#include "mmvq.hpp"
#include "vecdotq.hpp"
-
+#include <cassert>
template <int qk, int qi, typename block_q_t, int vdr, vec_dot_q_sycl_t vec_dot_q_sycl>
static void mul_mat_vec_q(const void * __restrict__ vx, const void * __restrict__ vy, float * __restrict__ dst, const int ncols, const int nrows,
}
const int blocks_per_row = ncols / qk;
- const int blocks_per_warp = vdr * WARP_SIZE / qi;
+ const int blocks_per_warp = vdr * QK_WARP_SIZE / qi;
+ assert(blocks_per_warp>0);
// partial sum for each thread
float tmp = 0.0f;
// sum up partial sums and write back result
#pragma unroll
- for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
+ for (int mask = QK_WARP_SIZE / 2; mask > 0; mask >>= 1) {
tmp +=
dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
}
}
const int blocks_per_row = ncols / qk;
- const int blocks_per_warp = vdr * WARP_SIZE / qi;
+ const int blocks_per_warp = vdr * QK_WARP_SIZE / qi;
+ assert(blocks_per_warp>0);
// partial sum for each thread
float tmp = 0.0f;
// sum up partial sums and write back result
#pragma unroll
- for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
+ for (int mask = QK_WARP_SIZE / 2; mask > 0; mask >>= 1) {
tmp +=
dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
}
}
const int blocks_per_row = ncols / qk;
- const int blocks_per_warp = vdr * WARP_SIZE / qi;
-
+ const int blocks_per_warp = vdr * QK_WARP_SIZE / qi;
+ assert(blocks_per_warp>0);
// partial sum for each thread
float tmp = 0.0f;
// sum up partial sums and write back result
#pragma unroll
- for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
+ for (int mask = QK_WARP_SIZE / 2; mask > 0; mask >>= 1) {
tmp +=
dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
}
}
const int blocks_per_row = ncols / qk;
- const int blocks_per_warp = vdr * WARP_SIZE / qi;
-
+ const int blocks_per_warp = vdr * QK_WARP_SIZE / qi;
+ assert(blocks_per_warp>0);
// partial sum for each thread
float tmp = 0.0f;
// sum up partial sums and write back result
#pragma unroll
- for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
+ for (int mask = QK_WARP_SIZE / 2; mask > 0; mask >>= 1) {
tmp +=
dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
}
}
const int blocks_per_row = ncols / qk;
- const int blocks_per_warp = vdr * WARP_SIZE / qi;
-
+ const int blocks_per_warp = vdr * QK_WARP_SIZE / qi;
+ assert(blocks_per_warp>0);
// partial sum for each thread
float tmp = 0.0f;
// sum up partial sums and write back result
#pragma unroll
- for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
+ for (int mask = QK_WARP_SIZE / 2; mask > 0; mask >>= 1) {
tmp +=
dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
}
}
const int blocks_per_row = ncols / qk;
- const int blocks_per_warp = vdr * WARP_SIZE / qi;
-
+ const int blocks_per_warp = vdr * QK_WARP_SIZE / qi;
+ assert(blocks_per_warp>0);
// partial sum for each thread
float tmp = 0.0f;
// sum up partial sums and write back result
#pragma unroll
- for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
+ for (int mask = QK_WARP_SIZE / 2; mask > 0; mask >>= 1) {
tmp +=
dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
}
}
const int blocks_per_row = ncols / qk;
- const int blocks_per_warp = vdr * WARP_SIZE / qi;
-
+ const int blocks_per_warp = vdr * QK_WARP_SIZE / qi;
+ assert(blocks_per_warp>0);
// partial sum for each thread
float tmp = 0.0f;
// sum up partial sums and write back result
#pragma unroll
- for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
+ for (int mask = QK_WARP_SIZE / 2; mask > 0; mask >>= 1) {
tmp +=
dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
}
}
const int blocks_per_row = ncols / qk;
- const int blocks_per_warp = vdr * WARP_SIZE / qi;
-
+ const int blocks_per_warp = vdr * QK_WARP_SIZE / qi;
+ assert(blocks_per_warp>0);
// partial sum for each thread
float tmp = 0.0f;
// sum up partial sums and write back result
#pragma unroll
- for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
+ for (int mask = QK_WARP_SIZE / 2; mask > 0; mask >>= 1) {
tmp +=
dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
}
}
const int blocks_per_row = ncols / qk;
- const int blocks_per_warp = vdr * WARP_SIZE / qi;
-
+ const int blocks_per_warp = vdr * QK_WARP_SIZE / qi;
+ assert(blocks_per_warp>0);
// partial sum for each thread
float tmp = 0.0f;
// sum up partial sums and write back result
#pragma unroll
- for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
+ for (int mask = QK_WARP_SIZE / 2; mask > 0; mask >>= 1) {
tmp +=
dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
}
}
const int blocks_per_row = ncols / qk;
- const int blocks_per_warp = vdr * WARP_SIZE / qi;
-
+ const int blocks_per_warp = vdr * QK_WARP_SIZE / qi;
+ assert(blocks_per_warp>0);
