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opencl: transposed gemm/gemv moe kernel with mxfp4,f32 (#16602)

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* opencl: transposed gemm/gemv moe kernel with mxfp4,f32

* add restore kernel for moe transpose

* fix trailing whitespaces

* resolve compilation warnings
This commit is contained in:
Shawn Gu
2025-10-17 17:55:32 -07:00
committed by GitHub
parent 66b0dbcb2d
commit 81387858f1
5 changed files with 567 additions and 8 deletions
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2
ggml/src/ggml-opencl/CMakeLists.txt
View File

@@ -91,6 +91,8 @@ set(GGML_OPENCL_KERNELS
mul_mv_id_q8_0_f32_flat
mul_mv_id_mxfp4_f32
mul_mv_id_mxfp4_f32_flat
gemm_moe_mxfp4_f32
gemv_moe_mxfp4_f32
mul_mm_f32_f32_l4_lm
mul_mm_f16_f32_l4_lm
mul_mm_q8_0_f32_l4_lm

213
ggml/src/ggml-opencl/ggml-opencl.cpp
View File

@@ -402,6 +402,7 @@ struct ggml_backend_opencl_context {
cl_program program_conv_2d_f32;
cl_program program_conv_2d_f16_f32;
cl_program program_tsembd;
cl_program program_gemv_moe_mxfp4_f32, program_gemm_moe_mxfp4_f32;
cl_program program_mul_mv_id_q4_0_f32_8x_flat;
cl_program program_mul_mv_id_q8_0_f32, program_mul_mv_id_q8_0_f32_flat;
cl_program program_mul_mv_id_mxfp4_f32;
@@ -452,7 +453,7 @@ struct ggml_backend_opencl_context {
cl_kernel kernel_mul_mat_f16_f32_tiled;
cl_kernel kernel_mul_mat_q4_0_f32, kernel_mul_mat_q4_0_f32_v;
cl_kernel kernel_convert_block_q4_0, kernel_restore_block_q4_0;
cl_kernel kernel_convert_block_mxfp4, kernel_restore_block_mxfp4;
cl_kernel kernel_convert_block_mxfp4, kernel_convert_block_mxfp4_trans, kernel_restore_block_mxfp4, kernel_restore_block_mxfp4_trans;
cl_kernel kernel_convert_block_q8_0, kernel_restore_block_q8_0;
cl_kernel kernel_mul_mat_q4_0_f32_8x_flat;
cl_kernel kernel_convert_block_q4_0_noshuffle;
@@ -475,6 +476,7 @@ struct ggml_backend_opencl_context {
cl_kernel kernel_conv_2d_f32;
cl_kernel kernel_conv_2d_f16_f32;
cl_kernel kernel_timestep_embedding;
cl_kernel kernel_gemv_moe_mxfp4_f32, kernel_gemm_moe_mxfp4_f32;
cl_kernel kernel_mul_mv_id_q4_0_f32_8x_flat;
cl_kernel kernel_mul_mv_id_q8_0_f32, kernel_mul_mv_id_q8_0_f32_flat;
cl_kernel kernel_mul_mv_id_mxfp4_f32;
@@ -559,14 +561,14 @@ struct ggml_backend_opencl_context {
fprintf(ftrace, "[\n");
for (const ProfilingInfo & info : profiling_info) {
fprintf(ftrace, "{\"name\": \"%s\", \"cat\": \"OpenCL\", \"ph\": \"B\", \"ts\": %lu, \"pid\": \"\", \"tid\": \"Host\"},\n",
fprintf(ftrace, "{\"name\": \"%s\", \"cat\": \"OpenCL\", \"ph\": \"B\", \"ts\": %llu, \"pid\": \"\", \"tid\": \"Host\"},\n",
info.kernel_name.c_str(), info.cmd_queued/1000);
fprintf(ftrace, "{\"name\": \"%s\", \"cat\": \"OpenCL\", \"ph\": \"E\", \"ts\": %lu, \"pid\": \"\", \"tid\": \"Host\"},\n",
fprintf(ftrace, "{\"name\": \"%s\", \"cat\": \"OpenCL\", \"ph\": \"E\", \"ts\": %llu, \"pid\": \"\", \"tid\": \"Host\"},\n",
info.kernel_name.c_str(), info.cmd_submit/1000);
fprintf(ftrace, "{\"name\": \"%s\", \"cat\": \"OpenCL\", \"ph\": \"B\", \"ts\": %lu, \"pid\": \"\", \"tid\": \"Device\"},\n",
fprintf(ftrace, "{\"name\": \"%s\", \"cat\": \"OpenCL\", \"ph\": \"B\", \"ts\": %llu, \"pid\": \"\", \"tid\": \"Device\"},\n",
info.kernel_name.c_str(), info.cmd_start/1000);
fprintf(ftrace, "{\"name\": \"%s\", \"cat\": \"OpenCL\", \"ph\": \"E\", \"ts\": %lu, \"pid\": \"\", \"tid\": \"Device\"},\n",
fprintf(ftrace, "{\"name\": \"%s\", \"cat\": \"OpenCL\", \"ph\": \"E\", \"ts\": %llu, \"pid\": \"\", \"tid\": \"Device\"},\n",
