similar to: Problem using F77_CALL(dgemm) in a package

Hi I am new to writing C code and am trying to write an R extension in C. I have hit a wall with F77_CALL(dgemm) in that it produces wrong results. The code below is a simplified example that multiplies the matrices Ab and Bm to give Cm. The results below show clearly that Cm is wrong. Am= 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Bm= 1 1 1 1 1

Hi, I'm trying to follow the R-admin instructions for using MKL10 as the external BLAS compiling R-2.6.2 under Linux on a RH EL head node of a cluster. The configure process seems to have problems when it checks for dgemm in the BLAS. I'm using configure as: ./configure CC=icc F77=ifort --with-lapack="$MKL" --with-blas="$MKL" where $MKL is defined as in R-admin

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)

Hi, I've got a problem building a contrast matrix for the Dunnet contrast in package multcopm. The following works fine: > summary(simtest(adiff ~ trial)) Simultaneous tests: Dunnett contrasts Data: adiff by trial Contrast matrix: trial1 trial2 trial3 trial4 trial5 trial2-trial1 -1 1 0 0 0 trial3-trial1 -1 0 1 0 0

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

Hi, I am trying to compile a single module (dgemm.c) using clang and generate dgemm.ll. Command: clang -emit-llvm dgemm.c -S -o dgemm.ll Some of the functions are declared as static and clang ignores these functions: One of the functions is: static void innerloop(double a, const double* b, double* c, double beta) { *b = a*beta; return; } Is there any way to make clang generate llvm code

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 Arvind, you need to use it effectively : static int add(int a, int b) { return a+b; } int use() { return add(4,5); } ==> ; ModuleID = '<stdin>' target datalayout = "e-p:32:32:32-i1:8:8-i8:8:8-i16:16:16-i32:32:32-i64:32:64-f32:32:32-f64:32:64-v64:64:64-v128:128:128-a0:0:64-f80:32:32" target triple = "i386-pc-linux-gnu" define i32 @use()

Hi, Sorry for not being specific. I just wanted to know if there is any way at all to force clang to generate intermediate code for static functions when they are not being called anywhere inside the current module. Other compilers seem to generate intermediate code (lcc, for instance). Thanks for your reply..Olivier. Sincerely Arvind On Mon, Dec 14, 2009 at 1:10 PM, Olivier Meurant

Hello, I am using R 1.7.1 on a Redhat Linux machine, version 7.3. The following works fine: setClass("ok", representation( "A" = "matrix", "Cmatrix" = "matrix")) new("ok", "A" = diag(4), "Cmatrix" = diag(4)) But the following doesn't work: setClass("notok", representation(

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;

Ah ok. Sorry. :) I think that argument "-femit-all-decls" will help you. Olivier. On Mon, Dec 14, 2009 at 9:18 PM, Arvind Sudarsanam < arvind.sudarsanam at aggiemail.usu.edu> wrote: > Hi, > > Sorry for not being specific. I just wanted to know if there is any > way at all to force clang to generate intermediate code for static > functions when they are not being

If I configure in R-patched and R-devel, with the same options to configure, then R-patched says checking for ATL_xerbla in -latlas... yes checking for cblas_dgemm in -lcblas... yes checking for dgemm_ in -lf77blas... yes which R-devel says checking for ATL_xerbla in -latlas... yes checking for cblas_dgemm in -lcblas... yes checking for dgemm in -lf77blas... no This is on the same computer and

> 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

Dear R-help list, I would like to perform multiple comparisons for lme. Can you report to me if my way to is correct or not? Please, note that I am not nor a statistician nor a mathematician, so, some understandings are sometimes quite hard for me. According to the previous helps on the topic in R-help list May 2003 (please, see Torsten Hothorn advices) and books such as Venables &

Dear r-helpers, I have a question about multiple testing. Here an example that puzzles me: All matrixes and contrast vectors are presented in treatment contrasts. 1. example: library(multcomp) n<-60; sigma<-20 # n = sample size per group # sigma standard deviation of the residuals cov1 <- matrix(c(3/4,-1/2,-1/2,-1/2,1,0,-1/2,0,1), nrow = 3, ncol=3, byrow=TRUE, dimnames =

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

Dear list, As a reply to my recent mail: > simint and TukeyHSD work for aov objects. > Can someone point me to similar functions for lme objects? Douglas Bates wrote There aren't multiple comparison methods for lme objects because it is not clear how to do multiple comparisons for these. I don't think the theory of multiple comparisons extends easily to lme models. One could

I have run the following logistic regression model: options(contrasts=c("contr.treatment", "contr.poly")) m <- glm(wolf.cross ~ null.cross + feature, family = "binomial") where: wolf.cross = likelihood of wolves crossing a linear feature null.cross = proportion of random paths that crossed a linear feature feature = CATEGORY of linear feature with 5 levels:

I give up. Maybe it is my search (Windows) but I cannot seem to find the definition of the F77_CALL or F77_NAME macros. Either there are too many matches or the search just doesn't find it. For example where is the source for: F77_CALL(dpotri) ? Thank you. Kevin