row] = tmp; - } -} - -/* -DPCT1110:6: The total declared local variable size in device function -dequantize_mul_mat_vec_q4_k exceeds 128 bytes and may cause high register -pressure. Consult with your hardware vendor to find the total register size -available and adjust the code, or use smaller sub-group size to avoid high -register pressure. -*/ -static void dequantize_mul_mat_vec_q4_k(const void *__restrict__ vx, - const float *__restrict__ yy, - float *__restrict__ dst, - const int ncols, int nrows, - const sycl::nd_item<3> &item_ct1) { - - const int row = item_ct1.get_group(2) * item_ct1.get_local_range(1) + - item_ct1.get_local_id(1); - if (row > nrows) return; - const int num_blocks_per_row = ncols / QK_K; - const int ib0 = row*num_blocks_per_row; - - const block_q4_K * x = (const block_q4_K *)vx + ib0; - -#if QK_K == 256 - const uint16_t kmask1 = 0x3f3f; - const uint16_t kmask2 = 0x0f0f; - const uint16_t kmask3 = 0xc0c0; - - const int tid = - item_ct1.get_local_id(2) / K_QUANTS_PER_ITERATION; // 0...31 or 0...16 - const int ix = - item_ct1.get_local_id(2) % K_QUANTS_PER_ITERATION; // 0 or 0,1 - - const int step = 8/K_QUANTS_PER_ITERATION; // 8 or 4 - - const int il = tid/step; // 0...3 - const int ir = tid - step*il; // 0...7 or 0...3 - const int n = 2 * K_QUANTS_PER_ITERATION; // 2 or 4 - - const int im = il/2; // 0 or 1. 0 computes 0,32 + 128,160, 1 computes 64,96 + 192,224 - const int in = il%2; - - const int l0 = n*(2*ir + in); - const int q_offset = 32*im + l0; - const int y_offset = 64*im + l0; - - uint16_t aux[4]; - const uint8_t * sc = (const uint8_t *)aux; - -#if K_QUANTS_PER_ITERATION == 2 - uint32_t q32[4]; - const uint8_t * q4 = (const uint8_t *)q32; -#else - uint16_t q16[4]; - const uint8_t * q4 = (const uint8_t *)q16; -#endif - - float tmp = 0; // partial sum for thread in warp - - for (int i = ix; i < num_blocks_per_row; i += K_QUANTS_PER_ITERATION) { - - const float * y1 = yy + i*QK_K + y_offset; - const float * y2 = y1 + 128; - - const float dall = x[i].dm[0]; - const float dmin = x[i].dm[1]; - - const uint16_t * a = (const uint16_t *)x[i].scales; - aux[0] = a[im+0] & kmask1; - aux[1] = a[im+2] & kmask1; - aux[2] = ((a[im+4] >> 0) & kmask2) | ((a[im+0] & kmask3) >> 2); - aux[3] = ((a[im+4] >> 4) & kmask2) | ((a[im+2] & kmask3) >> 2); - -#if K_QUANTS_PER_ITERATION == 2 - const uint32_t * q1 = (const uint32_t *)(x[i].qs + q_offset); - const uint32_t * q2 = q1 + 16; - - q32[0] = q1[0] & 0x0f0f0f0f; - q32[1] = q1[0] & 0xf0f0f0f0; - q32[2] = q2[0] & 0x0f0f0f0f; - q32[3] = q2[0] & 0xf0f0f0f0; - - sycl::float4 s = {0.f, 0.f, 0.f, 0.f}; - float smin = 0; - for (int l = 0; l < 4; ++l) { - s.x() += y1[l] * q4[l + 0]; s.y() += y1[l + 32] * q4[l + 4]; - s.z() += y2[l] * q4[l + 8]; s.w() += y2[l + 32] * q4[l + 12]; - smin += y1[l] * sc[2] + y1[l+32] * sc[3] + y2[l] * sc[6] + y2[l+32] * sc[7]; - } - tmp += dall * (s.x() * sc[0] + s.y() * sc[1] * 1.f / 16.f + - s.z() * sc[4] + s.w() * sc[5] * 1.f / 16.f) - - dmin * smin; -#else - const uint16_t * q1 = (const uint16_t *)(x[i].qs + q_offset); - const uint16_t * q2 = q1 + 32; - - q16[0] = q1[0] & 0x0f0f; - q16[1] = q1[0] & 0xf0f0; - q16[2] = q2[0] & 0x0f0f; - q16[3] = q2[0] & 0xf0f0; - - float4 s = {0.f, 0.f, 0.f, 0.f}; - float smin = 0; - for (int l = 0; l < 2; ++l) { - s.x += y1[l] * q4[l+0]; s.y += y1[l+32] * q4[l+2]; - s.z += y2[l] * q4[l+4]; s.w += y2[l+32] * q4[l+6]; - smin += y1[l] * sc[2] + y1[l+32] * sc[3] + y2[l] * sc[6] + y2[l+32] * sc[7]; - } - tmp += dall * (s.x * sc[0] + s.y * sc[1] * 1.f/16.f + s.z * sc[4] + s.w * sc[5] * 1.f/16.f) - dmin * smin; -#endif - - } -#else - const int tid = item_ct1.get_local_id(2)/(2*K_QUANTS_PER_ITERATION); // 0...15 - const int ix = item_ct1.get_local_id(2)%(2*K_QUANTS_PER_ITERATION); - - const int step = tid * K_QUANTS_PER_ITERATION; - - uint16_t aux16[2]; - const uint8_t * s = (const uint8_t *)aux16; - - float tmp = 0; - - for (int i = ix; i < num_blocks_per_row; i += 2*K_QUANTS_PER_ITERATION) { - const uint8_t * q = x[i].qs + step; - const float * y = yy + i*QK_K + step; - const uint16_t * a = (const uint16_t *)x[i].scales; - aux16[0] = a[0] & 0x0f0f; - aux16[1] = (a[0] >> 4) & 0x0f0f; - const float d = (float)x[i].dm[0]; - const float m = (float)x[i].dm[1]; - float sum = 0.f; - for (int j = 0; j < K_QUANTS_PER_ITERATION; ++j) { - sum += y[j+ 0] * (d * s[0] * (q[j+ 0] & 0xF) - m * s[2]) - + y[j+16] * (d * s[0] * (q[j+16] & 0xF) - m * s[2]) - + y[j+32] * (d * s[1] * (q[j+ 0] >> 4) - m * s[3]) - + y[j+48] * (d * s[1] * (q[j+16] >> 4) - m * s[3]); - } - tmp += sum; - } - -#endif - - // sum up partial sums and write back result -#pragma unroll - for (int mask = 16; mask > 0; mask >>= 1) { - tmp += - dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask); - } - - if (tid == 0) { - dst[row] = tmp; - } -} - -/* -DPCT1110:7: The total declared local variable size in device function -dequantize_mul_mat_vec_q5_k exceeds 128 bytes and may cause high register -pressure. Consult with your hardware vendor to find the total register size -available and adjust the code, or use smaller sub-group size to avoid high -register pressure. -*/ -static void dequantize_mul_mat_vec_q5_k(const void *__restrict__ vx, - const float *__restrict__ yy, - float *__restrict__ dst, - const int ncols, - const sycl::nd_item<3> &item_ct1) { - - const int row = item_ct1.get_group(2); - const int num_blocks_per_row = ncols / QK_K; - const int ib0 = row*num_blocks_per_row; - - const block_q5_K * x = (const block_q5_K *)vx + ib0; - - float tmp = 0; // partial sum for thread in warp - -#if QK_K == 256 - const uint16_t kmask1 = 0x3f3f; - const uint16_t kmask2 = 0x0f0f; - const uint16_t kmask3 = 0xc0c0; - - const int tid = item_ct1.get_local_id(2) / 2; // 0...15 - const int ix = item_ct1.get_local_id(2) % 2; - - const int il = tid/4; // 0...3 - const int ir = tid - 4*il;// 0...3 - const int n = 2; - - const int im = il/2; // 0 or 1. 