// partial sum for each thread
float tmp = 0.0f;
// sum up partial sums and write back result
#pragma unroll
- for (int mask = WARP_SIZE / 2; mask > 0; mask >>= 1) {
+ for (int mask = QK_WARP_SIZE / 2; mask > 0; mask >>= 1) {
tmp +=
dpct::permute_sub_group_by_xor(item_ct1.get_sub_group(), tmp, mask);
}
GGML_ASSERT(ncols % QK4_0 == 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);
+ const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, QK_WARP_SIZE);
{
stream->submit([&](sycl::handler &cgh) {
cgh.parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1)
- [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+ [[intel::reqd_sub_group_size(QK_WARP_SIZE)]] {
mul_mat_vec_q<QK4_0, QI4_0, block_q4_0,
VDR_Q4_0_Q8_1_MMVQ, vec_dot_q4_0_q8_1>(
vx, vy, dst, ncols, nrows, item_ct1);
GGML_ASSERT(ncols % QK4_1 == 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);
+ const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, QK_WARP_SIZE);
{
stream->submit([&](sycl::handler &cgh) {
cgh.parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1)
- [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+ [[intel::reqd_sub_group_size(QK_WARP_SIZE)]] {
mul_mat_vec_q<QK4_0, QI4_1, block_q4_1,
VDR_Q4_1_Q8_1_MMVQ, vec_dot_q4_1_q8_1>(
vx, vy, dst, ncols, nrows, item_ct1);
GGML_ASSERT(ncols % QK5_0 == 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);
+ const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, QK_WARP_SIZE);
{
stream->submit([&](sycl::handler &cgh) {
cgh.parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1)
- [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+ [[intel::reqd_sub_group_size(QK_WARP_SIZE)]] {
mul_mat_vec_q<QK5_0, QI5_0, block_q5_0,
VDR_Q5_0_Q8_1_MMVQ, vec_dot_q5_0_q8_1>(
vx, vy, dst, ncols, nrows, item_ct1);
GGML_ASSERT(ncols % QK5_1 == 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);
+ const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, QK_WARP_SIZE);
{
stream->submit([&](sycl::handler &cgh) {
cgh.parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1)
- [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+ [[intel::reqd_sub_group_size(QK_WARP_SIZE)]] {
mul_mat_vec_q<QK5_1, QI5_1, block_q5_1,
VDR_Q5_1_Q8_1_MMVQ, vec_dot_q5_1_q8_1>(
vx, vy, dst, ncols, nrows, item_ct1);
GGML_ASSERT(ncols % QK8_0 == 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);
+ const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, QK_WARP_SIZE);
{
stream->submit([&](sycl::handler &cgh) {
cgh.parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1)
- [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+ [[intel::reqd_sub_group_size(QK_WARP_SIZE)]] {
mul_mat_vec_q<QK8_0, QI8_0, block_q8_0,
VDR_Q8_0_Q8_1_MMVQ, vec_dot_q8_0_q8_1>(
vx, vy, dst, ncols, nrows, item_ct1);
GGML_ASSERT(ncols % QK_K == 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);
+ const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, QK_WARP_SIZE);
{
stream->submit([&](sycl::handler &cgh) {
cgh.parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1)
- [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+ [[intel::reqd_sub_group_size(QK_WARP_SIZE)]] {
mul_mat_vec_q<QK_K, QI2_K, block_q2_K,
VDR_Q2_K_Q8_1_MMVQ, vec_dot_q2_K_q8_1>(
vx, vy, dst, ncols, nrows, item_ct1);
GGML_ASSERT(ncols % QK_K == 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);
+ const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, QK_WARP_SIZE);
{
stream->submit([&](sycl::handler &cgh) {
cgh.parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1)
- [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+ [[intel::reqd_sub_group_size(QK_WARP_SIZE)]] {
mul_mat_vec_q<QK_K, QI3_K, block_q3_K,
VDR_Q3_K_Q8_1_MMVQ, vec_dot_q3_K_q8_1>(
vx, vy, dst, ncols, nrows, item_ct1);
GGML_ASSERT(ncols % QK_K == 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);
+ const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, QK_WARP_SIZE);
{
stream->submit([&](sycl::handler &cgh) {
cgh.parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1)
- [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+ [[intel::reqd_sub_group_size(QK_WARP_SIZE)]] {
mul_mat_vec_q<QK_K, QI4_K, block_q4_K,
VDR_Q4_K_Q8_1_MMVQ, vec_dot_q4_K_q8_1>(
vx, vy, dst, ncols, nrows, item_ct1);
GGML_ASSERT(ncols % QK_K == 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);
+ const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, QK_WARP_SIZE);
{
stream->submit([&](sycl::handler &cgh) {
cgh.parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1)
- [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+ [[intel::reqd_sub_group_size(QK_WARP_SIZE)]] {
mul_mat_vec_q<QK_K, QI5_K, block_q5_K,
VDR_Q5_K_Q8_1_MMVQ, vec_dot_q5_K_q8_1>(
vx, vy, dst, ncols, nrows, item_ct1);
