I believe you have the wrong list. (Read the Posting Guide... you seem to have R under control.) Try Rcpp-devel.
FWIW You probably need to spend some time with a C++ profiler... any language can be unintentionally mis-used, and you first need to identify whether your calling code is inefficiently handling memory or invoking setup code repetitively before blaming BLAS. A reproducible example will probably help when you ask at Rcpp-devel. On November 21, 2018 10:34:33 AM PST, "Hoffman, Gabriel" <gabriel.hoff...@mssm.edu> wrote: >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? > >Here is my example: > >library(Matrix) >library(inline) > ># construct sparse matrix >######################### > ># construct a matrix C that is N x X with S total entries >N = 10000 >S = 1000000 >i = sample(1:1000, S, replace=TRUE) >j = sample(1:1000, S, replace=TRUE) >idx = i >= j >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 > >Thanks, >- Gabriel > > > > > [[alternative HTML version deleted]] -- Sent from my phone. Please excuse my brevity. ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