0 computes 0,32 + 128,160, 1 computes 64,96 + 192,224 - const int in = il%2; - - const int l0 = n*(2*ir + in); - const int q_offset = 32*im + l0; - const int y_offset = 64*im + l0; - - const uint8_t hm1 = 1 << (2*im); - const uint8_t hm2 = hm1 << 4; - - uint16_t aux[4]; - const uint8_t * sc = (const uint8_t *)aux; - - uint16_t q16[8]; - const uint8_t * q4 = (const uint8_t *)q16; - - for (int i = ix; i < num_blocks_per_row; i += 2) { - - const uint8_t * ql1 = x[i].qs + q_offset; - const uint8_t * qh = x[i].qh + l0; - const float * y1 = yy + i*QK_K + y_offset; - const float * y2 = y1 + 128; - - const float dall = x[i].dm[0]; - const float dmin = x[i].dm[1]; - - const uint16_t * a = (const uint16_t *)x[i].scales; - aux[0] = a[im+0] & kmask1; - aux[1] = a[im+2] & kmask1; - aux[2] = ((a[im+4] >> 0) & kmask2) | ((a[im+0] & kmask3) >> 2); - aux[3] = ((a[im+4] >> 4) & kmask2) | ((a[im+2] & kmask3) >> 2); - - sycl::float4 sum = {0.f, 0.f, 0.f, 0.f}; - float smin = 0; - const uint16_t * q1 = (const uint16_t *)ql1; - const uint16_t * q2 = q1 + 32; - q16[0] = q1[0] & 0x0f0f; - q16[1] = q1[8] & 0x0f0f; - q16[2] = (q1[0] >> 4) & 0x0f0f; - q16[3] = (q1[8] >> 4) & 0x0f0f; - q16[4] = q2[0] & 0x0f0f; - q16[5] = q2[8] & 0x0f0f; - q16[6] = (q2[0] >> 4) & 0x0f0f; - q16[7] = (q2[8] >> 4) & 0x0f0f; - for (int l = 0; l < n; ++l) { - sum.x() += - y1[l + 0] * (q4[l + 0] + (qh[l + 0] & (hm1 << 0) ? 16 : 0)) + - y1[l + 16] * (q4[l + 2] + (qh[l + 16] & (hm1 << 0) ? 16 : 0)); - sum.y() += - y1[l + 32] * (q4[l + 4] + (qh[l + 0] & (hm1 << 1) ? 16 : 0)) + - y1[l + 48] * (q4[l + 6] + (qh[l + 16] & (hm1 << 1) ? 16 : 0)); - sum.z() += - y2[l + 0] * (q4[l + 8] + (qh[l + 0] & (hm2 << 0) ? 16 : 0)) + - y2[l + 16] * (q4[l + 10] + (qh[l + 16] & (hm2 << 0) ? 16 : 0)); - sum.w() += - y2[l + 32] * (q4[l + 12] + (qh[l + 0] & (hm2 << 1) ? 16 : 0)) + - y2[l + 48] * (q4[l + 14] + (qh[l + 16] & (hm2 << 1) ? 16 : 0)); - smin += (y1[l] + y1[l+16]) * sc[2] + (y1[l+32] + y1[l+48]) * sc[3] - + (y2[l] + y2[l+16]) * sc[6] + (y2[l+32] + y2[l+48]) * sc[7]; - } - tmp += dall * (sum.x() * sc[0] + sum.y() * sc[1] + sum.z() * sc[4] + - sum.w() * sc[5]) - - dmin * smin; - } - -#else - const int tid = item_ct1.get_local_id(2)/(2*K_QUANTS_PER_ITERATION); // 0...15 - const int ix = item_ct1.get_local_id(2)%(2*K_QUANTS_PER_ITERATION); - const int step = tid * K_QUANTS_PER_ITERATION; - const int im = step/8; - const int in = step%8; - - for (int i = ix; i < num_blocks_per_row; i += 2*K_QUANTS_PER_ITERATION) { - const uint8_t * q = x[i].qs + step; - const int8_t * s = x[i].scales; - const float * y = yy + i*QK_K + step; - const float d = x[i].d; - float sum = 0.f; - for (int j = 0; j < K_QUANTS_PER_ITERATION; ++j) { - const uint8_t h = x[i].qh[in+j] >> im; - sum += y[j+ 0] * d * s[0] * ((q[j+ 0] & 0xF) - ((h >> 0) & 1 ? 