问题描述
我有以下 Eigen C++ 代码，并进行了 10 万次 sqrednorm 计算。
有没有办法让它更健壮/更快。
#include <Eigen/Core>
#include <tbb/parallel_for.h>
#include "tbb/tbb.h"
#include <mutex>
#include <opencv2/opencv.hpp>
int main(){
int numberOFdata = 10000008;
Eigen::MatrixXf feat = Eigen::MatrixXf::Random(numberOFdata,512);
Eigen::MatrixXf b_cmp= Eigen::MatrixXf::Random(1,512);
int count_feature = feat.rows();
std::vector<int> found_number ;
std::mutex mutex1;
for (int loop = 0 ; loop<16 ; loop++){
double start_1 = static_cast<double>(cv::getTickCount());
tbb::affinity_partitioner ap;
tbb::parallel_for( tbb::blocked_range<int>(0,count_feature),[&](tbb::blocked_range<int> r )
{
for (int i=r.begin(); i<r.end(); ++i)
{
auto distance = ( feat.row(i)- b_cmp ).squarednorm();
if (distance < 0.5) {
mutex1.lock();
found_number.push_back(i);
mutex1.unlock();
}
}
},ap);
double timefin = ((double)cv::getTickCount() - start_1) / cv::getTickFrequency();
std::cout << count_feature << " TOTAL : " << timefin << std::endl;
}
}
编译标志：
-Xpreprocessor -std=c++11 -fopenmp -pthread -O3 -mavx2 -march=native -funroll-loops -fpermissive
本征版本 3.3.7 tbb opencv 和本征链接。
您可以删除 opencv 并使用不同的经过时间计算。
谢谢
解决方法
如果您按照访问 function listFolders(folder) {
var sheet = SpreadsheetApp.getActiveSheet();
sheet.appendRow(["Name","FileId"]); //writes the headers
var folder = DriveApp.getFolderById("XXXXXXXXXX")
var subfolders = folder.getFolders();
while (subfolders.hasNext()) {
var name = subfolders.next();
var files = name.getFiles();
var cnt = 0;
var file;
while (files.hasNext()) {
var file = files.next();
cnt++;
data = [
file.getName(),file.getId()
];
sheet.appendRow(data);
};
}
}
的相同顺序存储 feat，那么速度应该会快 4 倍左右（即，在您的情况下为 Eigen::RowMajor）。
删除所有非本征相关事物的最小示例：
int numberOFdata = 10000008;
Eigen::Matrix<float,Eigen::Dynamic,Eigen::RowMajor> feat = Eigen::MatrixXf::Random(numberOFdata,512);
Eigen::RowVectorXf b_cmp = Eigen::MatrixXf::Random(1,512);
int count_feature = feat.rows();
std::vector<int> found_number;
for (int loop = 0; loop < 16; loop++) {
auto start = std::chrono::steady_clock::now();
{
for (int i = 0; i < feat.rows(); ++i) {
float distance = (feat.row(i) - b_cmp).squaredNorm();
if (distance < 0.5f) {
found_number.push_back(i);
}
}
};
auto end = std::chrono::steady_clock::now();
std::chrono::duration<double> diff = end-start;
std::cout << count_feature << " TOTAL : " <<
diff.count() << std::endl;
}
Godbolt-Demo（由于内存限制减少了 feat 的维度）：https://godbolt.org/z/b6r5K4Yxv