similar to: When calling external C-function repeatedly I get different results; can't figure out why..

Not an expert in programming either, but to me it seems like you've forgotten to initialize the variable "tr". It just picks up garbage from allocated memory previously initialized by other processes. Med venlig hilsen Frede Aakmann T?gersen > -----Oprindelig meddelelse----- > Fra: r-help-bounces at stat.math.ethz.ch > [mailto:r-help-bounces at stat.math.ethz.ch] P?

I have ported some R code to C to make it faster. I can perform .Call("foobar",....) once and it works fine. Absolutely correct answer. If I put a loop inside foobar and run the main code routine more than 100 times, it crashes R. Or if I call .Call("foobar"....) seperately more than two tims it crashes R. For the most part I am doing matirx multiplies using EXP

Hi, I was wondering if I could use the matprod function from array.c in my own C routine. I tried the following as a test /* my_matprod.c */ # include <Rinternals.h> /* for REAL, SEXP etc */ # include <R_ext/Applic.h> /* array.c says need for dgemm */ /* following copied from array.c */ static void matprod(double *x, int nrx, int ncx, double *y, int nry, int ncy, double *z)

I've looked at the code for matrix multiplies in R, and found that it can speeded up quite a bit, for multiplies that are really vector dot products, and for other multiplies in which the result matrix is small. Here's my test program: u <- seq(0,1,length=1000) v <- seq(0,2,length=1000) A2 <- matrix(2.1,2,1000) A5 <- matrix(2.1,5,1000) B3 <- matrix(3.2,1000,3) A4 <-

Hi, I'm just following your messages the overhead that the code for dealing with possible NA/NaN values brings. When I was setting up part of the matrixStats package, I've also though about this. I was thinking of having an additional logical argument 'hasNA'/'has.na' where you as a user can specify whether there is NA/NaN:s or not, allowing the code to avoid it or not.

With this patch, > A <- matrix(1, 2, 2) > B <- matrix(2, 3, 2) > A %*% B Error in A %*% B : non-conformable arguments of dimension (2, 2) and (3, 2) >From 205b591d4d14b5ff667325fb233a6deb08314726 Mon Sep 17 00:00:00 2001 From: Joshua Nathaniel Pritikin <jpritikin at pobox.com> Date: Fri, 5 Apr 2019 12:03:58 -0400 Subject: [PATCH] Improve non-conformable arguments error

I think this is a good idea. Is there a reason why it got no interest? Slippery slope? Or maybe others were also just occupied trying to figure out how Joshua's second message had timestamp earlier than his first message? On Fri, Apr 05, 2019 at 12:05:36PM -0400, Joshua N Pritikin wrote: >With this patch, > >> A <- matrix(1, 2, 2) >> B <- matrix(2, 3, 2) >> A

>>>>> Cohn, Robert S <robert.s.cohn at intel.com> >>>>> on Sat, 7 Jan 2017 16:41:42 +0000 writes: > I am using R to multiply some large (30k x 30k double) > matrices on a 64 core machine (xeon phi). I added some timers > to src/main/array.c to see where the time is going. All of the > time is being spent in the matprod function, most of that

I am using R to multiply some large (30k x 30k double) matrices on a 64 core machine (xeon phi). I added some timers to src/main/array.c to see where the time is going. All of the time is being spent in the matprod function, most of that time is spent in dgemm. 15 seconds is in matprod in some code that is checking if there are NaNs. > system.time (C <- B %*% A) nancheck: wall time

Hi Robert, thanks for the report and your suggestions how to make the NaN checks faster. Based on my experiments it seems that the "break" in the loop actually can have positive impact on performance even in the common case when we don't have NaNs. With gcc on linux (corei7), where isnan is inlined, the "break" version uses a conditional jump while the

> Do you have R code (including set.seed(.) if relevant) to show on how to generate > the large square matrices you've mentioned in the beginning? So we get to some > reproducible benchmarks? Hi Martin, Here is the program I used. I only generate 2 random numbers and reuse them to make the benchmark run faster. Let me know if there is something I can do to help--alternate

Hi, in R-3.0 I get the following error when calling lsfit with more observations than variables, which seems to come from an error in the formatting of the error message (note that this was not happening in 2.15.3): > nobs <- 5; nvar <- 6; lsfit(matrix(runif(nobs*nvar), ncol=nvar), runif(nobs), intercept=FALSE) Error in sprintf(ngettext(nry, "%d response", "%d

Hi Tomas, Can you share the full code for your benchmark, compiler options, and performance results so that I can try to reproduce them? There are a lot of variables that can affect the results. Private email is fine if it is too much for the mailing list. I am measuring on Knight's Landing (KNL) that was released in November. KNL is not a co-processor so no offload is necessary. R executes

Hi guys, interestingly, my problem seems to be solved by writing a FORTRAN wrapper for the Fortran code! (As long as the check doesn't get smarter...). This is the relevant part of my Fortran code: ----------------------------------------------------------- subroutine gmlfun(what, & totevent, totrs, ns, & antrs, antevents, size, & totsize,

>>>>> Jan van der Laan <rhelp at eoos.dds.nl> >>>>> on Fri, 6 Oct 2017 12:13:39 +0200 writes: > It is actually model.matrix that crashes, not glm. Same > crash occurs with e.g. lm. > model.matrix(dob_mon ~ dob_day*dob_mon, data = tab) > also crashes R. Yes, segmentation fault. It only happens when these are *logical*

I would like to see how the matrix multiplication operator %*% is implemented (because I want to see which external Fortran/C routines are used). How can I do so? Best S??ren

Hi all, I have a C function, say Cfun, that calls Lapack's DGEMM routine and I need to create a shared library to use Cfun inside R. The C file is the following #include<stdio.h> #include<R.h> #include<R_ext/Lapack.h> void Cfun(double *res, double *X, int *n, int *q) { char *ptr_TRANSA, TRANSA='T', *ptr_TRANSB, TRANSB='N'; ptr_TRANSA=&TRANSA;

Hi, This is Kotien Wu from NIH/NCI. We want to use R function for our web: http://cgap.nci.nih.gov It works for functions in R/R-1.9.1/src/nmath/standalone very well. We have function GetPvalueForT.c which has #define MATHLIB_STANDALONE 1 #include <Rmath.h> double GetPvalueForT ( double t, double deg ) { return 2 * pt(t, deg, 0, 0); } We create GetPvalueForT.i, which has /* File :

Hi, I am working on a UNIX machine and I am interfacing R and C with the .C function. I am trying to call LAPACK and BLAS routines, but am running into a problem where, while I am able to run the BLAS routines, I cannot run the LAPACK routines. I compile my .c file (at end of email) in the following way: [mhitczen at jlogin2 ~/Cstuff]$ R CMD SHLIB testmore.c gcc -std=gnu99

Hello, I am trying to profile a function of OpenMx (http://openmx.psyc.virginia.edu) for CPU time. My operating system is OS X 10.10. OpenMx contains C++ and Fortran code. I have read the section regarding profiling compiled code in the manual (https://cran.r-project.org/doc/manuals/r-release/R-exts.html#Profiling-compiled-code). This section and this post (http://blog.fellstat.com/?p=337)