info.kernel_name.c_str(), info.cmd_end/1000);
}
fclose(ftrace);
@@ -777,6 +779,8 @@ static void load_cl_kernels(ggml_backend_opencl_context *backend_ctx, ggml_cl_ve
CL_CHECK((backend_ctx->kernel_convert_block_q4_0 = clCreateKernel(backend_ctx->program_cvt, "kernel_convert_block_q4_0", &err), err));
CL_CHECK((backend_ctx->kernel_restore_block_q4_0 = clCreateKernel(backend_ctx->program_cvt, "kernel_restore_block_q4_0", &err), err));
CL_CHECK((backend_ctx->kernel_convert_block_mxfp4 = clCreateKernel(backend_ctx->program_cvt, "kernel_convert_block_mxfp4", &err), err));
CL_CHECK((backend_ctx->kernel_convert_block_mxfp4_trans = clCreateKernel(backend_ctx->program_cvt, "kernel_convert_block_mxfp4_trans", &err), err));
CL_CHECK((backend_ctx->kernel_restore_block_mxfp4_trans = clCreateKernel(backend_ctx->program_cvt, "kernel_restore_block_mxfp4_trans", &err), err));
CL_CHECK((backend_ctx->kernel_restore_block_mxfp4 = clCreateKernel(backend_ctx->program_cvt, "kernel_restore_block_mxfp4", &err), err));
CL_CHECK((backend_ctx->kernel_convert_block_q8_0 = clCreateKernel(backend_ctx->program_cvt, "kernel_convert_block_q8_0", &err), err));
CL_CHECK((backend_ctx->kernel_restore_block_q8_0 = clCreateKernel(backend_ctx->program_cvt, "kernel_restore_block_q8_0", &err), err));
@@ -1991,6 +1995,42 @@ static void load_cl_kernels(ggml_backend_opencl_context *backend_ctx, ggml_cl_ve
CL_CHECK((backend_ctx->CL_mul_mat_Ab_Bi_8x4 = clCreateKernel(backend_ctx->program_CL_gemm, "kernel_mul_mat_Ab_Bi_8x4", &err), err));
GGML_LOG_CONT(".");
}
std::string CL_moe_compile_opts = std::string("-cl-std=") + opencl_c_std +
" -cl-mad-enable "
" -cl-fast-relaxed-math";
// gemv_moe_mxfp4_f32
{
#ifdef GGML_OPENCL_EMBED_KERNELS
const std::string kernel_src {
#include "gemv_moe_mxfp4_f32.cl.h"
};
#else
const std::string kernel_src = read_file("gemv_moe_mxfp4_f32.cl");
#endif
backend_ctx->program_gemv_moe_mxfp4_f32 =
build_program_from_source(backend_ctx->context, backend_ctx->device, kernel_src.c_str(), CL_moe_compile_opts);
CL_CHECK((backend_ctx->kernel_gemv_moe_mxfp4_f32 = clCreateKernel(backend_ctx->program_gemv_moe_mxfp4_f32, "kernel_gemv_moe_mxfp4_f32", &err), err));
GGML_LOG_CONT(".");
}
// gemm_moe_mxfp4_f32
{
#ifdef GGML_OPENCL_EMBED_KERNELS
const std::string kernel_src {
#include "gemm_moe_mxfp4_f32.cl.h"
};
#else
const std::string kernel_src = read_file("gemm_moe_mxfp4_f32.cl");
#endif
backend_ctx->program_gemm_moe_mxfp4_f32 =
build_program_from_source(backend_ctx->context, backend_ctx->device, kernel_src.c_str(), CL_moe_compile_opts);
CL_CHECK((backend_ctx->kernel_gemm_moe_mxfp4_f32 = clCreateKernel(backend_ctx->program_gemm_moe_mxfp4_f32, "kernel_gemm_moe_mxfp4_f32", &err), err));
GGML_LOG_CONT(".");
}
#endif // GGML_OPENCL_USE_ADRENO_KERNELS
GGML_LOG_CONT("\n");
}
@@ -3299,6 +3339,12 @@ inline bool use_adreno_kernels(const ggml_backend_opencl_context *backend_ctx, c
tensor->ne[2] == 1 && tensor->ne[3] == 1;
}
inline bool use_adreno_moe_kernels(const ggml_backend_opencl_context *backend_ctx, const ggml_tensor *tensor) {
GGML_UNUSED(backend_ctx);
int ne01 = tensor->ne[1];
return ((strstr(tensor->name, "ffn") != NULL) || (strstr(tensor->name, "as") != NULL)) && (ne01 % 64 == 0);
}
static void ggml_backend_opencl_buffer_set_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor, const void * data, size_t offset, size_t size) {
ggml_backend_opencl_context *backend_ctx = ggml_cl2_init(buffer->buft->device);
