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103 lines
3.4 KiB
103 lines
3.4 KiB
// Patric Zhao: patric.zhao@intel.com
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#include <CL/sycl.hpp>
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#include <iostream>
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using namespace sycl;
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constexpr int64_t N = 10000000;
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int main() {
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// Enable queue profiling
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auto propList = cl::sycl::property_list {cl::sycl::property::queue::enable_profiling()};
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queue my_gpu_queue(gpu_selector{}, propList);
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std::cout << "Selected GPU device: " <<
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my_gpu_queue.get_device().get_info<info::device::name>() << "\n";
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int *host_mem = malloc_host<int>(N, my_gpu_queue);
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int *cpu_mem = malloc_host<int>(N, my_gpu_queue);
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int *device_mem = malloc_device<int>(N, my_gpu_queue);
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// Init CPU data
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for(int64_t i = 0; i < N; i++) {
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host_mem[i] = i % 6666;
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}
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float duration_cpu = 0.0;
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float duration_gpu_a = 0.0;
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float duration_gpu_b = 0.0;
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float duration_gpu_c = 0.0;
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std::chrono::high_resolution_clock::time_point s, e;
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std::chrono::high_resolution_clock::time_point s_a, e_a;
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std::chrono::high_resolution_clock::time_point s_b, e_b;
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std::chrono::high_resolution_clock::time_point s_c, e_c;
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// CPU computation
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printf("\n Start CPU Computation, Number of Elems = %ld \n", N);
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s = std::chrono::high_resolution_clock::now();
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// CPU code here
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for(int64_t i = 0; i < N; i++) {
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cpu_mem[i] = host_mem[i] * 2;
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}
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e = std::chrono::high_resolution_clock::now();
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duration_cpu = std::chrono::duration<float, std::milli>(e - s).count();
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printf("\n End CPU Computation, Time = %lf \n", duration_cpu);
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// warmup
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/*********************************************************************/
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my_gpu_queue.memcpy(device_mem, host_mem, N * sizeof(int)).wait();
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my_gpu_queue.submit([&](handler& h) {
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// Parallel Computation
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h.parallel_for(range{N}, [=](id<1> item) {
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device_mem[item] *= 2;
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});
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});
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my_gpu_queue.wait();
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/*********************************************************************/
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s_c = std::chrono::high_resolution_clock::now();
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// Copy from host(CPU) to device(GPU)
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my_gpu_queue.memcpy(device_mem, host_mem, N * sizeof(int)).wait();
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s_b = std::chrono::high_resolution_clock::now();
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s_a = std::chrono::high_resolution_clock::now();
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// submit the content to the queue for execution
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auto event = my_gpu_queue.submit([&](handler& h) {
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// Parallel Computation
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h.parallel_for(range{N}, [=](id<1> item) {
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device_mem[item] *= 2;
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});
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});
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// wait the computation done
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my_gpu_queue.wait();
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e_b = std::chrono::high_resolution_clock::now();
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duration_gpu_b = std::chrono::duration<float, std::milli>(e_b - s_b).count();
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duration_gpu_a =
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(event.get_profiling_info<info::event_profiling::command_end>() -
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event.get_profiling_info<info::event_profiling::command_start>()) /1000.0f/1000.0f;
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// Copy back from GPU to CPU
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my_gpu_queue.memcpy(host_mem, device_mem, N * sizeof(int)).wait();
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e_c = std::chrono::high_resolution_clock::now();
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duration_gpu_c = std::chrono::duration<float, std::milli>(e_c - s_c).count();
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printf("\n GPU Computation, GPU Time A = %lf \n", duration_gpu_a);
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printf("\n GPU Computation, GPU Time B = %lf \n", duration_gpu_b);
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printf("\n GPU Computation, GPU Time C = %lf \n", duration_gpu_c);
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printf("\nTask Done!\n");
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return 0;
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}
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