0 : 16)) - + y[j+16] * d * s[1] * ((q[j+16] & 0xF) - ((h >> 2) & 1 ? 0 : 16)) - + y[j+32] * d * s[2] * ((q[j+ 0] >> 4) - ((h >> 4) & 1 ? 0 : 16)) - + y[j+48] * d * s[3] * ((q[j+16] >> 4) - ((h >> 6) & 1 ? 0 : 16)); - } - tmp += sum; - } -#endif - - // sum up partial sums and write back result -#pragma unroll - for (int mask = 16; mask > 0; mask >>= 1) { - tmp += - dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask); - } - - if (item_ct1.get_local_id(2) == 0) { - dst[row] = tmp; - } -} - -static void dequantize_mul_mat_vec_q6_k(const void * __restrict__ vx, const float * __restrict__ yy, float * __restrict__ dst, const int ncols, int nrows, - const sycl::nd_item<3> &item_ct1) { - - static_assert(16%K_QUANTS_PER_ITERATION == 0, "16 must be divisible by K_QUANTS_PER_ITERATION"); - - const int row = item_ct1.get_group(2) * item_ct1.get_local_range(1) + - item_ct1.get_local_id(1); - if (row > nrows) return; - - const int num_blocks_per_row = ncols / QK_K; - const int ib0 = row*num_blocks_per_row; - - const block_q6_K * x = (const block_q6_K *)vx + ib0; - -#if QK_K == 256 - - const int tid = - item_ct1.get_local_id(2) / K_QUANTS_PER_ITERATION; // 0...31 or 0...16 - const int ix = - item_ct1.get_local_id(2) % K_QUANTS_PER_ITERATION; // 0 or 0, 1 - - const int step = 16/K_QUANTS_PER_ITERATION; // 16 or 8 - - const int im = tid/step; // 0 or 1. 0 computes 0..., 1 computes 128... - const int in = tid - step*im; // 0...15 or 0...7 - -#if K_QUANTS_PER_ITERATION == 1 - const int l0 = K_QUANTS_PER_ITERATION*in; // 0...15 - const int is = 0; -#else - const int l0 = 4 * in; // 0, 4, 8, ..., 28 - const int is = in / 4; -#endif - const int ql_offset = 64*im + l0; - const int qh_offset = 32*im + l0; - const int s_offset = 8*im + is; - const int y_offset = 128*im + l0; - - float tmp = 0; // partial sum for thread in warp - - for (int i = ix; i < num_blocks_per_row; i += K_QUANTS_PER_ITERATION) { - - const float * y = yy + i * QK_K + y_offset; - const uint8_t * ql = x[i].ql + ql_offset; - const uint8_t * qh = x[i].qh + qh_offset; - const int8_t * s = x[i].scales + s_offset; - - const float d = x[i].d; - -#if K_QUANTS_PER_ITERATION == 1 - float sum = y[ 0] * s[0] * d * ((int8_t)((ql[ 0] & 0xF) | ((qh[ 0] & 0x03) << 4)) - 32) - + y[16] * s[1] * d * ((int8_t)((ql[16] & 0xF) | ((qh[16] & 0x03) << 4)) - 32) - + y[32] * s[2] * d * ((int8_t)((ql[32] & 0xF) | ((qh[ 0] & 0x0c) << 2)) - 32) - + y[48] * s[3] * d * ((int8_t)((ql[48] & 0xF) | ((qh[16] & 0x0c) << 2)) - 32) - + y[64] * s[4] * d * ((int8_t)((ql[ 0] >> 4) | ((qh[ 0] & 0x30) >> 0)) - 32) - + y[80] * s[5] * d * ((int8_t)((ql[16] >> 4) | ((qh[16] & 0x30) >> 0)) - 32) - + y[96] * s[6] * d * ((int8_t)((ql[32] >> 4) | ((qh[ 0] & 0xc0) >> 2)) - 32) - +y[112] * s[7] * d * ((int8_t)((ql[48] >> 