@@ -3601,14 +3647,39 @@ static void ggml_backend_opencl_buffer_set_tensor(ggml_backend_buffer_t buffer,
CL_BUFFER_CREATE_TYPE_REGION, &region, &err);
CL_CHECK(err);
#ifdef GGML_OPENCL_USE_ADRENO_KERNELS
if (use_adreno_moe_kernels(backend_ctx, tensor)) {
cl_kernel kernel = backend_ctx->kernel_convert_block_mxfp4_trans;
int ne00 = tensor->ne[0];
int ne01 = tensor->ne[1];
int ne02 = tensor->ne[2];
CL_CHECK(clSetKernelArg(kernel, 0, sizeof(cl_mem), &data_device));
CL_CHECK(clSetKernelArg(kernel, 1, sizeof(cl_mem), &extra->q));
CL_CHECK(clSetKernelArg(kernel, 2, sizeof(cl_mem), &extra->e));
CL_CHECK(clSetKernelArg(kernel, 3, sizeof(int), &ne00));
CL_CHECK(clSetKernelArg(kernel, 4, sizeof(int), &ne01));
size_t global_work_size[3] = {static_cast<size_t>(((ne01 + 63) / 64) * 64), static_cast<size_t>(ne00 / 32), static_cast<size_t>(ne02)};
size_t local_work_size[3] = {64, 2, 1};
cl_event evt;
CL_CHECK(clEnqueueNDRangeKernel(queue, kernel, 3, NULL, global_work_size, local_work_size, 0, NULL, &evt));
CL_CHECK(clWaitForEvents(1, &evt));
CL_CHECK(clReleaseMemObject(data_device));
tensor->extra = extra;
return;
}
#endif
cl_kernel kernel = backend_ctx->kernel_convert_block_mxfp4;
CL_CHECK(clSetKernelArg(kernel, 0, sizeof(cl_mem), &data_device));
CL_CHECK(clSetKernelArg(kernel, 1, sizeof(cl_mem), &extra->q));
CL_CHECK(clSetKernelArg(kernel, 2, sizeof(cl_mem), &extra->e));
size_t global_work_size[] = {(size_t)ggml_nelements(tensor)/ggml_blck_size(tensor->type), 1, 1};
size_t local_work_size[] = {64, 1, 1};
size_t global_work_size[3] = {(size_t)ggml_nelements(tensor)/ggml_blck_size(tensor->type), 1, 1};
size_t local_work_size[3] = {64, 1, 1};
cl_event evt;
CL_CHECK(clEnqueueNDRangeKernel(queue, kernel, 3, NULL, global_work_size, local_work_size, 0, NULL, &evt));
@@ -3624,7 +3695,6 @@ static void ggml_backend_opencl_buffer_set_tensor(ggml_backend_buffer_t buffer,
{ extra->q }
};
extra->q_img = clCreateImage(context, CL_MEM_READ_ONLY, &img_format_q, &img_desc_q, NULL, &err);
tensor->extra = extra;
return;
@@ -3751,6 +3821,33 @@ static void ggml_backend_opencl_buffer_get_tensor(ggml_backend_buffer_t buffer,
ggml_nbytes(tensor), NULL, &err);
CL_CHECK(err);
#ifdef GGML_OPENCL_USE_ADRENO_KERNELS
if (use_adreno_moe_kernels(backend_ctx, tensor)) {
cl_kernel kernel = backend_ctx->kernel_restore_block_mxfp4_trans;
int ne00 = tensor->ne[0];
int ne01 = tensor->ne[1];
int ne02 = tensor->ne[2];
CL_CHECK(clSetKernelArg(kernel, 0, sizeof(cl_mem), &extra->q));
CL_CHECK(clSetKernelArg(kernel, 1, sizeof(cl_mem), &extra->e));
CL_CHECK(clSetKernelArg(kernel, 2, sizeof(cl_mem), &data_device));
CL_CHECK(clSetKernelArg(kernel, 3, sizeof(cl_int), &ne00));
CL_CHECK(clSetKernelArg(kernel, 4, sizeof(cl_int), &ne01));
size_t global_work_size[3] = {static_cast<size_t>(((ne01 + 63) / 64) * 64), static_cast<size_t>(ne00 / 32), static_cast<size_t>(ne02)};
size_t local_work_size[3] = {64, 2, 1};
cl_event evt;
CL_CHECK(clEnqueueNDRangeKernel(queue, kernel, 3, NULL,
global_work_size, local_work_size, 0, NULL, &evt));
CL_CHECK(clWaitForEvents(1, &evt));
CL_CHECK(clEnqueueReadBuffer(
queue, data_device, CL_TRUE, offset,
size, data, 0, NULL, NULL));
CL_CHECK(clReleaseMemObject(data_device));
return;
}
#endif
cl_kernel kernel = backend_ctx->kernel_restore_block_mxfp4;
CL_CHECK(clSetKernelArg(kernel, 0, sizeof(cl_mem), &extra->q));
CL_CHECK(clSetKernelArg(kernel, 1, sizeof(cl_mem), &extra->e));
