On 26 August 2011 at 08:37, Davor Cubranic wrote: | On August 25, 2011 05:32:45 PM Dirk Eddelbuettel wrote: | > Long story short I just committed a new self-contained example to the Rcpp | > source which you can look at (and copy) via the URL | [...] | > The results bear this out. On my (standard i7, four cores hyperthreaded) | > box: | > | > edd@max:~$ r ~/svn/rcpp/pkg/Rcpp/inst/examples/OpenMP/OpenMPandInline.r | > Loading required package: methods | > test replications elapsed relative user.self sys.self | > 2 funOpenMP(z) 100 3.219 1.000000 25.26 0.07 | > 3 funSerialRcpp(z) 100 9.030 2.805219 9.43 0.32 | > 4 funSugarRcpp(z) 100 9.423 2.927307 9.06 0.35 | > 1 funSerial(z) 100 9.601 2.982603 9.59 0.00 | > edd@max:~$ | > | [...] | > Rcpp sugar has no real leg up on manual loops, but is the shortest | > implementation in two lines. Looping over an Rcpp vector is a little faster | > than looping over a C++ STL vector (which incurs a copy). | | I know you wanted to keep all code looking the same, but with std::transform | all serial code is very short:
Good thinking, I'll make that change! | serialStdAlgCode <- ' | std::vector<double> x = Rcpp::as<std::vector< double > >(xs); | std::transform(x.begin(), x.end(), x.begin(), ::log); | return Rcpp::wrap(x); | ' | funSerialStdAlg <- cxxfunction(signature(xs="numeric"), body=serialStdAlgCode, | plugin="Rcpp") | | serialStdAlgRcppCode <- ' | Rcpp::NumericVector x = Rcpp::NumericVector(xs); | std::transform(x.begin(), x.end(), x.begin(), ::log); | return x; | ' | funSerialStdAlgRcpp <- cxxfunction(signature(xs="numeric"), | body=serialStdAlgRcppCode, plugin="Rcpp") That's much nicer. And quicker. Nice :) | The results (without OpenMP because I'm currently on a single-core CPU): | | test replications elapsed relative user.self sys.self | 3 funSerialStdAlgRcpp(z) 20 4.236 1.000000 3.792 0.252 | 4 funSerialRcpp(z) 20 4.312 1.017941 3.792 0.272 | 5 funSugarRcpp(z) 20 4.537 1.071058 3.744 0.588 | 2 funSerialStdAlg(z) 20 5.514 1.301700 4.329 0.884 | 1 funSerial(z) 20 5.536 1.306893 4.480 0.808 Thanks for the suggestion. Dirk -- Two new Rcpp master classes for R and C++ integration scheduled for New York (Sep 24) and San Francisco (Oct 8), more details are at http://dirk.eddelbuettel.com/blog/2011/08/04#rcpp_classes_2011-09_and_2011-10 http://www.revolutionanalytics.com/products/training/public/rcpp-master-class.php _______________________________________________ Rcpp-devel mailing list Rcpp-devel@lists.r-forge.r-project.org https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/rcpp-devel