4) | ((qh[16] & 0xc0) >> 2)) - 32); - tmp += sum; -#else - float sum = 0; - for (int l = 0; l < 4; ++l) { - sum += y[l+ 0] * s[0] * d * ((int8_t)((ql[l+ 0] & 0xF) | (((qh[l] >> 0) & 3) << 4)) - 32) - + y[l+32] * s[2] * d * ((int8_t)((ql[l+32] & 0xF) | (((qh[l] >> 2) & 3) << 4)) - 32) - + y[l+64] * s[4] * d * ((int8_t)((ql[l+ 0] >> 4) | (((qh[l] >> 4) & 3) << 4)) - 32) - + y[l+96] * s[6] * d * ((int8_t)((ql[l+32] >> 4) | (((qh[l] >> 6) & 3) << 4)) - 32); - } - tmp += sum; -#endif - - } - -#else - - const int tid = item_ct1.get_local_id(2)/(2*K_QUANTS_PER_ITERATION); // 0...7 - const int ix = item_ct1.get_local_id(2)%(2*K_QUANTS_PER_ITERATION); // 0...3 - - const int step = tid * K_QUANTS_PER_ITERATION; - - float tmp = 0; // partial sum for thread in warp - - for (int i = ix; i < num_blocks_per_row; i += 2*K_QUANTS_PER_ITERATION) { - - const float * y = yy + i * QK_K + step; - const uint8_t * ql = x[i].ql + step; - const uint8_t * qh = x[i].qh + step; - const int8_t * s = x[i].scales; - - const float d = x[i+0].d; - - float sum = 0; - for (int j = 0; j < K_QUANTS_PER_ITERATION; ++j) { - sum += y[j+ 0] * s[0] * d * ((int8_t)((ql[j+ 0] & 0xF) | ((qh[j] & 0x03) << 4)) - 32) - + y[j+16] * s[1] * d * ((int8_t)((ql[j+16] & 0xF) | ((qh[j] & 0x0c) << 2)) - 32) - + y[j+32] * s[2] * d * ((int8_t)((ql[j+ 0] >> 4) | ((qh[j] & 0x30) >> 0)) - 32) - + y[j+48] * s[3] * d * ((int8_t)((ql[j+16] >> 4) | ((qh[j] & 0xc0) >> 2)) - 32); - } - tmp += sum; - - } - -#endif - - // sum up partial sums and write back result -#pragma unroll - for (int mask = 16; mask > 0; mask >>= 1) { - tmp += - dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask); - } - - if (tid == 0) { - dst[row] = tmp; - } -} - - -static void dequantize_mul_mat_vec_q4_0_sycl(const void *vx, const dfloat *y, - float *dst, const int ncols, - const int nrows, - dpct::queue_ptr stream) { - GGML_ASSERT(ncols % GGML_SYCL_DMMV_X == 0); - const int block_num_y = (nrows + GGML_SYCL_MMV_Y - 1) / GGML_SYCL_MMV_Y; - // the number of rows may exceed maximum grid size in the y or z dimensions, use the x dimension instead - const sycl::range<3> block_nums(1, 1, block_num_y); - const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, WARP_SIZE); - { - dpct::has_capability_or_fail(stream->get_device(), - {sycl::aspect::fp16}); - - stream->parallel_for( - sycl::nd_range<3>(block_nums * block_dims, block_dims), - [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(32)]] { - dequantize_mul_mat_vec<QK4_0, QR4_0, dequantize_q4_0>( - vx, y, dst, ncols, nrows, item_ct1); - }); - } -} - -static void dequantize_mul_mat_vec_q4_1_sycl(const void *vx, const dfloat *y, - float *dst, const int ncols, - const int nrows, - dpct::queue_ptr stream) { - GGML_ASSERT(ncols % GGML_SYCL_DMMV_X == 0); - const int block_num_y = (nrows + GGML_SYCL_MMV_Y - 1) / GGML_SYCL_MMV_Y; - const sycl::range<3> block_nums(1, 