网站流量统计平台,如何利用网站做demo,上海市网,seo网站结构如何优化CUDA程序错误检测
所有CUDA的API函数都有一个类型为cudaError_t的返回值#xff0c;代表了一种错误信息#xff1b;只有返回cudaSuccess时#xff0c;才是成功调用。
cudaGetLastError()用来检测核函数的执行是否出错cudaGetErrorString()输出错误信息
#include stdi…CUDA程序错误检测
所有CUDA的API函数都有一个类型为cudaError_t的返回值代表了一种错误信息只有返回cudaSuccess时才是成功调用。
cudaGetLastError()用来检测核函数的执行是否出错cudaGetErrorString()输出错误信息
#include stdio.h
#include cuda_runtime.h
#include device_launch_parameters.h
#includemath.h
#include malloc.h
#include opencv2/opencv.hpp
#include stdlib.h#define BLOCK_SIZE 1//图像卷积 GPU
__global__ void sobel_gpu(unsigned char* in, unsigned char* out, const int Height, const int Width)
{int x blockDim.x * blockIdx.x threadIdx.x;int y blockDim.y blockIdx.y threadIdx.y;int index y * Width x;int Gx 0;int Gy 0;unsigned char x0, x1, x2, x3, x4, x5, x6, x7, x8;if (x0 x(Width-1) y0 y(Height-1)){x0 in[(y - 1)*Width (x - 1)];x1 in[(y - 1)*Width (x)];x2 in[(y - 1)*Width (x 1)];x3 in[(y)*Width (x - 1)];x5 in[(y)*Width (x 1)];x6 in[(y 1)*Width (x - 1)];x7 in[(y 1)*Width (x)];x8 in[(y 1)*Width (x 1)];Gx (x0 2 * x3 x6) - (x2 2 * x5 x8);Gy (x0 2 * x1 x2) - (x6 2 * x7 x8);out[index] (abs(Gx) abs(Gy)) / 2;}
}int main()
{cv::Mat src;src cv::imread(complete004.jpg);cv::Mat grayImg,gaussImg;cv::cvtColor(src, grayImg, cv::COLOR_BGR2GRAY);cv::GaussianBlur(grayImg, gaussImg, cv::Size(3,3), 0, 0, cv::BORDER_DEFAULT);int height src.rows;int width src.cols;//输出图像cv::Mat dst_gpu(height, width, CV_8UC1, cv::Scalar(0));//GPU存储空间int memsize height * width * sizeof(unsigned char);//输入 输出unsigned char* in_gpu;unsigned char* out_gpu;cudaMalloc((void**)in_gpu, memsize);cudaMalloc((void**)out_gpu, memsize);cudaError_t error_code;dim3 threadsPreBlock(BLOCK_SIZE, BLOCK_SIZE);dim3 blocksPreGrid((width threadsPreBlock.x - 1)/threadsPreBlock.x, (height threadsPreBlock.y - 1)/threadsPreBlock.y);cudaMemcpy(in_gpu, gaussImg.data, memsize, cudaMemcpyHostToDevice);sobel_gpu blocksPreGrid, threadsPreBlock (in_gpu, out_gpu, height, width);error_code cudaGetLastError();printf(Error: %s\n, cudaGetErrorString(error_code));printf(FILE: %s\n, __FILE__);printf(LINE: %d\n, __LINE__);printf(Error code: %d\n, error_code);cudaMemcpy(dst_gpu.data, out_gpu, memsize, cudaMemcpyDeviceToHost);cv::imwrite(dst_gpu_save.png, dst_gpu);//cv::namedWindow(src, cv::WINDOW_NORMAL);cv::imshow(src, src);cv::imshow(dst_gpu, dst_gpu);cv::waitKey();cudaFree(in_gpu);cudaFree(out_gpu);return 0;
} 樊哲勇大牛的检测CUDA运行时错误的宏函数
#pragma once
#includestdio.h#define CHECK(call) \
do \
{ \const cudaError_t error_code call; \if (error_code ! cudaSuccess) \{ \printf(CUDA Error:\n); \printf( File: %s\n, __FILE__); \printf( Line: %d\n,__LINE__); \printf( Error code: %d\n,error_code); \printf( Error text: %s\n, cudaGetErrorString(error_code)); \exit(1); \} \
} while (0)
采用检测CUDA运行时错误的宏函数
#include stdio.h
#include cuda_runtime.h
#include device_launch_parameters.h
#includemath.h
#include malloc.h
#include opencv2/opencv.hpp
#include stdlib.h#include error.cuh#define BLOCK_SIZE 1//图像卷积 GPU
__global__ void sobel_gpu(unsigned char* in, unsigned char* out, const int Height, const int Width)
{int x blockDim.x * blockIdx.x threadIdx.x;int y blockDim.y blockIdx.y threadIdx.y;int index y * Width x;int Gx 0;int Gy 0;unsigned char x0, x1, x2, x3, x4, x5, x6, x7, x8;if (x0 x(Width-1) y0 y(Height-1)){x0 in[(y - 1)*Width (x - 1)];x1 in[(y - 1)*Width (x)];x2 in[(y - 1)*Width (x 1)];x3 in[(y)*Width (x - 1)];x5 in[(y)*Width (x 1)];x6 in[(y 1)*Width (x - 1)];x7 in[(y 1)*Width (x)];x8 in[(y 1)*Width (x 1)];Gx (x0 2 * x3 x6) - (x2 2 * x5 x8);Gy (x0 2 * x1 x2) - (x6 2 * x7 x8);out[index] (abs(Gx) abs(Gy)) / 2;}
}int main()
{cv::Mat src;src cv::imread(complete004.jpg);cv::Mat grayImg,gaussImg;cv::cvtColor(src, grayImg, cv::COLOR_BGR2GRAY);cv::GaussianBlur(grayImg, gaussImg, cv::Size(3,3), 0, 0, cv::BORDER_DEFAULT);int height src.rows;int width src.cols;//输出图像cv::Mat dst_gpu(height, width, CV_8UC1, cv::Scalar(0));//GPU存储空间int memsize height * width * sizeof(unsigned char);//输入 输出unsigned char* in_gpu;unsigned char* out_gpu;cudaMalloc((void**)in_gpu, memsize);cudaMalloc((void**)out_gpu, memsize);dim3 threadsPreBlock(BLOCK_SIZE, BLOCK_SIZE);dim3 blocksPreGrid((width threadsPreBlock.x - 1)/threadsPreBlock.x, (height threadsPreBlock.y - 1)/threadsPreBlock.y);cudaMemcpy(in_gpu, gaussImg.data, memsize, cudaMemcpyHostToDevice);sobel_gpu blocksPreGrid, threadsPreBlock (in_gpu, out_gpu, height, width);CHECK(cudaMemcpy(dst_gpu.data, out_gpu, memsize*10, cudaMemcpyDeviceToHost));//增大size值 引起报错cv::imwrite(dst_gpu_save.png, dst_gpu);//cv::namedWindow(src, cv::WINDOW_NORMAL);cv::imshow(src, src);cv::imshow(dst_gpu, dst_gpu);cv::waitKey();cudaFree(in_gpu);cudaFree(out_gpu);return 0;
}
