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opencl: add l2_norm (#20160)

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lhez
2026-03-06 18:03:05 -08:00
committed by GitHub
parent c024d85908
commit 6fce5c6a7d
3 changed files with 156 additions and 0 deletions
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ggml/src/ggml-opencl/ggml-opencl.cpp
+84
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@@ -497,6 +497,7 @@ struct ggml_backend_opencl_context {
kernel_geglu_f16, kernel_reglu_f16, kernel_swiglu_f16, kernel_geglu_erf_f16, kernel_geglu_quick_f16;
cl_kernel kernel_norm, kernel_norm_mul_add;
cl_kernel kernel_rms_norm, kernel_rms_norm_mul;
cl_kernel kernel_l2_norm_f32;
cl_kernel kernel_group_norm, kernel_group_norm_mul_add;
cl_kernel kernel_diag_mask_inf, kernel_diag_mask_inf_8;
cl_kernel kernel_diag_f32;
@@ -1585,6 +1586,23 @@ static void load_cl_kernels(ggml_backend_opencl_context *backend_ctx, ggml_cl_ve
GGML_LOG_CONT(".");
}
// l2_norm
{
#ifdef GGML_OPENCL_EMBED_KERNELS
const std::string kernel_src {
#include "l2_norm.cl.h"
};
#else
const std::string kernel_src = read_file("l2_norm.cl");
#endif
cl_program prog =
build_program_from_source(backend_ctx->context, backend_ctx->device, kernel_src.c_str(), compile_opts);
CL_CHECK((backend_ctx->kernel_l2_norm_f32 = clCreateKernel(prog, "kernel_l2_norm_f32", &err), err));
CL_CHECK(clReleaseProgram(prog));
GGML_LOG_CONT(".");
}
// rope
{
#ifdef GGML_OPENCL_EMBED_KERNELS
@@ -3689,6 +3707,8 @@ static bool ggml_opencl_supports_op(ggml_backend_dev_t dev, const struct ggml_te
return true;
case GGML_OP_RMS_NORM:
return op->ne[0] % 4 == 0 && ggml_is_contiguous_rows(op->src[0]);
case GGML_OP_L2_NORM:
return ggml_is_contiguous_rows(op->src[0]);
case GGML_OP_REPEAT:
return op->src[0]->type == GGML_TYPE_F32 && op->type == GGML_TYPE_F32; // Assuming F32 for now, can be expanded
case GGML_OP_PAD:
@@ -7554,6 +7574,64 @@ static void ggml_cl_group_norm(ggml_backend_t backend, const ggml_tensor * src0,
backend_ctx->enqueue_ndrange_kernel(kernel, 3, global_work_size, local_work_size, dst);
}
static void ggml_cl_l2_norm(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);
UNUSED(src1);
ggml_backend_opencl_context *backend_ctx = (ggml_backend_opencl_context *)backend->context;
ggml_tensor_extra_cl * extra0 = (ggml_tensor_extra_cl *)src0->extra;
ggml_tensor_extra_cl * extrad = (ggml_tensor_extra_cl *)dst->extra;
cl_ulong offset0 = extra0->offset + src0->view_offs;
cl_ulong offsetd = extrad->offset + dst->view_offs;
float eps;
memcpy(&eps, dst->op_params, sizeof(float));
GGML_TENSOR_LOCALS(int, ne0, src0, ne);
GGML_TENSOR_LOCALS(cl_ulong, nb0, src0, nb);
size_t sgs;
if (backend_ctx->gpu_family == ADRENO) {
sgs = 64;
} else if (backend_ctx->gpu_family == INTEL) {
sgs = 32;
} else {
GGML_ASSERT(false && "Unsupported GPU");
}
cl_kernel kernel = backend_ctx->kernel_l2_norm_f32;
int nth = sgs;
while (nth < ne00 && nth < (int)backend_ctx->get_kernel_workgroup_size(kernel)) {
nth *= 2;
}
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), &extrad->data_device));
CL_CHECK(clSetKernelArg(kernel, 3, sizeof(cl_ulong), &offsetd));
CL_CHECK(clSetKernelArg(kernel, 4, sizeof(int), &ne00));
CL_CHECK(clSetKernelArg(kernel, 5, sizeof(int), &ne01));
CL_CHECK(clSetKernelArg(kernel, 6, sizeof(int), &ne02));
CL_CHECK(clSetKernelArg(kernel, 7, sizeof(int), &ne03));
CL_CHECK(clSetKernelArg(kernel, 8, sizeof(cl_ulong), &nb01));
CL_CHECK(clSetKernelArg(kernel, 9, sizeof(cl_ulong), &nb02));
CL_CHECK(clSetKernelArg(kernel, 10, sizeof(cl_ulong), &nb03));
CL_CHECK(clSetKernelArg(kernel, 11, sizeof(float), &eps));
CL_CHECK(clSetKernelArg(kernel, 12, sizeof(float)*nth/sgs, NULL));
size_t global_work_size[] = {(size_t)ne01*nth, (size_t)ne02, (size_t)ne03};
size_t local_work_size[] = {(size_t)nth, 1, 1};
backend_ctx->enqueue_ndrange_kernel(kernel, 3, global_work_size, local_work_size, dst);
}
static void ggml_cl_tanh(ggml_backend_t backend, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
GGML_ASSERT(src0);
GGML_ASSERT(src0->extra);
@@ -12184,6 +12262,12 @@ bool ggml_cl_compute_forward(ggml_backend_t backend, struct ggml_tensor * tensor
}
func = ggml_cl_rms_norm;
break;
case GGML_OP_L2_NORM:
if (!any_on_device) {
return false;
}
func = ggml_cl_l2_norm;
break;
case GGML_OP_GROUP_NORM:
if (!any_on_device) {
return false;