@@ -7553,6 +7650,7 @@ static void ggml_cl_mul_mat_id(ggml_backend_t backend, const ggml_tensor * src0,
const int ne21 = src2->ne[1];
const cl_ulong nb21 = src2->nb[1];
const cl_ulong nb20 = src2->nb[0];
const int ne0 = dst->ne[0];
const int ne1 = dst->ne[1];
@@ -7692,6 +7790,105 @@ static void ggml_cl_mul_mat_id(ggml_backend_t backend, const ggml_tensor * src0,
break;
}
case GGML_TYPE_MXFP4: {
#ifdef GGML_OPENCL_USE_ADRENO_KERNELS
if (use_adreno_moe_kernels(backend_ctx, src0)) {
cl_int status;
size_t local_size[3] = {64, 2, 1};
size_t global_size[3] = {64, 2, 1};
cl_mem src1_sub_buffer, buf_src1_image, buf_src2;
int tile_size = 320;
if (ne12 == 1) { // for gemv
kernel = backend_ctx->kernel_gemv_moe_mxfp4_f32;
// create a sub_buffer for src2
cl_buffer_region region;
region.origin = offset2;
region.size = ne20 * ne21 * sizeof(int);
buf_src2 = clCreateSubBuffer(extra2->data_device, 0, CL_BUFFER_CREATE_TYPE_REGION, &region, &status);
CL_CHECK(status);
// set thread grid
global_size[0] = static_cast<size_t>(ne01);
global_size[1] = 4;
global_size[2] = static_cast<size_t>(ne20);
local_size[1] = 4;
} else { // for gemm
kernel = backend_ctx->kernel_gemm_moe_mxfp4_f32;
// preprocess router table
int num_tiles_per_expert = (ne01 + tile_size - 1) / tile_size;
void * host_src2_reorder = malloc(ne20 * ne21 * 4 * num_tiles_per_expert * sizeof(short));
void * host_src2 = malloc(ne21 * nb21);
CL_CHECK(clEnqueueReadBuffer(backend_ctx->queue, extra2->data_device, CL_TRUE, offset2, ne21 * nb21, host_src2, 0, NULL, NULL));
int total_experts = nb21 / nb20;
int out_idx = 0;
for (int i_expert = 0; i_expert < ne02; i_expert++) {
for (int i_tile = 0; i_tile < num_tiles_per_expert; i_tile++) {
for (int j = 0; j < ne21; j++) {
for (int i = 0; i < ne20; i++) {
int expert = ((int *)host_src2)[j * total_experts + i];
if (i_expert == expert) {
((short *)host_src2_reorder)[out_idx] = static_cast<short>(expert);
((short *)host_src2_reorder)[out_idx + 1] = static_cast<short>(j * ne11 + (i % ne11));
((short *)host_src2_reorder)[out_idx + 2] = static_cast<short>(j * ne20 + i);
((short *)host_src2_reorder)[out_idx + 3] = static_cast<short>(i_tile);
out_idx += 4;
}
}
}
}
}
buf_src2 = clCreateBuffer(backend_ctx->context, CL_MEM_READ_ONLY | CL_MEM_COPY_HOST_PTR, ne20 * ne21 * 4 * num_tiles_per_expert * sizeof(short), host_src2_reorder, &status);
CL_CHECK(status);
// set thread grid
global_size[0] = static_cast<size_t>(tile_size);
global_size[2] = static_cast<size_t>(ne20 * ne21 * num_tiles_per_expert);
}
// create a sub_buffer for src1
cl_buffer_region region;
region.origin = offset1;
region.size = ne10 * ne11 * ne12 * sizeof(float);
src1_sub_buffer = clCreateSubBuffer(extra1->data_device, 0, CL_BUFFER_CREATE_TYPE_REGION, &region, &status);
CL_CHECK(status);
// create image for src1
cl_image_format image_format_buf_src1 = {CL_RGBA, CL_FLOAT};
cl_image_desc image_desc_buf_src1 = {CL_MEM_OBJECT_IMAGE1D_BUFFER, static_cast<size_t>(ne10 * ne11 * ne12 / 4), 0,0,0,0,0,0,0, {src1_sub_buffer}};
buf_src1_image = clCreateImage(backend_ctx->context, CL_MEM_READ_ONLY, &image_format_buf_src1, &image_desc_buf_src1, NULL, &status);
CL_CHECK(status);
// Set kernel args
int arg_idx = 0;
CL_CHECK(clSetKernelArg(kernel, arg_idx++, sizeof(cl_mem), &extra0_mxfp4->q));
CL_CHECK(clSetKernelArg(kernel, arg_idx++, sizeof(cl_mem), &extra0_mxfp4->e));
CL_CHECK(clSetKernelArg(kernel, arg_idx++, sizeof(cl_mem), &buf_src1_image));
CL_CHECK(clSetKernelArg(kernel, arg_idx++, sizeof(cl_mem), &buf_src2));
