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;
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;
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;
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);
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));
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");
}
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);
CL_BUFFER_CREATE_TYPE_REGION, ®ion, &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));
{ extra->q }
};
extra->q_img = clCreateImage(context, CL_MEM_READ_ONLY, &img_format_q, &img_desc_q, NULL, &err);
-
tensor->extra = extra;
return;
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));
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];
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, ®ion, &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, ®ion, &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;
--- /dev/null
+#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;
+ }
+
+}
--- /dev/null
+#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;
+ }
+
+}
overview / pkg / ggml / sources / llama.cpp / commitdiff