upstream-archive/whisper.cpp
1
0
Fork 0
mirror of https://github.com/ggml-org/whisper.cpp.git synced 2026-07-23 11:10:57 -05:00
Code Issues Packages Projects Releases Wiki Activity

sycl : fix reorder function; add fp32/fp16 in build script (llama/24578)

Browse Source
This commit is contained in:
Neo Zhang
2026-06-15 15:08:34 +08:00
committed by Georgi Gerganov
parent d20057908a
commit e958dcead1
1 changed files with 63 additions and 67 deletions
Download Patch File Download Diff File Expand all files Collapse all files

130
ggml/src/ggml-sycl/mmvq.cpp
View File

@@ -662,13 +662,12 @@ static void reorder_mul_mat_vec_q4_0_q8_1_sycl(const void * vx, const void * vy,
GGML_ASSERT(ncols % QK4_0 == 0);
// Round up to a whole number of subgroup-sized workgroups; out-of-range rows are skipped inside the kernel.
constexpr size_t num_subgroups = WARP_SIZE;
const int block_num_y = ceil_div(nrows, GGML_SYCL_MMV_Y * (int) num_subgroups) * (int) num_subgroups;
const sycl::range<3> global_size(1, GGML_SYCL_MMV_Y, (block_num_y * WARP_SIZE));
const sycl::range<3> workgroup_size(1, GGML_SYCL_MMV_Y, num_subgroups * WARP_SIZE);
const int block_num_y = ceil_div(nrows, GGML_SYCL_MMV_Y * (int) num_subgroups);
const sycl::range<3> block_nums(1, 1, block_num_y);
const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, num_subgroups * WARP_SIZE);
stream->submit([&](sycl::handler & cgh) {
cgh.parallel_for(sycl::nd_range<3>(global_size, workgroup_size),
cgh.parallel_for(sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> nd_item) [[sycl::reqd_sub_group_size(WARP_SIZE)]] {
mul_mat_vec_q_reorder<reorder_vec_dot_q_sycl<GGML_TYPE_Q4_0>>(vx, vy, dst, ncols, nrows,
nd_item);
@@ -683,13 +682,13 @@ static void reorder_mul_mat_vec_q4_0_q8_1_sycl_ncols(
const int stride_col_y_bytes, const int stride_col_dst,
dpct::queue_ptr stream) {
GGML_ASSERT(ncols % QK4_0 == 0);
const int block_num_y = ceil_div(nrows, GGML_SYCL_MMV_Y);
constexpr size_t num_subgroups = 16;
GGML_ASSERT(block_num_y % num_subgroups == 0);
const sycl::range<3> global_size(1, GGML_SYCL_MMV_Y, block_num_y * WARP_SIZE);
const sycl::range<3> workgroup_size(1, GGML_SYCL_MMV_Y, num_subgroups * WARP_SIZE);
constexpr size_t num_subgroups = WARP_SIZE;
const int block_num_y = ceil_div(nrows, GGML_SYCL_MMV_Y * (int) num_subgroups);
const sycl::range<3> block_nums(1, 1, block_num_y);
const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, num_subgroups * WARP_SIZE);
stream->submit([&](sycl::handler & cgh) {
cgh.parallel_for(sycl::nd_range<3>(global_size, workgroup_size),
cgh.parallel_for(sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> nd_item) [[sycl::reqd_sub_group_size(WARP_SIZE)]] {
mul_mat_vec_q_reorder_ncols<reorder_vec_dot_q_sycl<GGML_TYPE_Q4_0>, ncols_dst>(
vx, vy, dst, ncols, nrows, stride_col_y_bytes, stride_col_dst, nd_item);
@@ -1080,13 +1079,12 @@ static void reorder_mul_mat_vec_q8_0_q8_1_sycl(const void * vx, const void * vy,
GGML_ASSERT(ncols % QK8_0 == 0);
// Round up to a whole number of subgroup-sized workgroups; out-of-range rows are skipped inside the kernel.
