Eigen3 微小矩阵差异但开销大

Question

我想使用 eigen3 库计算两个 640x512 小矩阵之间的差异，但我最终遇到了一些高计算延迟（在 Intel Xeon 16 核 @ 2.4GHz 上为 45 毫秒）。我可以问你一些提示来改善这个异常的计算时间吗？下面是相关的代码片段：

static inline void tsnorm(stTime *ts) 
{
  while (ts->tv_nsec >= NSEC_PER_SEC) 
  {
    ts->tv_nsec -= NSEC_PER_SEC;
    ts->tv_sec++;
  }
}

  const unsigned short usRawFrameRows = 640;
  const unsigned short usRawFrameCols = 512;
  using  pixType = unsigned short;
  using pixDynMat = Matrix<pixType, Dynamic, Dynamic, RowMajor>;

  pixDynMat biasFrame = pixDynMat::Zero(usRawFrameRows, usRawFrameCols);
  pixType *myRawFrame = new pixType[usRawFrameRows * usRawFrameCols];

  struct timespec tBeforeProcessFrameCall, tAfterProcessFrameCall;
  clock_gettime(CLOCK_MONOTONIC_RAW, &tBeforeProcessFrameCall);
  tsnorm(&tBeforeProcessFrameCall); 
  
  // Substract the bias from the current raw frame
  MatrixXd calFrame = Map<pixDynMat>(myRawFrame, usRawFrameRows, usRawFrameCols).cast<double>() 
                      - biasFrame.cast<double>();

  clock_gettime(CLOCK_MONOTONIC_RAW, &tAfterProcessFrameCall);
  tsnorm(&tAfterProcessFrameCall); 

  cout << " PHI processFrame overhead (ms) = " << (tAfterProcessFrameCall.tv_nsec - tBeforeProcessFrameCall.tv_nsec)/1e6 << endl;

干杯！

西尔万

Answer 1

我编译了你的代码（i7-9700K）：

Compiler: g++ -O3 -march=native test.cpp -o testbin
====================================================
PHI processFrame overhead (ms) = 0.952253

然而，没有优化：

Compiler: g++ test.cpp -o testbin
====================================================
PHI processFrame overhead (ms) = 20.1365

我怀疑您缺少编译器优化。您可以尝试在启用优化的情况下进行编译。根据 FAQ 页面，这很容易让您获得十倍或更多的收益（参见 http://eigen.tuxfamily.org/index.php?title=FAQ#Optimization）。

Eigen3 微小矩阵差异但开销大

Eigen3 tiny matrices difference but large overhead

eigen3