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opencl : add GEGLU, REGLU, SWIGLU (#14456)

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lhez
2025-07-01 00:19:16 -07:00
committed by GitHub
parent 0a5a3b5cdf
commit 79b33b2317
3 changed files with 326 additions and 0 deletions
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124
ggml/src/ggml-opencl/ggml-opencl.cpp
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@@ -351,6 +351,7 @@ struct ggml_backend_opencl_context {
cl_program program_gemv_noshuffle_general;
cl_program program_gemv_noshuffle;
cl_program program_get_rows;
cl_program program_glu;
cl_program program_im2col_f16;
cl_program program_im2col_f32;
cl_program program_mul_mat_Ab_Bi_8x4;
@@ -401,6 +402,8 @@ struct ggml_backend_opencl_context {
cl_kernel kernel_relu;
cl_kernel kernel_sigmoid_f32, kernel_sigmoid_f16;
cl_kernel kernel_clamp;
cl_kernel kernel_geglu, kernel_reglu, kernel_swiglu,
kernel_geglu_f16, kernel_reglu_f16, kernel_swiglu_f16;
cl_kernel kernel_norm;
cl_kernel kernel_rms_norm;
cl_kernel kernel_group_norm;
@@ -738,6 +741,27 @@ static void load_cl_kernels(ggml_backend_opencl_context *backend_ctx, ggml_cl_ve
GGML_LOG_CONT(".");
}
// glu
{
#ifdef GGML_OPENCL_EMBED_KERNELS
const std::string kernel_src {
#include "glu.cl.h"
};
#else
const std::string kernel_src = read_file("glu.cl");
#endif
backend_ctx->program_glu =
build_program_from_source(backend_ctx->context, backend_ctx->device, kernel_src.c_str(), compile_opts);
CL_CHECK((backend_ctx->kernel_geglu = clCreateKernel(backend_ctx->program_glu, "kernel_geglu", &err), err));
CL_CHECK((backend_ctx->kernel_reglu = clCreateKernel(backend_ctx->program_glu, "kernel_reglu", &err), err));
CL_CHECK((backend_ctx->kernel_swiglu = clCreateKernel(backend_ctx->program_glu, "kernel_swiglu", &err), err));
CL_CHECK((backend_ctx->kernel_geglu_f16 = clCreateKernel(backend_ctx->program_glu, "kernel_geglu_f16", &err), err));
CL_CHECK((backend_ctx->kernel_reglu_f16 = clCreateKernel(backend_ctx->program_glu, "kernel_reglu_f16", &err), err));
CL_CHECK((backend_ctx->kernel_swiglu_f16 = clCreateKernel(backend_ctx->program_glu, "kernel_swiglu_f16", &err), err));
GGML_LOG_CONT(".");
}
// get_rows
{
#ifdef GGML_OPENCL_EMBED_KERNELS
@@ -2242,6 +2266,15 @@ static bool ggml_opencl_supports_op(ggml_backend_dev_t dev, const struct ggml_te
default:
return false;
}
case GGML_OP_GLU:
switch (ggml_get_glu_op(op)) {
case GGML_GLU_OP_GEGLU:
case GGML_GLU_OP_REGLU:
case GGML_GLU_OP_SWIGLU:
return ggml_is_contiguous_1(op->src[0]) && (op->type == GGML_TYPE_F32 || op->type == GGML_TYPE_F16);
default:
return false;
}
case GGML_OP_CLAMP:
return op->src[0]->type == GGML_TYPE_F32;
case GGML_OP_SOFT_MAX:
@@ -6143,6 +6176,91 @@ static void ggml_cl_sum_rows(ggml_backend_t backend, const ggml_tensor * src0, c
backend_ctx->enqueue_ndrange_kernel(kernel, 3, global_work_size, local_work_size, dst);
}
static void ggml_cl_glu(ggml_backend_t backend, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
GGML_ASSERT(src0);
GGML_ASSERT(src0->extra);