1, block_num_y); - const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, WARP_SIZE); - { - dpct::has_capability_or_fail(stream->get_device(), - {sycl::aspect::fp16}); - - stream->parallel_for( - sycl::nd_range<3>(block_nums * block_dims, block_dims), - [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(32)]] { - dequantize_mul_mat_vec<QK4_1, QR4_1, dequantize_q4_1>( - vx, y, dst, ncols, nrows, item_ct1); - }); - } -} - -static void dequantize_mul_mat_vec_q5_0_sycl(const void *vx, const dfloat *y, - float *dst, const int ncols, - const int nrows, - dpct::queue_ptr stream) { - GGML_ASSERT(ncols % GGML_SYCL_DMMV_X == 0); - const int block_num_y = (nrows + GGML_SYCL_MMV_Y - 1) / GGML_SYCL_MMV_Y; - const sycl::range<3> block_nums(1, 1, block_num_y); - const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, WARP_SIZE); - { - dpct::has_capability_or_fail(stream->get_device(), - {sycl::aspect::fp16}); - - stream->parallel_for( - sycl::nd_range<3>(block_nums * block_dims, block_dims), - [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(32)]] { - dequantize_mul_mat_vec<QK5_0, QR5_0, dequantize_q5_0>( - vx, y, dst, ncols, nrows, item_ct1); - }); - } -} - -static void dequantize_mul_mat_vec_q5_1_sycl(const void *vx, const dfloat *y, - float *dst, const int ncols, - const int nrows, - dpct::queue_ptr stream) { - GGML_ASSERT(ncols % GGML_SYCL_DMMV_X == 0); - const int block_num_y = (nrows + GGML_SYCL_MMV_Y - 1) / GGML_SYCL_MMV_Y; - const sycl::range<3> block_nums(1, 1, block_num_y); - const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, WARP_SIZE); - { - dpct::has_capability_or_fail(stream->get_device(), - {sycl::aspect::fp16}); - - stream->parallel_for( - sycl::nd_range<3>(block_nums * block_dims, block_dims), - [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(32)]] { - dequantize_mul_mat_vec<QK5_1, QR5_1, dequantize_q5_1>( - vx, y, dst, ncols, nrows, item_ct1); - }); - } -} - -static void dequantize_mul_mat_vec_q8_0_sycl(const void *vx, const dfloat *y, - float *dst, const int ncols, - const int nrows, - dpct::queue_ptr stream) { - GGML_ASSERT(ncols % GGML_SYCL_DMMV_X == 0); - const int block_num_y = (nrows + GGML_SYCL_MMV_Y - 1) / GGML_SYCL_MMV_Y; - const sycl::range<3> block_nums(1, 1, block_num_y); - const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, WARP_SIZE); - { - dpct::has_capability_or_fail(stream->get_device(), - {sycl::aspect::fp16}); - - stream->parallel_for( - sycl::nd_range<3>(block_nums * block_dims, block_dims), - [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(32)]] { - dequantize_mul_mat_vec<QK8_0, QR8_0, dequantize_q8_0>( - vx, y, dst, ncols, nrows, item_ct1); - }); - } -} - -static void dequantize_mul_mat_vec_q2_K_sycl(const void *vx, const float *y, - float *dst, const int ncols, - const int nrows, - dpct::queue_ptr stream) { - GGML_ASSERT(ncols % QK_K == 0); - const