#include "../iqk_mmvq_templates.cuh" __device__ __forceinline__ void vec_dot_iq1_bn_q8_1( const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & kbx, const int & iqs, float * result) { half d16; memcpy(&d16, vbq, sizeof(d16)); float scale = d16; const block_iq1_bn * bq1 = (const block_iq1_bn *)((const char *)vbq + sizeof(d16)) + kbx; // iqs is 0 or 1 int sumi = 0; #if __CUDA_ARCH__ >= MIN_CC_DP4A // lowest compute capability for integer intrinsics uint16_t mult[2]; mult[1] = iqs == 0 ? 27 : 3; mult[0] = mult[1] + (mult[1] << 1); const int * q8 = (const int *)bq8_1[iqs].qs; int val[4]; for (int l = 0; l < 2; ++l) { int8_t * a = (int8_t *)val; const int i16 = 2*iqs + l; for (int k = 0; k < 3; ++k) { uint16_t q = bq1->ql[3*i16+k]; for (int j = 4; j >= 0; --j) { uint16_t v = q & 0xff; v += v << 1; a[j] = v >> 8; q += q << 1; } a += 5; } uint16_t v = (mult[l]*bq1->extra) & 0xff; v += v << 1; *a = v >> 8; sumi = ggml_cuda_dp4a(val[0], q8[4*l+0], ggml_cuda_dp4a(val[1], q8[4*l+1], ggml_cuda_dp4a(val[2], q8[4*l+2], ggml_cuda_dp4a(val[3], q8[4*l+3], sumi)))); } float2 d8 = __half22float2(bq8_1[iqs].ds); *result += scale * (d8.x * sumi - d8.y); #else static const uint16_t k_mult[5] = {81, 27, 9, 3, 1}; const int8_t * q8 = bq8_1[iqs].qs; for (int l = 0; l < 2; ++l) { const int i16 = 2*iqs + l; for (int k = 0; k < 3; ++k) { uint8_t q = bq1->ql[3*i16+k]; for (int j = 0; j < 5; ++j) { uint8_t v = k_mult[j]*q; int8_t vs = (v + (v >> 1)) >> 7; sumi += q8[j]*(vs - 1); } q8 += 5; } uint8_t v = k_mult[i16]*bq1->extra; int8_t vs = (v + (v >> 1)) >> 7; sumi += q8[0]*(vs - 1); q8++; } *result += scale * __low2float(bq8_1[iqs].ds) * sumi; #endif } void mul_mat_vec_iq1_bn_q8_1_cuda(const mmvq_args & args, cudaStream_t stream) { iqk_mul_mat_vec_q_cuda(args, stream); }