[Rcpp-devel] Linking to c++ files in a package without Rcpp overhead for faster computation

[Qiang Kou]

Hi, John,

Making your code header-only is your best choice and it will make
everything easier.

If header-only is impossible, this can happen, there is one trick you may
want to try.

As I remember the early version of Rcpp, maybe before 0.9, it builds a
libRcpp.so when installing Rcpp.

You can also do this by adding several lines in Makevars [1] and write
helper functions to help system find the shared library you want to link to
[2].

But I don't think this is good practice for Rcpp developing.

Best wishes,

KK

[1] https://github.com/thirdwing/RcppMLPACK/blob/master/src/Makevars#L44-L61

[2] https://github.com/thirdwing/RcppMLPACK/blob/master/R/flags.R




On Fri, Mar 6, 2015 at 5:03 PM, John Tipton <jtipton25 at gmail.com> wrote:

> Hey Rcpp developers,
>
> I am brand spanking new to the Rcpp community and I want to introduce
> myself with what is likely a very simple question that I haven't found an
> answer for yet. My question is on package development and linking c++ files
> from one package directly to another package without having to create a
> CCallable function . As a relatively experienced R programmer but novice
> c++ programmer, I am still learning as I go so I created a minimal example
> below that I believe better illustrates my question.
>
> I am building a package with RStudio and I want to make available to
> another package the .h header files - (more explicitly the c++ subroutines
> in those headers) without the loss of computation speed shown below.
>
> My question can best be summarized with two parts
>
> 1) Why when I directly source testPack.h is the function call so much
> slower than when I define the function in the same .cpp file (i.e. why is
> fun1.cpp so much slower (~40%) than fun2.cpp in test.R)
>
> 2) How do I build a library in an automated fashion (maybe there is a
> CPPFLAGS variable?) so I can use the functionality of something like
> #include “path/to/file/hello_world2.h” in fun2.cpp without using an
> absolute path? I am building a large MCMC sampler so every bit of marginal
> speed gain is important. In other words, how can I replicate the behavior
> of fun2.cpp in a function that sources my library testPack
>
>
> I have the following files (outside my package) that provide testing.
> Thanks for any help.
>
> test.R
> fun1.cpp <- includes <testPack.h> header, runs slow
> fun2.cpp <- includes “hello_world2.h” header, runs faster
>
> I built a package skeleton in RStudio using Rcpp. Within the src directory
> I have the files
> hello_world2.h
> cpp_hello_world.cpp
>
>
> The files are as follows
> ##
> ##
> ##
> ———— begin test.R script ————
>
> library(rbenchmark)
> n <- 10000
> Rcpp::sourceCpp('~/test/fun1.cpp’)
> Rcpp::sourceCpp('~/test/fun2.cpp’)
>
> benchmark(fun1(n), fun2(n), replications = 500)
>
> ———— end test.R script ————
> ##
> ##
> ##
> ———— begin fun1.cpp ————
>
> #include <RcppArmadillo.h>
> #include <testPack.h>
> // [[Rcpp::depends(testPack)]]
> // [[Rcpp::depends(RcppArmadillo)]]
>
> //using namespace Rcpp;
>
> //[[Rcpp::export]]
> void fun1(const int& n) {
>    for(int i = 0; i < n; i++){
>     testPack::rcpp_hello_world();
>    }
> }
>
> ———— end fun1.cpp ————
> ##
> ##
> ##
> ———— begin fun2.cpp ————
>
> #include <RcppArmadillo.h>
> #include <path/to/file/testPack/src/hello_world2.h>
>
> // [[Rcpp::depends(RcppArmadillo)]]
>
> //[[Rcpp::export]]
> void fun2(const int& n) {
>    for(int i = 0; i < n; i++){
>     rcpp_hello_world2();
>    }
> }
>
> ———— end fun2.cpp ————
> ##
> ##
> ##
> ———— begin hello_world2.h ————
>
> Rcpp::List rcpp_hello_world2() {
>
>     Rcpp::CharacterVector x = Rcpp::CharacterVector::create("foo", "bar");
>     Rcpp::NumericVector y   = Rcpp::NumericVector::create(0.0, 1.0);
>     Rcpp::List z            = Rcpp::List::create(x, y);
>
>     return z ;
> }
>
> ———— end hello_world2.h ————
> ##
> ##
> ##
> ———— begin rcpp_hello_world.cpp ————
>
> #include <RcppArmadillo.h>
>
> // [[Rcpp::depends(RcppArmadillo)]]
> // [[Rcpp::interfaces(cpp)]]
>
> using namespace Rcpp;
>
> //[[Rcpp::export]]
> List rcpp_hello_world() {
>
>     CharacterVector x = CharacterVector::create( "foo", "bar" )  ;
>     NumericVector y   = NumericVector::create( 0.0, 1.0 ) ;
>     List z            = List::create( x, y ) ;
>
>     return z ;
> }
>
> ———— end rcpp_hello_world.cpp ————
>
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-- 
Qiang Kou
qkou at umail.iu.edu
School of Informatics and Computing, Indiana University
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