similar to: Is it possible to pass a function argument from R to compiled code in C?

R Developers, Could someone help explain what it means that R is single threaded? I am trying to understand what is actually going on inside R when users want to parallelize code. For example, using mclapply or foreach (with some backend) somehow allows users to benefit from multiple CPUs. Similarly there is the RcppParallel package for RMatrix/RVector objects. But none of these address the

On 12 May 2016 at 13:11, Mark van der Loo wrote: | Charles, | | 1. Perhaps this question is better directed at the R-help or | R-pacakge-devel mailinglist. | | 2. It basically means that R itself can only evaluate one R expression at | the time. | | The parallel package circumvents this by starting multiple R-sessions and | dividing workload. | | Compiled code called by R (such as C++ code

Charles, 1. Perhaps this question is better directed at the R-help or R-pacakge-devel mailinglist. 2. It basically means that R itself can only evaluate one R expression at the time. The parallel package circumvents this by starting multiple R-sessions and dividing workload. Compiled code called by R (such as C++ code through RCpp or C-code through base R's interface) can execute

I believe the performance of isUnsorted() in sort.c could be improved by calling REAL() once (outside of the for loop), rather than calling it twice inside the loop. As an aside, it is implemented in the faster way in doSort() (sort.c line 401). The example below shows the performance improvement for a vectors of double of moving REAL() outside the for loop. # example as implemented in

Hi all, I'm not sure if I'm not supposed to do the following (the dyn.unload part, I mean) or this could be a bug (in R or Rcpp): ``` Rcpp::sourceCpp(code=' #include <Rcpp.h> class Object {}; //[[Rcpp::export]] SEXP new_object() { return Rcpp::XPtr<Object>(new Object()); }' ) new_object() dyn.unload(list.files(tempdir(), ".(so|dll)$",

We (the lme4 authors) are having a problem with doing a proper deep copy of a reference class object in recent versions of R-devel with the LAZY_DUPLICATE_OK flag in src/main/bind.c enabled. Apologies in advance for any improper terminology. TL;DR Is there an elegant way to force non-lazy/deep copying in our case? Is anyone else using reference classes with a field that is an external pointer?

You might not be doing anything wrong. Speex is stateful and can get into a bad state sometimes. It's happened to me too, but not recently. And I've seen such bugs reported on this list and fixed. I suggest several approaches to solving the problem: 1) Try compiling Speex without compiler optimizations and see if the problem still occurs. Most likely it will, but this is an

Dear R Devel, Since Linux moved away from using a file-system interface for audio, I think it is necessary to write special libraries to interface with audio hardware from various languages on Linux. In R, it seems like the appropriate datatype for a `snd_pcm_t` handle pointing to an open ALSA source or sink would be a "connection". Connection types are already defined in R for

I work with problems that have rather large data requirements -- typically a bunch of multigig arrays. Given how generous R is with using memory, the only way for me to work with R has been to use bigmatrices from bigmemory package. One thing that is missing a bit is interoperability of bigmatrices with C++ and possibly java. What i mean by that is API that would allow read and write filebacked

Thank you Simon for the detailed reply. That explains much more of what I was looking for from the R side. Dirk, I'm sorry if I seem hung up on anything here but I am trying to understand the details. My reply about XPtr or XPtr on arma/Eigen was to confirm my understanding was correct, which it appears it was. I was not aware the RVector/RMatrix objects don't connect to R as I am just

Hi, I have been using R for close to two years now and have grown quite comfortable with the language. I am presently trying to implement an optimization routine in R (Newton Rhapson). I have some R functions that calculate the gradient and hessian (pre requisite matrices) fairly efficiently. Now, I have to call this function iteratively until some convergance criterion is reached. I think the

Thanks for the replies. Regarding the answer by Dirk, I didn't feel like I still understood the reasoning why mclapply or foreach cannot handle XPtr objects. Instead of cluttering the SO question with comments I was getting the impression that this was a limitation inherited with R objects (which XPtr is supposed to be a proxy for an R object according to Dirk's comment). If this is not

Hi there, Although I'm a quite experienced R user and know my ways in C, I stumbled upon a problem I don't know how to solve. Therefore, I hope someone can provide me with the information or pointers I need in order to understand the way in which the communication between R and C occurs. I have the following C code which basicallly reflects what I want: typedef struct { float

My question is based on a project I have partially done, but there is still something I'm not clear. My goal is to create a R package contains GPU functions (some are from Nividia cuda library, some are my self-defined CUDA functions) My design is quite different from current R's GPU package, I want to create a R object (external pointer) point to GPU address, and run my GPU function

Has anyone tried building Samba 4.0 on AIX with XLC? I'm moving right along, but tripping up on some bugs in source3/utils/net_rpc.c, source3/utils/net_rpc_printer.c, and source3/utils/net_cache.c where there is an invalid use of the ":" operator. According to some other posts on the PostgreSQL forum, this shouldn't compile anywhere, even though GCC apparently allows it??

First, let me say that I think the speex code is incredible in the way it supports floating and fixed point code from one set of code. The same is true for supporting multiple processors, etc... I've used speex with the PC, TI 64xx and 55xx. Please view the following comments not as an attack on speex (which I think is incredible!) but as my contribution to an open source project. I know

Hello all, I’m looking into solving an AVR-specific issue and would love to hear peoples thoughts on how to best fix it. Background As you may or may not know, I maintain the in-tree AVR backend, which also happens to be (to the best of my knowledge) the first in-tree backend for a Harvard architecture. In this architecture, code lives inside the ‘program memory’ space (numbered 1), whereas data

R's dyn.unload() will unconditionally unload the given shared object; it does not check whether there is any object (external pointer or weak reference) with a C finalizer pointing into the space of the shared object being unloaded. So it is expected that R will segfault later when such finalizer is run. Currently there is no other way than to handle this on the side of the shared

===== Summary ===== Version 0.8.0 of the Rcpp package was released to CRAN today. This release marks another milestone in the ongoing redesign of the package, and underlying C++ library. ===== Overview ===== Rcpp is an R package and C++ library that facilitates integration of C++ code in R packages. The package features a set of C++ classes (Rcpp::IntegerVector, Rcpp::Function,

===== Summary ===== Version 0.8.0 of the Rcpp package was released to CRAN today. This release marks another milestone in the ongoing redesign of the package, and underlying C++ library. ===== Overview ===== Rcpp is an R package and C++ library that facilitates integration of C++ code in R packages. The package features a set of C++ classes (Rcpp::IntegerVector, Rcpp::Function,