ikawrakow/ik_llama.cpp
1
0
Fork 0
mirror of https://github.com/ikawrakow/ik_llama.cpp.git synced 2026-03-07 20:40:02 +00:00
Code Issues Packages Projects Releases Wiki Activity

iq2_k: CUDA dot product finally works

Browse Source 
Performance is pathetic: 140 t/s for LLaMA-3.1-8B vs
172 t/s for iq2_xs.
This commit is contained in:
Iwan Kawrakow
2024-07-30 12:33:48 +03:00
committed by Kawrakow
parent 69842c6ad8
commit ab4f9e1fdb
1 changed files with 55 additions and 24 deletions
Download Patch File Download Diff File Expand all files Collapse all files

79
ggml/src/ggml-cuda/iqk_mmvq.cu
View File

@@ -251,30 +251,61 @@ __device__ __forceinline__ float vec_dot_iq5_k_q8_1(
// TODO
__device__ __forceinline__ float vec_dot_iq2_k_q8_1(
const void * __restrict__ vbq, const block_q8_1 * __restrict__ bq8_1, const int & kbx, const int & iqs) {
return 0;
//
// const block_iq2_k * bq4 = (const block_iq2_k *) vbq + kbx;
// const uint8_t * all_values = (const uint8_t *)iq4k_values;
//
// // iqs is 0...28
// const int ib32 = iqs/4;
// // Why iqs/4 ?
// const int32_t * q8 = (const int *)bq8_1[ib32].qs;
// const uint16_t * q4 = (const uint16_t *)bq4->qs + 8*ib32;
// const uint16_t extra = bq4->extra >> 2*ib32;
// int v1, v2;
// int sumi1 = 0, sumi2 = 0;
// for (int j = 0; j < 4; ++j) {
// const uint32_t aux32 = q4[2*j+0] | (q4[2*j+1] << 16);
// get_int_from_table_16_shift(aux32, extra, all_values, v1, v2);
// sumi1 = ggml_cuda_dp4a(v1, q8[j+0], sumi1);
// sumi2 = ggml_cuda_dp4a(v2, q8[j+4], sumi2);
// }
// const float d = __half2float(bq4->d) * __low2float(bq8_1[ib32].ds);
// const uint8_t sh = bq4->scales_h[ib32/2] >> 4*(ib32%2);
// const int ls1 = ((bq4->scales_l[ib32] & 0xf) | ((sh << 4) & 0x30)) - 32;
// const int ls2 = ((bq4->scales_l[ib32] >> 4) | ((sh << 2) & 0x30)) - 32;
// return d * (sumi1 * ls1 + sumi2 * ls2);
// iqs is 0, 4, 8, 12, 16, 20, 24, 28
// we have 16 packed quants (when cast to int)
int i4 = iqs/4; // 0...7. We will process q8 blocks 4*(i4/4), 4*(i4/4)+1, 4*(i4/4)+2, 4*(i4/4)+3
const int32_t * q8_1 = (const int *)bq8_1[4*(i4/4)+0].qs + 2*(i4%4);
const int32_t * q8_2 = (const int *)bq8_1[4*(i4/4)+1].qs + 2*(i4%4);
const int32_t * q8_3 = (const int *)bq8_1[4*(i4/4)+2].qs + 2*(i4%4);
const int32_t * q8_4 = (const int *)bq8_1[4*(i4/4)+3].qs + 2*(i4%4);
const block_iq2_k * bq2 = (const block_iq2_k *) vbq + kbx;
const uint32_t * q2 = (const uint32_t *)bq2->qs + 8*(i4/4) + 2*(i4%4);
const uint16_t extra = bq2->extra >> (8*(i4/4) + (i4%4)/2);
const uint8_t * all_values = (const uint8_t *)iq2nl_values;
const uint8_t * values;
uint32_t val1 = q2[0], val2 = q2[1];
uint32_t aux32[2];
const uint8_t * a8 = (const uint8_t *)&aux32;
int v1, v2, ls;
// Block of 16: (32*(4*(i4/4)+k)+8*(i4%4))/16 = 8*(i4/4) + 2*k + (i4%4)/2
// -> scales_l[4*(i4/4) + k] >> 4*(((i4%4)/2)%2)
ls = (bq2->scales[4*(i4/4) + 0] >> 4*(((i4%4)/2)%2)) & 0xf;
aux32[0] = ((val1 >> 0) & 0x03030303); aux32[1] = ((val2 >> 0) & 0x03030303); values = all_values + ((extra & 0x01) << 2);
v1 = int_from_table(a8 + 0, values);
v2 = int_from_table(a8 + 4, values);
int sumi1 = ggml_cuda_dp4a(v2, q8_1[1], ggml_cuda_dp4a(v1, q8_1[0], 0)) * (2*ls - 15);
ls = (bq2->scales[4*(i4/4) + 1] >> 4*(((i4%4)/2)%2)) & 0xf;
aux32[0] = ((val1 >> 2) & 0x03030303); aux32[1] = ((val2 >> 2) & 0x03030303); values = all_values + ((extra & 0x04) << 0);
v1 = int_from_table(a8 + 0, values);
v2 = int_from_table(a8 + 4, values);
int sumi2 = ggml_cuda_dp4a(v2, q8_2[1], ggml_cuda_dp4a(v1, q8_2[0], 0)) * (2*ls - 15);
ls = (bq2->scales[4*(i4/4) + 2] >> 4*(((i4%4)/2)%2)) & 0xf;
aux32[0] = ((val1 >> 4) & 0x03030303); aux32[1] = ((val2 >> 4) & 0x03030303); values = all_values + ((extra & 0x10) >> 2);
v1 = int_from_table(a8 + 0, values);
v2 = int_from_table(a8 + 4, values);
int sumi3 = ggml_cuda_dp4a(v2, q8_3[1], ggml_cuda_dp4a(v1, q8_3[0], 0)) * (2*ls - 15);
ls = (bq2->scales[4*(i4/4) + 3] >> 4*(((i4%4)/2)%2)) & 0xf;
aux32[0] = ((val1 >> 6) & 0x03030303); aux32[1] = ((val2 >> 6) & 0x03030303); values = all_values + ((extra & 0x40) >> 4);
v1 = int_from_table(a8 + 0, values);
v2 = int_from_table(a8 + 4, values);
int sumi4 = ggml_cuda_dp4a(v2, q8_4[1], ggml_cuda_dp4a(v1, q8_4[0], 0)) * (2*ls - 15);
return __half2float(bq2->d) * (__low2float(bq8_1[4*(i4/4)+0].ds) * sumi1
+ __low2float(bq8_1[4*(i4/4)+1].ds) * sumi2
+ __low2float(bq8_1[4*(i4/4)+2].ds) * sumi3
+ __low2float(bq8_1[4*(i4/4)+3].ds) * sumi4);
}
}