diff --git a/ggml/src/ggml-cuda/iqk_mmvq.cu b/ggml/src/ggml-cuda/iqk_mmvq.cu index 842174b3..88eb798a 100644 --- a/ggml/src/ggml-cuda/iqk_mmvq.cu +++ b/ggml/src/ggml-cuda/iqk_mmvq.cu @@ -21,6 +21,9 @@ struct ggml_cuda_type_traits { // constexpr int qi = ggml_cuda_type_traits::qi; // constexpr int vdr = get_vdr_mmvq(type); +// QI4_XS = 256/(4*2) = 32 +// vdr = 4, qi = 32 -> qi/vdr = 8, kqs = 4*(tid%8), blocks_per_iter = 4*1*32/32 = 4 +// vdr = 2, qi = 32 -> qi/vdr =16, kqs = 2*(tid%16), blocks_per_iter = 2*1*32/32 = 2 namespace { template __device__ void iqk_mul_mat_vec_q( @@ -254,39 +257,34 @@ static __device__ __forceinline__ int2 get_int_from_table_16(const int & q4, con return make_int2(*((const int *) &val0_8), *((const int *) &val1_8)); } -// TODO __device__ __forceinline__ void vec_dot_iq4_k_r4_q8_1( const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & kbx, const int & iqs, float * result) { const block_iq4_k_r4 * bq4 = (const block_iq4_k_r4 *)vbq + kbx; - // iqs is 0...28 - const int ib32 = iqs/4; - const float d8 = __low2float(bq8_1[ib32].ds); - const int32_t * q8 = (const int *)bq8_1[ib32].qs; + // iqs is 0...28 in steps of 2 + const int ib16 = iqs/2; + const float d8 = __low2float(bq8_1[ib16/2].ds); + const int32_t * q8 = (const int *)bq8_1[ib16/2].qs + 4*(ib16%2); - int scales[2]; + int ib32 = ib16/2; + int is = ib16%2; + int scales; const uint32_t * scales_l = (const uint32_t *)bq4->scales_l; const uint32_t * scales_h = (const uint32_t *)bq4->scales_h; - scales[0] = __vsub4(((scales_l[2*(ib32%4)+0] >> 4*(ib32/4)) & 0x0f0f0f0f) | (((scales_h[2*(ib32%2)+0] >> 2*(ib32/2)) & 0x03030303) << 4), 0x20202020); - scales[1] = __vsub4(((scales_l[2*(ib32%4)+1] >> 4*(ib32/4)) & 0x0f0f0f0f) | (((scales_h[2*(ib32%2)+1] >> 2*(ib32/2)) & 0x03030303) << 4), 0x20202020); - const int8_t * s8 = (const int8_t *)scales; + scales = __vsub4(((scales_l[2*(ib32%4)+is] >> 4*(ib32/4)) & 0x0f0f0f0f) | (((scales_h[2*(ib32%2)+is] >> 2*(ib32/2)) & 0x03030303) << 4), 0x20202020); + const int8_t * s8 = (const int8_t *)&scales; int2 val1, val2; const int * q4 = (const int *)bq4->qs + 16*ib32; for (int i = 0; i < 4; ++i) { - auto values1 = iq4k_values + (((bq4->extra[i+0] >> ib32) & 1) << 4); - auto values2 = iq4k_values + (((bq4->extra[i+4] >> ib32) & 1) << 4); - int sumi1 = 0, sumi2 = 0; - val1 = get_int_from_table_16(q4[i+ 0], values1); + auto values1 = iq4k_values + (((bq4->extra[i+4*is] >> ib32) & 1) << 4); + int sumi1 = 0; + val1 = get_int_from_table_16(q4[i+4*is+0], values1); sumi1 = ggml_cuda_dp4a(val1.x, q8[0], ggml_cuda_dp4a(val1.y, q8[2], sumi1)); - val2 = get_int_from_table_16(q4[i+ 4], values2); - sumi2 = ggml_cuda_dp4a(val2.x, q8[4], ggml_cuda_dp4a(val2.y, q8[6], sumi2)); - val1 = get_int_from_table_16(q4[i+ 8], values1); + val1 = get_int_from_table_16(q4[i+4*is+8], values1); sumi1 = ggml_cuda_dp4a(val1.x, q8[1], ggml_cuda_dp4a(val1.y, q8[3], sumi1)); - val2 = get_int_from_table_16(q4[i+12], values2); - sumi2 = ggml_cuda_dp4a(val2.x, q8[5], ggml_cuda_dp4a(val2.y, q8[7], sumi2)); const float d = __half2float(bq4->d[i]) * d8; - result[i] += d * (sumi1 * s8[i] + sumi2 * s8[i+4]); + result[i] += d * sumi1 * s8[i]; } } @@ -863,7 +861,7 @@ void mul_mat_vec_iq4_k_r4_q8_1_cuda( const int ncols_x, const int nrows_x, const int nrows_y, const int ncols_y, const int nrows_dst, const int ne2, const uint64_t nb02, const uint64_t nb12, const uint64_t nb2, int64_t ids_nb0, cudaStream_t stream) { - iqk_mul_mat_vec_q_cuda(vx, vy, dst, ids_data, ncols_x, nrows_x, nrows_y, ncols_y, nrows_dst, ne2, nb02, nb12, nb2, ids_nb0, stream); + iqk_mul_mat_vec_q_cuda(vx, vy, dst, ids_data, ncols_x, nrows_x, nrows_y, ncols_y, nrows_dst, ne2, nb02, nb12, nb2, ids_nb0, stream); } void mul_mat_vec_iq4_ks_q8_1_cuda(