int ny = 2; // very slightly faster than 1 even when K_QUANTS_PER_ITERATION = 2 - const int block_num_y = (nrows + ny - 1) / ny; - const sycl::range<3> block_nums(1, 1, block_num_y); - const sycl::range<3> block_dims(1, ny, 32); - stream->parallel_for( - sycl::nd_range<3>(block_nums * block_dims, block_dims), - [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(32)]] { - dequantize_mul_mat_vec_q2_k(vx, y, dst, ncols, nrows, item_ct1); - }); -} - -static void dequantize_mul_mat_vec_q3_K_sycl(const void *vx, const float *y, - float *dst, const int ncols, - const int nrows, - dpct::queue_ptr stream) { - GGML_ASSERT(ncols % QK_K == 0); - const int ny = 2 / K_QUANTS_PER_ITERATION; - const int block_num_y = (nrows + ny - 1) / ny; - const sycl::range<3> block_nums(1, 1, block_num_y); - const sycl::range<3> block_dims(1, ny, 32); - stream->parallel_for( - sycl::nd_range<3>(block_nums * block_dims, block_dims), - [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(32)]] { - dequantize_mul_mat_vec_q3_k(vx, y, dst, ncols, nrows, item_ct1); - }); -} - -static void dequantize_mul_mat_vec_q4_K_sycl(const void *vx, const float *y, - float *dst, const int ncols, - const int nrows, - dpct::queue_ptr stream) { - GGML_ASSERT(ncols % QK_K == 0); - const int ny = 2 / K_QUANTS_PER_ITERATION; - const int block_num_y = (nrows + ny - 1) / ny; - const sycl::range<3> block_nums(1, 1, block_num_y); - const sycl::range<3> block_dims(1, ny, 32); - stream->parallel_for( - sycl::nd_range<3>(block_nums * block_dims, block_dims), - [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(32)]] { - dequantize_mul_mat_vec_q4_k(vx, y, dst, ncols, nrows, item_ct1); - }); -} - -static void dequantize_mul_mat_vec_q5_K_sycl(const void *vx, const float *y, - float *dst, const int ncols, - const int nrows, - dpct::queue_ptr stream) { - GGML_ASSERT(ncols % QK_K == 0); - const sycl::range<3> block_dims(1, 1, 32); - stream->parallel_for( - sycl::nd_range<3>(sycl::range<3>(1, 1, nrows) * block_dims, block_dims), - [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(32)]] { - dequantize_mul_mat_vec_q5_k(vx, y, dst, ncols, item_ct1); - }); -} - -static void dequantize_mul_mat_vec_q6_K_sycl(const void *vx, const float *y, - float *dst, const int ncols, - const int nrows, - dpct::queue_ptr stream) { - GGML_ASSERT(ncols % QK_K == 0); - const int ny = 2 / K_QUANTS_PER_ITERATION; - const int block_num_y = (nrows + ny - 1) / ny; - const sycl::range<3> block_nums(1, 1, block_num_y); - const sycl::range<3> block_dims(1, ny, 32); - stream->parallel_for( - sycl::nd_range<3>(block_nums * block_dims, block_dims), - [=](sycl::nd_item<3> item_ct1) [[intel::reqd_sub_group_size(32)]] { - dequantize_mul_mat_vec_q6_k(vx, y, dst, ncols, nrows, item_ct1); - }); -} - -void ggml_sycl_op_dequantize_mul_mat_vec( - ggml_backend_sycl_context & ctx, - const ggml_tensor *src0, const