CL_CHECK(clSetKernelArg(kernel, arg_idx++, sizeof(cl_mem), &extrad->data_device));
CL_CHECK(clSetKernelArg(kernel, arg_idx++, sizeof(cl_ulong), &offsetd));
CL_CHECK(clSetKernelArg(kernel, arg_idx++, sizeof(int), &ne00));
CL_CHECK(clSetKernelArg(kernel, arg_idx++, sizeof(int), &ne01));
if (ne12 == 1) {
CL_CHECK(clSetKernelArg(kernel, arg_idx++, sizeof(int), &ne11));
} else {
CL_CHECK(clSetKernelArg(kernel, arg_idx++, sizeof(int), &tile_size));
}
// launch kernel
backend_ctx->enqueue_ndrange_kernel(kernel, 3, global_size, local_size, dst);
// deallocate sub buffers and images
CL_CHECK(clReleaseMemObject(src1_sub_buffer));
CL_CHECK(clReleaseMemObject(buf_src1_image));
CL_CHECK(clReleaseMemObject(buf_src2));
return;
} // else fallback to generic kernel
#endif // GGML_OPENCL_USE_ADRENO_KERNELS
#ifdef GGML_OPENCL_SOA_Q
kernel = backend_ctx->kernel_mul_mv_id_mxfp4_f32_flat;

42
ggml/src/ggml-opencl/kernels/cvt.cl
View File

@@ -147,6 +147,27 @@ kernel void kernel_convert_block_mxfp4(
}
}
kernel void kernel_convert_block_mxfp4_trans(
global struct block_mxfp4 * src0,
__global uint4 * dst_q,
__global uchar * dst_e,
uint ne00,
uint ne01
) {
int i00 = get_global_id(1);
uint i01 = get_global_id(0);
uint i02 = get_global_id(2);
uint ne00_blk = ne00 / QK_MXFP4;
uint src_blk_offset = i00 + i01 * ne00_blk + i02 * ne00_blk * ne01;
uint dst_blk_offset = i01 + i00 * ne01 + i02 * ne00_blk * ne01;
global struct block_mxfp4 * b = src0 + src_blk_offset;
dst_q[dst_blk_offset] = ((global uint4 *)(&(b->qs[0])))[0];
dst_e[dst_blk_offset] = b->e;
}
kernel void kernel_restore_block_mxfp4(
global uchar * src_q,
global half * src_e,
@@ -162,6 +183,27 @@ kernel void kernel_restore_block_mxfp4(
}
}
kernel void kernel_restore_block_mxfp4_trans(
__global uint4 * src_q,
__global uchar * src_e,
global struct block_mxfp4 * dst,
uint ne00,
uint ne01
) {
int i00 = get_global_id(1);
uint i01 = get_global_id(0);
uint i02 = get_global_id(2);
uint ne00_blk = ne00 / QK_MXFP4;
uint src_blk_offset = i01 + i00 * ne01 + i02 * ne00_blk * ne01;
uint dst_blk_offset = i00 + i01 * ne00_blk + i02 * ne00_blk * ne01;
global struct block_mxfp4 * b = dst + dst_blk_offset;
((global uint4 *)(&(b->qs[0])))[0] = src_q[src_blk_offset];
b->e = src_e[src_blk_offset];
}
//------------------------------------------------------------------------------
// block_q8_0
//------------------------------------------------------------------------------

162
ggml/src/ggml-opencl/kernels/gemm_moe_mxfp4_f32.cl Normal file
View File

@@ -0,0 +1,162 @@
#pragma OPENCL EXTENSION cl_khr_fp16 : enable
#pragma OPENCL EXTENSION cl_khr_subgroups : enable
#pragma OPENCL EXTENSION cl_qcom_reqd_sub_group_size : enable
#define QK_MXFP4 32
#define N_SIMDGROUP 2
#define SIMDGROUP_WIDTH 64
static inline half8 mxfp4_to_fp16_packed8(ushort2 fp4x8) { //, ushort 0x0E00, ushort 0x8000) {
ushort2 fp16_packed_a_0, fp16_packed_b_0, bias_a, bias_b, sign_a, sign_b;
fp16_packed_a_0.lo = (fp4x8.s0 << 9) & 0x0E00;
fp16_packed_a_0.hi = (fp4x8.s0 << 5) & 0x0E00;
fp16_packed_b_0.lo = (fp4x8.s0 << 1) & 0x0E00;
fp16_packed_b_0.hi = (fp4x8.s0 >> 3) & 0x0E00;
bias_a.lo = (fp16_packed_a_0.lo != 0) ? 0x3800 : 0x0;
bias_a.hi = (fp16_packed_a_0.hi != 0) ? 0x3800 : 0x0;
bias_b.lo = (fp16_packed_b_0.lo != 0) ? 0x3800 : 0x0;
bias_b.hi = (fp16_packed_b_0.hi != 0) ? 0x3800 : 0x0;
fp16_packed_a_0.lo = (fp16_packed_a_0.lo != 0x0200) ? fp16_packed_a_0.lo : 0x0;