constexpr size_t num_subgroups = WARP_SIZE;
const int block_num_y = ceil_div(nrows, GGML_SYCL_MMV_Y * (int) num_subgroups) * (int) num_subgroups;
const sycl::range<3> global_size(1, GGML_SYCL_MMV_Y, (block_num_y * WARP_SIZE));
const sycl::range<3> workgroup_size(1, GGML_SYCL_MMV_Y, num_subgroups * WARP_SIZE);
const int block_num_y = ceil_div(nrows, GGML_SYCL_MMV_Y * (int) num_subgroups);
const sycl::range<3> block_nums(1, 1, block_num_y);
const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, num_subgroups * WARP_SIZE);
stream->submit([&](sycl::handler & cgh) {
cgh.parallel_for(sycl::nd_range<3>(global_size, workgroup_size),
cgh.parallel_for(sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> nd_item) [[sycl::reqd_sub_group_size(WARP_SIZE)]] {
mul_mat_vec_q_reorder<reorder_vec_dot_q_sycl<GGML_TYPE_Q8_0>>(vx, vy, dst, ncols, nrows,
nd_item);
@@ -1101,13 +1099,13 @@ static void reorder_mul_mat_vec_q8_0_q8_1_sycl_ncols(
const int stride_col_y_bytes, const int stride_col_dst,
dpct::queue_ptr stream) {
GGML_ASSERT(ncols % QK8_0 == 0);
const int block_num_y = ceil_div(nrows, GGML_SYCL_MMV_Y);
constexpr size_t num_subgroups = 16;
GGML_ASSERT(block_num_y % num_subgroups == 0);
const sycl::range<3> global_size(1, GGML_SYCL_MMV_Y, block_num_y * WARP_SIZE);
const sycl::range<3> workgroup_size(1, GGML_SYCL_MMV_Y, num_subgroups * WARP_SIZE);
constexpr size_t num_subgroups = WARP_SIZE;
const int block_num_y = ceil_div(nrows, GGML_SYCL_MMV_Y * (int) num_subgroups);
const sycl::range<3> block_nums(1, 1, block_num_y);
const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, num_subgroups * WARP_SIZE);
stream->submit([&](sycl::handler & cgh) {
cgh.parallel_for(sycl::nd_range<3>(global_size, workgroup_size),
cgh.parallel_for(sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> nd_item) [[sycl::reqd_sub_group_size(WARP_SIZE)]] {
mul_mat_vec_q_reorder_ncols<reorder_vec_dot_q_sycl<GGML_TYPE_Q8_0>, ncols_dst>(
vx, vy, dst, ncols, nrows, stride_col_y_bytes, stride_col_dst, nd_item);
@@ -1289,13 +1287,12 @@ static void reorder_mul_mat_vec_q3_k_q8_1_sycl(const void * vx, const void * vy,
// Round up to a whole number of subgroup-sized workgroups; out-of-range rows are skipped inside the kernel.
constexpr size_t num_subgroups = WARP_SIZE;
const int block_num_y = ceil_div(nrows, GGML_SYCL_MMV_Y * (int) num_subgroups) * (int) num_subgroups;
const sycl::range<3> global_size(1, GGML_SYCL_MMV_Y, block_num_y * WARP_SIZE);
const sycl::range<3> workgroup_size(1, GGML_SYCL_MMV_Y, num_subgroups * WARP_SIZE);
const int block_num_y = ceil_div(nrows, GGML_SYCL_MMV_Y * (int) num_subgroups);
const sycl::range<3> block_nums(1, 1, block_num_y);
const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, num_subgroups * WARP_SIZE);
stream->submit([&](sycl::handler & cgh) {
cgh.parallel_for(sycl::nd_range<3>(global_size, workgroup_size),
cgh.parallel_for(sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> nd_item) [[sycl::reqd_sub_group_size(WARP_SIZE)]] {
mul_mat_vec_q_reorder<reorder_vec_dot_q_sycl<GGML_TYPE_Q3_K>>(vx, vy, dst, ncols, nrows,
nd_item);
@@ -1310,13 +1307,13 @@ static void reorder_mul_mat_vec_q3_k_q8_1_sycl_ncols(
const int stride_col_y_bytes, const int stride_col_dst,
dpct::queue_ptr stream) {
GGML_ASSERT(ncols % QK_K == 0);
const int block_num_y = ceil_div(nrows, GGML_SYCL_MMV_Y);
constexpr size_t num_subgroups = 16;
GGML_ASSERT(block_num_y % num_subgroups == 0);
const sycl::range<3> global_size(1, GGML_SYCL_MMV_Y, block_num_y * WARP_SIZE);
const sycl::range<3> workgroup_size(1, GGML_SYCL_MMV_Y, num_subgroups * WARP_SIZE);
constexpr size_t num_subgroups = WARP_SIZE;
const int block_num_y = ceil_div(nrows, GGML_SYCL_MMV_Y * (int) num_subgroups);
const sycl::range<3> block_nums(1, 1, block_num_y);
const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, num_subgroups * WARP_SIZE);
stream->submit([&](sycl::handler & cgh) {
cgh.parallel_for(sycl::nd_range<3>(global_size, workgroup_size),
cgh.parallel_for(sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> nd_item) [[sycl::reqd_sub_group_size(WARP_SIZE)]] {
mul_mat_vec_q_reorder_ncols<reorder_vec_dot_q_sycl<GGML_TYPE_Q3_K>, ncols_dst>(
vx, vy, dst, ncols, nrows, stride_col_y_bytes, stride_col_dst, nd_item);
@@ -1457,13 +1454,12 @@ static void reorder_mul_mat_vec_q4_k_q8_1_sycl(const void * vx, const void * vy,
// Round up to a whole number of subgroup-sized workgroups; out-of-range rows are skipped inside the kernel.