GGML_ASSERT(ncols % QK_K == 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);
+ const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, QK_WARP_SIZE);
{
stream->submit([&](sycl::handler &cgh) {
cgh.parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1)
- [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+ [[intel::reqd_sub_group_size(QK_WARP_SIZE)]] {
mul_mat_vec_q<QK_K, QI6_K, block_q6_K,
VDR_Q6_K_Q8_1_MMVQ, vec_dot_q6_K_q8_1>(
vx, vy, dst, ncols, nrows, item_ct1);
GGML_ASSERT(ncols % QK_K == 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);
+ const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, QK_WARP_SIZE);
{
stream->submit([&](sycl::handler &cgh) {
cgh.parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1)
- [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+ [[intel::reqd_sub_group_size(QK_WARP_SIZE)]] {
mul_mat_vec_q_iq2_xxs_q8_1<QK_K, QI2_XXS/2, block_iq2_xxs, 1>(
vx, vy, dst, ncols, nrows, item_ct1);
});
GGML_ASSERT(ncols % QK_K == 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);
+ const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, QK_WARP_SIZE);
{
stream->submit([&](sycl::handler &cgh) {
cgh.parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1)
- [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+ [[intel::reqd_sub_group_size(QK_WARP_SIZE)]] {
mul_mat_vec_q_iq2_xs_q8_1<QK_K, QI2_XS/2, block_iq2_xs, 1>(
vx, vy, dst, ncols, nrows, item_ct1);
});
GGML_ASSERT(ncols % QK_K == 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);
+ const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, QK_WARP_SIZE);
{
stream->submit([&](sycl::handler &cgh) {
cgh.parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1)
- [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+ [[intel::reqd_sub_group_size(QK_WARP_SIZE)]] {
mul_mat_vec_q_iq2_s_q8_1<QK_K, QI2_S/2, block_iq2_s, 1>(
vx, vy, dst, ncols, nrows, item_ct1);
});
GGML_ASSERT(ncols % QK_K == 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);
+ const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, QK_WARP_SIZE);
{
stream->submit([&](sycl::handler &cgh) {
cgh.parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1)
- [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+ [[intel::reqd_sub_group_size(QK_WARP_SIZE)]] {
mul_mat_vec_q_iq3_xxs_q8_1<QK_K, QI3_XXS/2, block_iq3_xxs, 1>(
vx, vy, dst, ncols, nrows, item_ct1);
});
GGML_ASSERT(ncols % QK_K == 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);
+ const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, QK_WARP_SIZE);
{
stream->submit([&](sycl::handler &cgh) {
cgh.parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1)
- [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+ [[intel::reqd_sub_group_size(QK_WARP_SIZE)]] {
mul_mat_vec_q_iq3_s_q8_1<QK_K, QI3_S/2, block_iq3_s, 1>(
vx, vy, dst, ncols, nrows, item_ct1);
});
GGML_ASSERT(ncols % QK_K == 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);
+ const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, QK_WARP_SIZE);
{
stream->submit([&](sycl::handler &cgh) {
cgh.parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1)
- [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+ [[intel::reqd_sub_group_size(QK_WARP_SIZE)]] {
mul_mat_vec_q_iq1_s_q8_1<QK_K, QI1_S, block_iq1_s, 1>(
vx, vy, dst, ncols, nrows, item_ct1);
});
GGML_ASSERT(ncols % QK_K == 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);
+ const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, QK_WARP_SIZE);
{
stream->submit([&](sycl::handler &cgh) {
cgh.parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1)
- [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+ [[intel::reqd_sub_group_size(QK_WARP_SIZE)]] {
mul_mat_vec_q_iq1_m_q8_1<QK_K, QI1_S, block_iq1_m, 1>(
vx, vy, dst, ncols, nrows, item_ct1);
});
GGML_ASSERT(ncols % QK4_NL == 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);
+ const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, QK_WARP_SIZE);
{
stream->submit([&](sycl::handler &cgh) {
cgh.parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1)
- [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+ [[intel::reqd_sub_group_size(QK_WARP_SIZE)]] {
mul_mat_vec_q_iq4_nl_q8_1<QK4_NL, QI4_NL, block_iq4_nl, 2>(
vx, vy, dst, ncols, nrows, item_ct1);
});
GGML_ASSERT(ncols % QK_K == 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);
+ const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, QK_WARP_SIZE);
{
stream->submit([&](sycl::handler &cgh) {
cgh.parallel_for(
sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> item_ct1)
- [[intel::reqd_sub_group_size(WARP_SIZE)]] {
+ [[intel::reqd_sub_group_size(QK_WARP_SIZE)]] {
mul_mat_vec_q_iq4_xs_q8_1<QK_K, QI4_XS/4, block_iq4_xs, 1>(
vx, vy, dst, ncols, nrows, item_ct1);
});