fp16_packed_a_0.hi = (fp16_packed_a_0.hi != 0x0200) ? fp16_packed_a_0.hi : 0x0;
fp16_packed_b_0.lo = (fp16_packed_b_0.lo != 0x0200) ? fp16_packed_b_0.lo : 0x0;
fp16_packed_b_0.hi = (fp16_packed_b_0.hi != 0x0200) ? fp16_packed_b_0.hi : 0x0;
sign_a.lo = (fp4x8.s0 << 12) & 0x8000;
sign_a.hi = (fp4x8.s0 << 8) & 0x8000;
sign_b.lo = (fp4x8.s0 << 4) & 0x8000;
sign_b.hi = fp4x8.s0 & 0x8000;
fp16_packed_a_0 = sign_a + bias_a + fp16_packed_a_0;
fp16_packed_b_0 = sign_b + bias_b + fp16_packed_b_0;
ushort2 fp16_packed_a_1, fp16_packed_b_1;
fp16_packed_a_1.lo = (fp4x8.s1 << 9) & 0x0E00;
fp16_packed_a_1.hi = (fp4x8.s1 << 5) & 0x0E00;
fp16_packed_b_1.lo = (fp4x8.s1 << 1) & 0x0E00;
fp16_packed_b_1.hi = (fp4x8.s1 >> 3) & 0x0E00;
bias_a.lo = (fp16_packed_a_1.lo != 0) ? 0x3800 : 0x0;
bias_a.hi = (fp16_packed_a_1.hi != 0) ? 0x3800 : 0x0;
bias_b.lo = (fp16_packed_b_1.lo != 0) ? 0x3800 : 0x0;
bias_b.hi = (fp16_packed_b_1.hi != 0) ? 0x3800 : 0x0;
fp16_packed_a_1.lo = (fp16_packed_a_1.lo != 0x0200) ? fp16_packed_a_1.lo : 0x0;
fp16_packed_a_1.hi = (fp16_packed_a_1.hi != 0x0200) ? fp16_packed_a_1.hi : 0x0;
fp16_packed_b_1.lo = (fp16_packed_b_1.lo != 0x0200) ? fp16_packed_b_1.lo : 0x0;
fp16_packed_b_1.hi = (fp16_packed_b_1.hi != 0x0200) ? fp16_packed_b_1.hi : 0x0;
sign_a.lo = (fp4x8.s1 << 12) & 0x8000;
sign_a.hi = (fp4x8.s1 << 8) & 0x8000;
sign_b.lo = (fp4x8.s1 << 4) & 0x8000;
sign_b.hi = fp4x8.s1 & 0x8000;
fp16_packed_a_1 = sign_a + bias_a + fp16_packed_a_1;
fp16_packed_b_1 = sign_b + bias_b + fp16_packed_b_1;
return as_half8((ushort8)(fp16_packed_a_0, fp16_packed_b_0, fp16_packed_a_1, fp16_packed_b_1));
}
static inline float e8m0_to_fp32(uchar x) {
int bits;
bits = (x == 0) ? 0x00400000 : ((uint) x << 23);
return as_float(bits);
}
__attribute__((qcom_reqd_sub_group_size("half")))
__kernel void kernel_gemm_moe_mxfp4_f32(
__global uint4 * src0_q,
__global uchar * src0_e,
__read_only image1d_buffer_t src1,
__global ushort4 * src2,
__global float * dst,
ulong offsetd,
int ne00,
int ne01,
int tile_size
) {
uint i01 = get_global_id(0);
uint i20 = get_global_id(2);
uint sgid = get_local_id(1);
uint slid = get_sub_group_local_id();
ushort4 router = src2[i20];
ushort expert_id = router.x;
ushort i11 = router.y;
ushort i1 = router.z;
ushort tile_id = router.w;
if (tile_id * tile_size + i01 >= ne01) { // handle edge case when ne01 is not multiple of tile_size
return;
}
uint expert_offset = expert_id * ne00 * ne01 / 32;
uint tile_offset = expert_offset + tile_id * tile_size + i01;
__private float sum = 0.0f; // each thread calculate partial sum of one output
// loop along ne00 in block granularity, skip 4 blocks every iter
for (uint ib00 = sgid; ib00 < (ne00 / QK_MXFP4); ib00 += N_SIMDGROUP) {
// load one block of q
uint4 regQ = src0_q[tile_offset + ib00 * ne01];
// convert 8 fp4 to fp16
half8 fp16x8 = mxfp4_to_fp16_packed8(as_ushort2(regQ.s0));
uint offset = i11 * ne00 / 4 + ib00 * 8;
float4 shared_y4;
shared_y4 = read_imagef(src1, (offset + 0));
float4 acc = shared_y4 * (float4)(fp16x8.s0, fp16x8.s2, fp16x8.s4, fp16x8.s6);
shared_y4 = read_imagef(src1, (offset + 4));
acc += shared_y4 * (float4)(fp16x8.s1, fp16x8.s3, fp16x8.s5, fp16x8.s7);
fp16x8 = mxfp4_to_fp16_packed8(as_ushort2(regQ.s1));
shared_y4 = read_imagef(src1, (offset + 1));
acc += shared_y4 * (float4)(fp16x8.s0, fp16x8.s2, fp16x8.s4, fp16x8.s6);
shared_y4 = read_imagef(src1, (offset + 5));
acc += shared_y4 * (float4)(fp16x8.s1, fp16x8.s3, fp16x8.s5, fp16x8.s7);