ggml_tensor *src1, ggml_tensor *dst, - const char *src0_dd_i, const float *src1_ddf_i, const char *src1_ddq_i, - float *dst_dd_i, const int64_t row_low, const int64_t row_high, - const int64_t src1_ncols, const int64_t src1_padded_row_size, - const dpct::queue_ptr &stream) { - - const int64_t ne00 = src0->ne[0]; - const int64_t row_diff = row_high - row_low; - - GGML_ASSERT(src1->type == GGML_TYPE_F32); - // on some GPUs it is faster to convert src1 to half and to use half precision intrinsics -#ifdef GGML_SYCL_F16 - ggml_sycl_pool_alloc<sycl::half> src1_dfloat_a(ctx.pool()); - sycl::half *src1_dfloat = nullptr; // dfloat == half - - bool src1_convert_f16 = - src0->type == GGML_TYPE_Q4_0 || src0->type == GGML_TYPE_Q4_1 || - src0->type == GGML_TYPE_Q5_0 || src0->type == GGML_TYPE_Q5_1 || - src0->type == GGML_TYPE_Q8_0 || src0->type == GGML_TYPE_F16; - - if (src1_convert_f16) { - src1_dfloat = src1_dfloat_a.alloc(ne00); - const to_fp16_sycl_t to_fp16_sycl = ggml_get_to_fp16_sycl(src1->type); - GGML_ASSERT(to_fp16_sycl != nullptr); - to_fp16_sycl(src1_ddf_i, src1_dfloat, ne00, stream); - } -#else - const dfloat * src1_dfloat = (const dfloat *) src1_ddf_i; // dfloat == float, no conversion -#endif // GGML_SYCL_F16 - - switch (src0->type) { - case GGML_TYPE_Q4_0: - dequantize_mul_mat_vec_q4_0_sycl(src0_dd_i, src1_dfloat, dst_dd_i, ne00, row_diff, stream); - break; - case GGML_TYPE_Q4_1: - dequantize_mul_mat_vec_q4_1_sycl(src0_dd_i, src1_dfloat, dst_dd_i, ne00, row_diff, stream); - break; - case GGML_TYPE_Q5_0: - dequantize_mul_mat_vec_q5_0_sycl(src0_dd_i, src1_dfloat, dst_dd_i, ne00, row_diff, stream); - break; - case GGML_TYPE_Q5_1: - dequantize_mul_mat_vec_q5_1_sycl(src0_dd_i, src1_dfloat, dst_dd_i, ne00, row_diff, stream); - break; - case GGML_TYPE_Q8_0: - dequantize_mul_mat_vec_q8_0_sycl(src0_dd_i, src1_dfloat, dst_dd_i, ne00, row_diff, stream); - break; - case GGML_TYPE_Q2_K: - dequantize_mul_mat_vec_q2_K_sycl(src0_dd_i, src1_ddf_i, dst_dd_i, ne00, row_diff, stream); - break; - case GGML_TYPE_Q3_K: - dequantize_mul_mat_vec_q3_K_sycl(src0_dd_i, src1_ddf_i, dst_dd_i, ne00, row_diff, stream); - break; - case GGML_TYPE_Q4_K: - dequantize_mul_mat_vec_q4_K_sycl(src0_dd_i, src1_ddf_i, dst_dd_i, ne00, row_diff, stream); - break; - case GGML_TYPE_Q5_K: - dequantize_mul_mat_vec_q5_K_sycl(src0_dd_i, src1_ddf_i, dst_dd_i, ne00, row_diff, stream); - break; - case GGML_TYPE_Q6_K: - dequantize_mul_mat_vec_q6_K_sycl(src0_dd_i, src1_ddf_i, dst_dd_i, ne00, row_diff, stream); - break; - case GGML_TYPE_F16: - convert_mul_mat_vec_f16_sycl(src0_dd_i, src1_dfloat, dst_dd_i, ne00, row_diff, stream); - break; - default: - printf("ggml_sycl_op_dequantize_mul_mat_vec unsupported GGML_TYPE %d\n", src0->type); - GGML_ASSERT(false); - break; - } - - (void) src1; - (void) dst; - (void) src1_ddq_i; - (void) src1_ncols; - (void) src1_padded_row_size; -} |