GGML_ASSERT(dst);
GGML_ASSERT(dst->extra);
GGML_ASSERT(ggml_is_contiguous_1(src0));
if (src1) {
GGML_ASSERT(src1);
GGML_ASSERT(src1->extra);
GGML_ASSERT(ggml_are_same_shape(src0, src1));
}
ggml_backend_opencl_context *backend_ctx = (ggml_backend_opencl_context *)backend->context;
cl_kernel kernel;
switch (ggml_get_glu_op(dst)) {
case GGML_GLU_OP_GEGLU:
if (dst->type == GGML_TYPE_F32) {
kernel = backend_ctx->kernel_geglu;
} else {
kernel = backend_ctx->kernel_geglu_f16;
}
break;
case GGML_GLU_OP_REGLU:
if (dst->type == GGML_TYPE_F32) {
kernel = backend_ctx->kernel_reglu;
} else {
kernel = backend_ctx->kernel_reglu_f16;
}
break;
case GGML_GLU_OP_SWIGLU:
if (dst->type == GGML_TYPE_F32) {
kernel = backend_ctx->kernel_swiglu;
} else {
kernel = backend_ctx->kernel_swiglu_f16;
}
break;
default:
GGML_ABORT("Unsupported glu op");
}
ggml_tensor_extra_cl * extra0 = (ggml_tensor_extra_cl *)src0->extra;
ggml_tensor_extra_cl * extrad = (ggml_tensor_extra_cl *)dst->extra;
ggml_tensor_extra_cl * extra1 = src1 ? (ggml_tensor_extra_cl *)src1->extra : nullptr;
cl_ulong offset0 = extra0->offset + src0->view_offs;
cl_ulong offsetd = extrad->offset + dst->view_offs;
cl_ulong offset1 = extra1 ? extra1->offset + src1->view_offs : offset0;
const int ne0 = dst->ne[0];
const cl_ulong nb01 = src0->nb[1];
const cl_ulong nb11 = src1 ? src1->nb[1] : nb01;
const cl_ulong nb1 = dst->nb[1];
const int swp = ((const int32_t *) dst->op_params)[1];
const int ne00_off = src1 ? 0 : (swp ? ne0 : 0);
const int ne10_off = src1 ? 0 : (swp ? 0 : ne0);
CL_CHECK(clSetKernelArg(kernel, 0, sizeof(cl_mem), &extra0->data_device));
CL_CHECK(clSetKernelArg(kernel, 1, sizeof(cl_ulong), &offset0));
CL_CHECK(clSetKernelArg(kernel, 2, sizeof(cl_mem), src1 ? &extra1->data_device : &extra0->data_device));
CL_CHECK(clSetKernelArg(kernel, 3, sizeof(cl_ulong), &offset1));
CL_CHECK(clSetKernelArg(kernel, 4, sizeof(cl_mem), &extrad->data_device));
CL_CHECK(clSetKernelArg(kernel, 5, sizeof(cl_ulong), &offsetd));
CL_CHECK(clSetKernelArg(kernel, 6, sizeof(cl_ulong), &nb01));
CL_CHECK(clSetKernelArg(kernel, 7, sizeof(cl_ulong), &nb11));
CL_CHECK(clSetKernelArg(kernel, 8, sizeof(int), &ne0));
CL_CHECK(clSetKernelArg(kernel, 9, sizeof(cl_ulong), &nb1));
CL_CHECK(clSetKernelArg(kernel, 10, sizeof(int), &ne00_off));
CL_CHECK(clSetKernelArg(kernel, 11, sizeof(int), &ne10_off));
const size_t nrows = ggml_nrows(src0);
size_t nth = 512;
size_t global_work_size[] = {nrows*nth, 1, 1};
size_t local_work_size[] = {nth, 1, 1};
backend_ctx->enqueue_ndrange_kernel(kernel, 3, global_work_size, local_work_size, dst);
}
//------------------------------------------------------------------------------
// Op offloading
//------------------------------------------------------------------------------
@@ -6244,6 +6362,12 @@ bool ggml_cl_compute_forward(ggml_backend_t backend, struct ggml_tensor * tensor
default:
return false;
} break;
case GGML_OP_GLU:
if (!any_on_device) {
return false;
}
func = ggml_cl_glu;
break;
case GGML_OP_CLAMP:
if (!any_on_device) {
return false;