GPU和CPU耗时统计方法

GPU端耗时统计

     cudaEvent_t start, stop;

     checkCudaErrors(cudaEventCreate(&start));

     checkCudaErrors(cudaEventCreate(&stop));

     checkCudaErrors(cudaDeviceSynchronize());

     float gpu_time = 0.0f;

     cudaEventRecord(start, );//cuda context中的操作完毕事件被记录

     //分配设备端内存

     float *d_idata;

     checkCudaErrors(cudaMalloc((void **) &d_idata, mem_size));

     //将主机端数据拷贝到设备端内存

     checkCudaErrors(cudaMemcpy(d_idata, h_idata, mem_size,  cudaMemcpyHostToDevice));

     //设备端为结果分配内存

     float *d_odata;

     checkCudaErrors(cudaMalloc((void **) &d_odata, mem_size));

     //设置执行参数

     dim3  grid(, , );

     dim3  threads(num_threads, , );

     //执行内核，参数含义：grid是网格的纬度，threads是块的纬度，mem_size最多能动态分配的共享内存大小

     testKernel<<< grid, threads, mem_size >>>(d_idata, d_odata);

     //检查内核执行状态

     getLastCudaError("Kernel execution failed");

     //在主机端为结果分配内存

     float *h_odata = (float *) malloc(mem_size);

     //从设备端拷贝结果到主机端

     checkCudaErrors(cudaMemcpy(h_odata, d_odata, sizeof(float) * num_threads,

                                cudaMemcpyDeviceToHost));

     cudaEventRecord(stop, );

     unsigned long int counter = ;

     while (cudaEventQuery(stop) == cudaErrorNotReady)

     {

         counter++;

     }

     checkCudaErrors(cudaEventElapsedTime(&gpu_time, start, stop));

     printf("GPU执行耗时: %.2f (ms)\n", gpu_time);

     printf("CPU executed %lu iterations while waiting for GPU to finish\n", counter);

CPU端耗时统计

     StopWatchInterface *timer = ;

     sdkCreateTimer(&timer);

     sdkResetTimer(&timer);

     sdkStartTimer(&timer);

     //计算参考方案

     float *reference = (float *) malloc(mem_size);

     computeGold(reference, h_idata, num_threads);

     sdkStopTimer(&timer);

     printf("串行耗时：%f (ms)\n", sdkGetTimerValue(&timer));