constexpr size_t num_subgroups = WARP_SIZE;
const int block_num_y = ceil_div(nrows, GGML_SYCL_MMV_Y * (int) num_subgroups) * (int) num_subgroups;
const sycl::range<3> global_size(1, GGML_SYCL_MMV_Y, block_num_y * WARP_SIZE);
const sycl::range<3> workgroup_size(1, GGML_SYCL_MMV_Y, num_subgroups * WARP_SIZE);
const int block_num_y = ceil_div(nrows, GGML_SYCL_MMV_Y * (int) num_subgroups);
const sycl::range<3> block_nums(1, 1, block_num_y);
const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, num_subgroups * WARP_SIZE);
stream->submit([&](sycl::handler & cgh) {
cgh.parallel_for(sycl::nd_range<3>(global_size, workgroup_size),
cgh.parallel_for(sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> nd_item) [[sycl::reqd_sub_group_size(WARP_SIZE)]] {
mul_mat_vec_q_reorder<reorder_vec_dot_q_sycl<GGML_TYPE_Q4_K>>(vx, vy, dst, ncols,
nrows, nd_item);
@@ -1478,13 +1474,14 @@ static void reorder_mul_mat_vec_q4_k_q8_1_sycl_ncols(
const int stride_col_y_bytes, const int stride_col_dst,
dpct::queue_ptr stream) {
GGML_ASSERT(ncols % QK_K == 0);
const int block_num_y = ceil_div(nrows, GGML_SYCL_MMV_Y);
constexpr size_t num_subgroups = 16;
GGML_ASSERT(block_num_y % num_subgroups == 0);
const sycl::range<3> global_size(1, GGML_SYCL_MMV_Y, block_num_y * WARP_SIZE);
const sycl::range<3> workgroup_size(1, GGML_SYCL_MMV_Y, num_subgroups * WARP_SIZE);
constexpr size_t num_subgroups = WARP_SIZE;
const int block_num_y = ceil_div(nrows, GGML_SYCL_MMV_Y * (int) num_subgroups);
const sycl::range<3> block_nums(1, 1, block_num_y);
const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, num_subgroups * WARP_SIZE);
stream->submit([&](sycl::handler & cgh) {
cgh.parallel_for(sycl::nd_range<3>(global_size, workgroup_size),
cgh.parallel_for(sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> nd_item) [[sycl::reqd_sub_group_size(WARP_SIZE)]] {
mul_mat_vec_q_reorder_ncols<reorder_vec_dot_q_sycl<GGML_TYPE_Q4_K>, ncols_dst>(
vx, vy, dst, ncols, nrows, stride_col_y_bytes, stride_col_dst, nd_item);
@@ -1583,15 +1580,13 @@ static void reorder_mul_mat_vec_q5_k_q8_1_sycl(const void * vx, const void * vy,
const int nrows, dpct::queue_ptr stream) {
GGML_ASSERT(ncols % QK_K == 0);
const int block_num_y = ceil_div(nrows, GGML_SYCL_MMV_Y);
constexpr size_t num_subgroups = 16;
GGML_ASSERT(block_num_y % num_subgroups == 0);
const sycl::range<3> global_size(1, GGML_SYCL_MMV_Y, block_num_y * WARP_SIZE);
const sycl::range<3> workgroup_size(1, GGML_SYCL_MMV_Y, num_subgroups * WARP_SIZE);
constexpr size_t num_subgroups = WARP_SIZE;
const int block_num_y = ceil_div(nrows, GGML_SYCL_MMV_Y * (int) num_subgroups);
const sycl::range<3> block_nums(1, 1, block_num_y);
const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, num_subgroups * WARP_SIZE);
stream->submit([&](sycl::handler & cgh) {
cgh.parallel_for(sycl::nd_range<3>(global_size, workgroup_size),
cgh.parallel_for(sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> nd_item) [[sycl::reqd_sub_group_size(WARP_SIZE)]] {
mul_mat_vec_q_reorder<reorder_vec_dot_q_sycl<GGML_TYPE_Q5_K>>(vx, vy, dst, ncols,
nrows, nd_item);
@@ -1606,13 +1601,14 @@ static void reorder_mul_mat_vec_q5_k_q8_1_sycl_ncols(
const int stride_col_y_bytes, const int stride_col_dst,
dpct::queue_ptr stream) {
