#include // cout #include #include // srand, rand, atoi #include // timespec, clock_gettime const int RANDOM_MAX = 1000; const int RANDOM_MIN = 1; timespec diff(timespec start, timespec end) { timespec temp; if ((end.tv_nsec-start.tv_nsec)<0) { temp.tv_sec = end.tv_sec-start.tv_sec-1; temp.tv_nsec = 1000000000+end.tv_nsec-start.tv_nsec; } else { temp.tv_sec = end.tv_sec-start.tv_sec; temp.tv_nsec = end.tv_nsec-start.tv_nsec; } return temp; } void serialConvolution(std::vector& output, const std::vector& input, const std::vector& kernel) { float sum; int middle = kernel.size() / 2; for (size_t i = 0; i < input.size(); i++) { sum = 0; for (int j = -middle; j <= middle; j++) if ( (int)i+j < 0 ) { sum += input[0] * kernel[j+middle]; } else if ( i+j > input.size()-1 ) { sum += input[input.size()-1] * kernel[j+middle]; } else { sum += input[i+j] * kernel[j+middle]; } output[i] = sum; } } int main(int argc, char* argv[]) { if (argc != 3) { std::cout << "Usage: " << argv[0] << " " << std::endl; exit(1); } const int NUMBER_OF_THREADS = atoi(argv[1]); const int DATA_SIZE = atoi(argv[2]); const int CHUNK_SIZE = DATA_SIZE / NUMBER_OF_THREADS; srand(time(NULL)); std::vector data(DATA_SIZE); for (int i = 0; i < DATA_SIZE; i++) data[i] = rand() % RANDOM_MAX + RANDOM_MIN; // the kernel for the gaussian smooth float kernelArray[7] = { 0.06, 0.061, 0.242, 0.383, 0.242, 0.061, 0.06 }; std::vector kernel (kernelArray, kernelArray + sizeof(kernelArray) / sizeof(float) ); // the convolution is not in-place, the result is stored in output std::vector output(DATA_SIZE); timespec startTime; clock_gettime(CLOCK_MONOTONIC, &startTime); serialConvolution(output, data, kernel); timespec endTime; clock_gettime(CLOCK_MONOTONIC, &endTime); timespec timeDiff = diff(startTime, endTime); std::cout << timeDiff.tv_sec << "." << timeDiff.tv_nsec << std::endl; return 0; }