fp16x8 = mxfp4_to_fp16_packed8(as_ushort2(regQ.s2));
shared_y4 = read_imagef(src1, (offset + 2));
acc += shared_y4 * (float4)(fp16x8.s0, fp16x8.s2, fp16x8.s4, fp16x8.s6);
shared_y4 = read_imagef(src1, (offset + 6));
acc += shared_y4 * (float4)(fp16x8.s1, fp16x8.s3, fp16x8.s5, fp16x8.s7);
fp16x8 = mxfp4_to_fp16_packed8(as_ushort2(regQ.s3));
shared_y4 = read_imagef(src1, (offset + 3));
acc += shared_y4 * (float4)(fp16x8.s0, fp16x8.s2, fp16x8.s4, fp16x8.s6);
shared_y4 = read_imagef(src1, (offset + 7));
acc += shared_y4 * (float4)(fp16x8.s1, fp16x8.s3, fp16x8.s5, fp16x8.s7);
uchar regE = src0_e[tile_offset + ib00 * ne01];
sum += e8m0_to_fp32(regE) * ((acc.s0 + acc.s1) + (acc.s2 + acc.s3));
}
// reduction in local memory, assumes #subgroups=4
__local float reduceLM[SIMDGROUP_WIDTH * (N_SIMDGROUP - 1)];
if (sgid == 1) reduceLM[SIMDGROUP_WIDTH * 0 + slid] = sum;
// if (sgid == 2) reduceLM[SIMDGROUP_WIDTH * 1 + slid] = sum;
// if (sgid == 3) reduceLM[SIMDGROUP_WIDTH * 2 + slid] = sum;
barrier(CLK_LOCAL_MEM_FENCE);
if (sgid == 0) sum += reduceLM[SIMDGROUP_WIDTH * 0 + slid];
// if (sgid == 0) sum += reduceLM[SIMDGROUP_WIDTH * 1 + slid];
// if (sgid == 0) sum += reduceLM[SIMDGROUP_WIDTH * 2 + slid];
// 1 outputs per thread in subgroup 0
if (sgid == 0) {
dst = dst + (offsetd >> 2);
dst[i01 + tile_id * tile_size + i1 * ne01] = sum;
}
}

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ggml/src/ggml-opencl/kernels/gemv_moe_mxfp4_f32.cl Normal file
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#pragma OPENCL EXTENSION cl_khr_fp16 : enable
#pragma OPENCL EXTENSION cl_khr_subgroups : enable
#pragma OPENCL EXTENSION cl_qcom_reqd_sub_group_size : enable
#define QK_MXFP4 32
#define N_SIMDGROUP 4
#define SIMDGROUP_WIDTH 64
static inline half8 mxfp4_to_fp16_packed8(ushort2 fp4x8) { //, ushort 0x0E00, ushort 0x8000) {
ushort2 fp16_packed_a_0, fp16_packed_b_0, bias_a, bias_b, sign_a, sign_b;
fp16_packed_a_0.lo = (fp4x8.s0 << 9) & 0x0E00;
fp16_packed_a_0.hi = (fp4x8.s0 << 5) & 0x0E00;
fp16_packed_b_0.lo = (fp4x8.s0 << 1) & 0x0E00;
fp16_packed_b_0.hi = (fp4x8.s0 >> 3) & 0x0E00;
bias_a.lo = (fp16_packed_a_0.lo != 0) ? 0x3800 : 0x0;
bias_a.hi = (fp16_packed_a_0.hi != 0) ? 0x3800 : 0x0;
bias_b.lo = (fp16_packed_b_0.lo != 0) ? 0x3800 : 0x0;
bias_b.hi = (fp16_packed_b_0.hi != 0) ? 0x3800 : 0x0;
fp16_packed_a_0.lo = (fp16_packed_a_0.lo != 0x0200) ? fp16_packed_a_0.lo : 0x0;
fp16_packed_a_0.hi = (fp16_packed_a_0.hi != 0x0200) ? fp16_packed_a_0.hi : 0x0;
fp16_packed_b_0.lo = (fp16_packed_b_0.lo != 0x0200) ? fp16_packed_b_0.lo : 0x0;
fp16_packed_b_0.hi = (fp16_packed_b_0.hi != 0x0200) ? fp16_packed_b_0.hi : 0x0;
sign_a.lo = (fp4x8.s0 << 12) & 0x8000;
sign_a.hi = (fp4x8.s0 << 8) & 0x8000;
sign_b.lo = (fp4x8.s0 << 4) & 0x8000;
sign_b.hi = fp4x8.s0 & 0x8000;
fp16_packed_a_0 = sign_a + bias_a + fp16_packed_a_0;
fp16_packed_b_0 = sign_b + bias_b + fp16_packed_b_0;
ushort2 fp16_packed_a_1, fp16_packed_b_1;
fp16_packed_a_1.lo = (fp4x8.s1 << 9) & 0x0E00;
fp16_packed_a_1.hi = (fp4x8.s1 << 5) & 0x0E00;
fp16_packed_b_1.lo = (fp4x8.s1 << 1) & 0x0E00;
fp16_packed_b_1.hi = (fp4x8.s1 >> 3) & 0x0E00;
bias_a.lo = (fp16_packed_a_1.lo != 0) ? 0x3800 : 0x0;
bias_a.hi = (fp16_packed_a_1.hi != 0) ? 0x3800 : 0x0;
bias_b.lo = (fp16_packed_b_1.lo != 0) ? 0x3800 : 0x0;
bias_b.hi = (fp16_packed_b_1.hi != 0) ? 0x3800 : 0x0;
fp16_packed_a_1.lo = (fp16_packed_a_1.lo != 0x0200) ? fp16_packed_a_1.lo : 0x0;
