R矩阵到犰狳的转换真的很慢 [英] Conversion of R matrices to armadillo is really slow

问题描述

观察

对于中等大小的矩阵，对于arma::mat类型，将矩阵从R传递到C ++的开销要比NumericMatrix类型慢得多.就像拍摄250倍左右的镜头一样.这是一个最小的例子

For medium-size matrices, the overheads on passing matrices from R to C++ are massively slower for arma::mat types than for NumericMatrix types. Like taking around 250x as long. Here's a minimal example

#include <RcppArmadillo.h>
// [[Rcpp::depends(RcppArmadillo)]]
using namespace Rcpp;
using namespace arma;

// [[Rcpp::export]]
double test_nm( NumericMatrix X ) {
  return 0.0 ;
}

// [[Rcpp::export]]
double test_arma( mat X ) {
  return 0.0 ;
}

// [[Rcpp::export]]
double test_nm_conv( NumericMatrix X ) {
  mat X_arma = as<mat>( X ) ; 
  return 0.0 ;
}

然后，在R中:

XX <- matrix( runif( 10000 ), 2000, 50 )
microbenchmark( test_nm( XX ), test_arma( XX ), ( XX ) )

Unit: microseconds
               expr      min       lq      mean   median       uq      max neval
        test_nm(XX)    5.541   16.154   16.0781   17.577   18.876   48.024   100
      test_arma(XX) 1280.946 1337.706 1404.0824 1361.237 1389.476 3385.868   100
   test_nm_conv(XX) 1277.417 1338.835 1393.4888 1358.128 1386.101 4355.533   100

因此，仅将矩阵作为arma::mat类型传递比NumericMatrix慢约250倍.太疯狂了！所以...

So just passing a matrix as an arma::mat type is around 250x slower than NumericMatrix. That's crazy! So...

提出的问题

1. 这是怎么回事?为什么mat so 比NumericMatrix慢得多?
2. 有没有解决这个问题的好方法?我遇到一个问题，我需要在一个被调用很多次的函数中为一些非常简单的矩阵代数使用arma::mat.我目前在整个过程中都使用arma类型，并且我的代码比我预期的要慢很多(这就是我最终编写上述愚蠢示例的方式). 250x的速度损失是如此之大，以至于我要重写大部分代码以在整个过程中使用NumericMatrix类型.实际上，我可能最终会为NumericMatrix和完全放弃arma类型编写自己的矩阵乘法函数.但是在我这样做之前，有没有更好的解决方案?

1. What's going on? Why is mat so much slower than NumericMatrix?
2. Is there a good way to deal with this? I've got a problem where I need to use an arma::mat for some fairly simple matrix algebra in a function that gets called a lot of times. I'm currently using arma types throughout, and my code is much slower than I expected (that's how I ended up cooking up the dumb examples above). A speed penalty of 250x is such a big deal that I'm about to rewrite large sections of code to use NumericMatrix types throughout. In fact, I might end up writing my own matrix multiplication function for NumericMatrix and abandon arma types altogether. But before I do, are there any better solutions?

(尽管我猜想另一种读法不是arma::mat从R类型转换很慢，而是NumericMatrix类型非常有效！)

(Although I guess another way to read this is not that arma::mat is slow to convert from R types, but that the NumericMatrix type is amazingly efficient!)

推荐答案

我相信这会创建一个新的犰狳矩阵，然后复制您的数字矩阵的内容.

I believe this creates a new Armadillo matrix then copies the contents of your numeric matrix.

要强制将NumericMatrix转换为arma :: mat类型，应使用以下代码:

To cast the NumericMatrix to type arma::mat, you should use the following:

// [[Rcpp::export]]
double test_const_arma( const mat& X ) { 
  return 0.0 ;
}

我的机器上的速度比较:

Speed comparison on my machine:

microbenchmark( test_const_arma( XX ), test_nm( XX ), test_arma( XX ), test_nm_conv( XX ))
## Unit: microseconds
##                 expr    min     lq     mean  median      uq     max neval
##  test_const_arma(XX)  1.852  2.381  3.69014  2.7885  4.3490  11.994   100
##          test_nm(XX)  1.925  2.455  3.47679  2.8535  3.5195  21.222   100
##        test_arma(XX) 68.593 71.212 83.63055 73.4555 98.8070 278.981   100
##     test_nm_conv(XX) 68.700 70.983 80.55983 73.1705 82.2665 183.484   100

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