This C++ API example demonstrates programming for Intel(R) Processor Graphics with OpenCL* extensions API in oneDNN.
#include <iostream>
#include <numeric>
#include <stdexcept>
#include <CL/cl.h>
#include "example_utils.hpp"
using namespace std;
#define OCL_CHECK(x) \
do { \
cl_int s = (x); \
if (s != CL_SUCCESS) { \
std::cout << "[" << __FILE__ << ":" << __LINE__ << "] '" << #x \
<< "' failed (status code: " << s << ")." << std::endl; \
exit(1); \
} \
} while (0)
cl_kernel create_init_opencl_kernel(
cl_context ocl_ctx, const char *kernel_name, const char *ocl_code) {
cl_int err;
const char *sources[] = {ocl_code};
cl_program ocl_program
= clCreateProgramWithSource(ocl_ctx, 1, sources, nullptr, &err);
OCL_CHECK(err);
OCL_CHECK(
clBuildProgram(ocl_program, 0, nullptr, nullptr, nullptr, nullptr));
cl_kernel ocl_kernel = clCreateKernel(ocl_program, kernel_name, &err);
OCL_CHECK(err);
OCL_CHECK(clReleaseProgram(ocl_program));
return ocl_kernel;
}
void gpu_opencl_interop_tutorial() {
const size_t N = std::accumulate(tz_dims.begin(), tz_dims.end(), (size_t)1,
std::multiplies<size_t>());
const char *ocl_code
= "__kernel void init(__global float *data) {"
" int id = get_global_id(0);"
" data[id] = (id % 2) ? -id : id;"
"}";
const char *kernel_name = "init";
cl_kernel ocl_init_kernel = create_init_opencl_kernel(
eng.get_ocl_context(), kernel_name, ocl_code);
cl_mem ocl_buf = mem.get_ocl_mem_object();
OCL_CHECK(clSetKernelArg(ocl_init_kernel, 0, sizeof(ocl_buf), &ocl_buf));
cl_command_queue ocl_queue = strm.get_ocl_command_queue();
OCL_CHECK(clEnqueueNDRangeKernel(ocl_queue, ocl_init_kernel, 1, nullptr, &N,
nullptr, 0, nullptr, nullptr));
strm.wait();
std::vector<float> mem_data(N);
read_from_dnnl_memory(mem_data.data(), mem);
for (size_t i = 0; i < N; i++) {
float expected = (i % 2) ? 0.0f : (float)i;
if (mem_data[i] != expected) {
std::cout << "Expect " << expected << " but got " << mem_data[i]
<< "." << std::endl;
throw std::logic_error("Accuracy check failed.");
}
}
OCL_CHECK(clReleaseKernel(ocl_init_kernel));
}
int main(int argc, char **argv) {
return handle_example_errors(
}
@ eltwise_relu
Elementwise: rectified linear unit (ReLU)
Definition dnnl.hpp:490
@ forward
Forward data propagation, alias for dnnl::prop_kind::forward_training.
Definition dnnl.hpp:455
#define DNNL_ARG_DST
A special mnemonic for destination argument for primitives that have a single destination.
Definition dnnl_types.h:1806
#define DNNL_ARG_SRC
A special mnemonic for source argument for primitives that have a single source.
Definition dnnl_types.h:1782
oneDNN namespace
Definition dnnl.hpp:81
Descriptor for an elementwise forward propagation primitive.
Definition dnnl.hpp:5488
Primitive descriptor for an elementwise forward propagation primitive.
Definition dnnl.hpp:5522
Elementwise unary operation forward propagation primitive.
Definition dnnl.hpp:5486
An execution engine.
Definition dnnl.hpp:844
@ gpu
GPU engine.
Definition dnnl.hpp:855
A memory descriptor.
Definition dnnl.hpp:1729
Memory object.
Definition dnnl.hpp:1188
@ nchw
4D CNN activations tensor; an alias for dnnl::memory::format_tag::abcd
Definition dnnl.hpp:1359
@ f32
32-bit/single-precision floating point.
Definition dnnl.hpp:1216
std::vector< dim > dims
Vector of dimensions.
Definition dnnl.hpp:1193
An execution stream.
Definition dnnl.hpp:1047