I am developing a statistical model and I have a prototype working in R code. I make extensive use of sparse matrices, so the R code is pretty fast, but hoped that using RCppEigen to evaluate the log-likelihood function could avoid a lot of memory copying and be substantially faster. However, in a simple example I am seeing that RCppEigen is 3-5x slower than standard R code for cholesky decomposition of a sparse matrix. This is the case on R 3.5.1 using RcppEigen_0.3.3.4.0 on both OS X and CentOS 6.9.
Since this simple operation is so much slower it doesn't seem like using RCppEigen is worth it in this case. Is this an issue with BLAS, some libraries or compiler options, or is R code really the fastest option? library(Matrix) library(inline) # construct sparse matrix ######################### # construct a matrix C that is N x N with S total entries # set C = crossprod(X) N = 100000 S = 1000000 i = sample(1:1000, S, replace=TRUE) j = sample(1:1000, S, replace=TRUE) values = runif(S, 0, .3) X = sparseMatrix(i=i, j=j, x = values, symmetric=FALSE ) C = as(crossprod(X), "dgCMatrix") # check sparsity fraction S / N^2 # define RCppEigen code CholeskyCppSparse<-' using Rcpp::as; using Eigen::Map; using Eigen::SparseMatrix; using Eigen::MappedSparseMatrix; using Eigen::SimplicialLLT; // get data into RcppEigen const MappedSparseMatrix<double> Sigma(as<MappedSparseMatrix<double> >(Sigma_in)); // compute Cholesky typedef SimplicialLLT<SparseMatrix<double> > SpChol; const SpChol Ch(Sigma); ' CholSparse <- cxxfunction(signature(Sigma_in = "dgCMatrix"), CholeskyCppSparse, plugin = "RcppEigen") # compare times system.time(replicate(10, chol( C ))) # output: # user system elapsed # 0.341 0.014 0.355 system.time(replicate(10, CholSparse( C ))) # output: # user system elapsed # 1.639 0.046 1.687 sessionInfo() R version 3.5.1 (2018-07-02) Platform: x86_64-apple-darwin15.6.0 (64-bit) Running under: macOS 10.14 Matrix products: default BLAS: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRblas.0.dylib LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib locale: [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8 attached base packages: [1] stats graphics grDevices datasets utils methods base other attached packages: [1] inline_0.3.15 Matrix_1.2-15 loaded via a namespace (and not attached): [1] compiler_3.5.1 RcppEigen_0.3.3.4.0 Rcpp_1.0.0 [4] grid_3.5.1 lattice_0.20-38 Changing the size of the matrix and the number of entries does not change the relative times much Thanks, - Gabriel
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