fp16_packed_a_1.hi = (fp16_packed_a_1.hi != 0x0200) ? fp16_packed_a_1.hi : 0x0;
fp16_packed_b_1.lo = (fp16_packed_b_1.lo != 0x0200) ? fp16_packed_b_1.lo : 0x0;
fp16_packed_b_1.hi = (fp16_packed_b_1.hi != 0x0200) ? fp16_packed_b_1.hi : 0x0;
sign_a.lo = (fp4x8.s1 << 12) & 0x8000;
sign_a.hi = (fp4x8.s1 << 8) & 0x8000;
sign_b.lo = (fp4x8.s1 << 4) & 0x8000;
sign_b.hi = fp4x8.s1 & 0x8000;
fp16_packed_a_1 = sign_a + bias_a + fp16_packed_a_1;
fp16_packed_b_1 = sign_b + bias_b + fp16_packed_b_1;
return as_half8((ushort8)(fp16_packed_a_0, fp16_packed_b_0, fp16_packed_a_1, fp16_packed_b_1));
}
static inline float e8m0_to_fp32(uchar x) {
int bits;
bits = (x == 0) ? 0x00400000 : ((uint) x << 23);
return as_float(bits);
}
__attribute__((qcom_reqd_sub_group_size("half")))
__kernel void kernel_gemv_moe_mxfp4_f32(
__global uint4 * src0_q,
__global uchar * src0_e,
__read_only image1d_buffer_t src1,
__global uint * src2,
__global float * dst,
ulong offsetd,
int ne00,
int ne01,
int ne11
) {
uint i01 = get_global_id(0);
uint i20 = get_global_id(2);
uint sgid = get_local_id(1);
uint slid = get_sub_group_local_id();
uint i11 = i20 % ne11;
uint expert_id = src2[i20];
uint expert_offset = expert_id * ne00 * ne01 / 32;
__private float sum = 0.0f; // each thread calculate partial sum of one output
// loop along ne00 in block granularity, skip 4 blocks every iter
for (uint ib00 = sgid; ib00 < (ne00 / QK_MXFP4); ib00 += N_SIMDGROUP) {
// load one block of q
uint4 regQ = src0_q[expert_offset + ib00 * ne01 + i01];
uint offset = i11 * ne00 / 4 + ib00 * 8;
half8 fp16x8 = mxfp4_to_fp16_packed8(as_ushort2(regQ.s0));
float4 shared_y4;
shared_y4 = read_imagef(src1, (offset + 0));
float4 acc = shared_y4 * (float4)(fp16x8.s0, fp16x8.s2, fp16x8.s4, fp16x8.s6);
shared_y4 = read_imagef(src1, (offset + 4));
acc += shared_y4 * (float4)(fp16x8.s1, fp16x8.s3, fp16x8.s5, fp16x8.s7);
fp16x8 = mxfp4_to_fp16_packed8(as_ushort2(regQ.s1));
shared_y4 = read_imagef(src1, (offset + 1));
acc += shared_y4 * (float4)(fp16x8.s0, fp16x8.s2, fp16x8.s4, fp16x8.s6);
shared_y4 = read_imagef(src1, (offset + 5));
acc += shared_y4 * (float4)(fp16x8.s1, fp16x8.s3, fp16x8.s5, fp16x8.s7);
fp16x8 = mxfp4_to_fp16_packed8(as_ushort2(regQ.s2));
shared_y4 = read_imagef(src1, (offset + 2));
acc += shared_y4 * (float4)(fp16x8.s0, fp16x8.s2, fp16x8.s4, fp16x8.s6);
shared_y4 = read_imagef(src1, (offset + 6));
acc += shared_y4 * (float4)(fp16x8.s1, fp16x8.s3, fp16x8.s5, fp16x8.s7);
fp16x8 = mxfp4_to_fp16_packed8(as_ushort2(regQ.s3));
shared_y4 = read_imagef(src1, (offset + 3));
acc += shared_y4 * (float4)(fp16x8.s0, fp16x8.s2, fp16x8.s4, fp16x8.s6);
shared_y4 = read_imagef(src1, (offset + 7));
acc += shared_y4 * (float4)(fp16x8.s1, fp16x8.s3, fp16x8.s5, fp16x8.s7);
uchar regE = src0_e[ib00 * ne01 + i01 + expert_offset];
sum += e8m0_to_fp32(regE) * ((acc.s0 + acc.s1) + (acc.s2 + acc.s3));
}
// reduction in local memory, assumes #subgroups=4
__local float reduceLM[SIMDGROUP_WIDTH * (N_SIMDGROUP - 1)];
if (sgid == 1) reduceLM[SIMDGROUP_WIDTH * 0 + slid] = sum;
if (sgid == 2) reduceLM[SIMDGROUP_WIDTH * 1 + slid] = sum;
if (sgid == 3) reduceLM[SIMDGROUP_WIDTH * 2 + slid] = sum;
barrier(CLK_LOCAL_MEM_FENCE);
if (sgid == 0) sum += reduceLM[SIMDGROUP_WIDTH * 0 + slid];
if (sgid == 0) sum += reduceLM[SIMDGROUP_WIDTH * 1 + slid];
if (sgid == 0) sum += reduceLM[SIMDGROUP_WIDTH * 2 + slid];
// 1 outputs per thread in subgroup 0
if (sgid == 0) {
dst = dst + (offsetd >> 2);
dst[i01 + i20 * ne01] = sum;
}
}