GGML_ASSERT(ncols % QK_K == 0);
const int block_num_y = ceil_div(nrows, GGML_SYCL_MMV_Y);
constexpr size_t num_subgroups = 16;
GGML_ASSERT(block_num_y % num_subgroups == 0);
const sycl::range<3> global_size(1, GGML_SYCL_MMV_Y, block_num_y * WARP_SIZE);
const sycl::range<3> workgroup_size(1, GGML_SYCL_MMV_Y, num_subgroups * WARP_SIZE);
constexpr size_t num_subgroups = WARP_SIZE;
const int block_num_y = ceil_div(nrows, GGML_SYCL_MMV_Y * (int) num_subgroups);
const sycl::range<3> block_nums(1, 1, block_num_y);
const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, num_subgroups * WARP_SIZE);
stream->submit([&](sycl::handler & cgh) {
cgh.parallel_for(sycl::nd_range<3>(global_size, workgroup_size),
cgh.parallel_for(sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> nd_item) [[sycl::reqd_sub_group_size(WARP_SIZE)]] {
mul_mat_vec_q_reorder_ncols<reorder_vec_dot_q_sycl<GGML_TYPE_Q5_K>, ncols_dst>(
vx, vy, dst, ncols, nrows, stride_col_y_bytes, stride_col_dst, nd_item);
@@ -1643,13 +1639,13 @@ static void reorder_mul_mat_vec_q6_k_q8_1_sycl(const void * vx, const void * vy,
GGML_ASSERT(ncols % QK_K == 0);
// Round up to a whole number of subgroup-sized workgroups; out-of-range rows are skipped inside the kernel.
constexpr size_t num_subgroups = WARP_SIZE;
const int block_num_y = ceil_div(nrows, GGML_SYCL_MMV_Y * (int) num_subgroups) * (int) num_subgroups;
const int block_num_y = ceil_div(nrows, GGML_SYCL_MMV_Y * (int) num_subgroups);
const sycl::range<3> block_nums(1, 1, block_num_y);
const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, num_subgroups * WARP_SIZE);
const sycl::range<3> global_size(1, GGML_SYCL_MMV_Y, block_num_y * WARP_SIZE);
const sycl::range<3> workgroup_size(1, GGML_SYCL_MMV_Y, num_subgroups * WARP_SIZE);
stream->submit([&](sycl::handler & cgh) {
cgh.parallel_for(sycl::nd_range<3>(global_size, workgroup_size),
cgh.parallel_for(sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> nd_item) [[sycl::reqd_sub_group_size(WARP_SIZE)]] {
mul_mat_vec_q_reorder<reorder_vec_dot_q_sycl<GGML_TYPE_Q6_K>>(vx, vy, dst, ncols, nrows,
nd_item);
@@ -1664,13 +1660,13 @@ static void reorder_mul_mat_vec_q6_k_q8_1_sycl_ncols(
const int stride_col_y_bytes, const int stride_col_dst,
dpct::queue_ptr stream) {
GGML_ASSERT(ncols % QK_K == 0);
const int block_num_y = ceil_div(nrows, GGML_SYCL_MMV_Y);
constexpr size_t num_subgroups = 16;
GGML_ASSERT(block_num_y % num_subgroups == 0);
const sycl::range<3> global_size(1, GGML_SYCL_MMV_Y, block_num_y * WARP_SIZE);
const sycl::range<3> workgroup_size(1, GGML_SYCL_MMV_Y, num_subgroups * WARP_SIZE);
constexpr size_t num_subgroups = WARP_SIZE;
const int block_num_y = ceil_div(nrows, GGML_SYCL_MMV_Y * (int) num_subgroups);
const sycl::range<3> block_nums(1, 1, block_num_y);
const sycl::range<3> block_dims(1, GGML_SYCL_MMV_Y, num_subgroups * WARP_SIZE);
stream->submit([&](sycl::handler & cgh) {
cgh.parallel_for(sycl::nd_range<3>(global_size, workgroup_size),
cgh.parallel_for(sycl::nd_range<3>(block_nums * block_dims, block_dims),
[=](sycl::nd_item<3> nd_item) [[sycl::reqd_sub_group_size(WARP_SIZE)]] {
mul_mat_vec_q_reorder_ncols<reorder_vec_dot_q_sycl<GGML_TYPE_Q6_K>, ncols_dst>(
vx, vy, dst, ncols, nrows, stride_col_y_bytes, stride_col_dst, nd_item);