similar to: Possibly useful idea

? Tue, 21 May 2024 08:00:11 +0000 Dario Strbenac via R-devel <r-devel at r-project.org> ?????: > Would a less resource-intensive value, such as 1, be a safer default > CPU value for confint? Which confint() method do you have in mind? There is at least four of them by default in R, and many additional classes could make use of stats:::confint.default by implementing vcov(). >

On 10/11/23 23:12, George Ostrouchov wrote: > I agree that the "R Installation and Administration" guide statement about FlexiBLAS needs an update. Standard R in CentOS Stream 9, which is now downstream from Fedora, gives the following result for Matrix products in sessionInfo(): > >> sessionInfo() > R version 4.3.1 (2023-06-16) > Platform: x86_64-redhat-linux-gnu

I agree that the "R Installation and Administration" guide statement about FlexiBLAS needs an update. Standard R in CentOS Stream 9, which is now downstream from Fedora, gives the following result for Matrix products in sessionInfo(): > sessionInfo() R version 4.3.1 (2023-06-16) Platform: x86_64-redhat-linux-gnu (64-bit) Running under: CentOS Stream 9 Matrix products: default

Hi, R has been built against FlexiBLAS in rawhide [1, 2]. These are the R packages that need to be rebuilt: R-ape-0:5.4-2.fc33.x86_64 R-expm-0:0.999.4-7.fc33.x86_64 R-gee-0:4.13.20-4.fc33.x86_64 R-gss-0:2.2.2-3.fc33.x86_64 R-igraph-0:1.2.5-3.fc33.x86_64 R-msm-0:1.6.8-5.fc33.x86_64 R-preprocessCore-0:1.50.0-4.fc33.x86_64 R-qtl-0:1.46.2-4.fc33.x86_64 R-quadprog-0:1.5.8-5.fc33.x86_64 Could

Seems like this in 83986 [1] needs a fix in Lapack.c: if (dladdr((void *) F77_NAME(ilaver), &dl_info)) { char buf[PATH_MAX+1]; char *res = realpath(dl_info.dli_fname, buf); if (res) { SEXP nfo = R_NilValue; if (strstr(res, "flexiblas")) nfo = R_flexiblas_info(); if

Hi Ivan, An apology, I was away for quite a bit. To reproduce the setup: I have been using the default GCC in RHEL 9.1. gcc -v Using built-in specs. COLLECT_GCC=gcc COLLECT_LTO_WRAPPER=/usr/libexec/gcc/x86_64-redhat-linux/11/lto-wrapper OFFLOAD_TARGET_NAMES=nvptx-none OFFLOAD_TARGET_DEFAULT=1 Target: x86_64-redhat-linux Configured with: ../configure --enable-bootstrap --enable-host-pie

Hello, Would a less resource-intensive value, such as 1, be a safer default CPU value for confint? I noticed excessive CPU usage on a I.T. administrator-managed server which was being three-quarters used by another staff member when the confidence interval calculation in an R Markdown document suddenly changed from two seconds to ninety seconds because of competition for CPUs between users. Also,

I also have this questions for this. I wonder if R initiates a system environment or options to instruct the packages on the number of cores to use? It doesn't have to be mandatory for now, but at least package maintainers can have shared consensus and start to adopt this humble settings rather than abusing parallel::detectCores() to max out the number of threads by default. > On Aug 7,

Hi all, I have the issue: icc -std=c99 -std=gnu11 -I../../src/extra -I../../src/extra/xdr -I. -I../../src/include -I../../src/include -I/usr/local/include -I../../src/nmath -DHAVE_CONFIG_H -fopenmp -fpic -g -O3 -wd188 -ip -mp -c eval.c -o eval.o arithmetic.c(66): warning #274: declaration is not visible outside of function int matherr(struct exception *exc) ^

Following up on this -- on my system, I have 69 packages installed that appear to provide something like a confint() method: h <- help.search("confint", agrep = FALSE) p <- sort(unique(h$matches$Package)) length(p) ## [1] 69 p [1] "bamlss" "bbmle" "binom" "brglm2" [5] "broom"

Note that 'intel 2022' is a bit vague. The current version is 2023.1.0, and that has both the 'classic' (icc/icpc/ifort which it seems you used) and new (icx/ixpx/ifx) compilers -- the former are said to be going to be discontinued later this year. R did not know about ifx so did not build with the new set. The parts of the manual Tomas referred to were about the old

Dear Miguel Esteva, I couldn't get a Red Hat "ubi9" container to install enough dependencies to build R. Is there a way to reproduce your setup on a virtual machine somewhere? On Fri, 3 May 2024 00:42:43 +0000 Miguel Esteva via R-help <r-help at r-project.org> wrote: > *** caught segfault *** > > address 0x1801fa8f70, cause 'memory not mapped' > >

Hi R-devel list, OpenBLAS is readily available for unix-likes: https://cloud.r-project.org/web/packages/gcbd/vignettes/gcbd.pdf However, my questions are: 1) Would R-devel consider using OpenBLAS for the main distribution of R for all platforms including Windows? 2) If so, would R-devel set the default multi-thread level to the number of (real) cores on a machine? My sense is there're a

On Mon, Aug 24, 2015 at 1:42 PM, Dirk Eddelbuettel <edd at debian.org> wrote: > > On 24 August 2015 at 11:43, arnaud gaboury wrote: > | On Mon, Aug 24, 2015 at 11:29 AM, Bj?rn-Helge Mevik > | <b.h.mevik at usit.uio.no> wrote: > | > arnaud gaboury <arnaud.gaboury at gmail.com> writes: > | > > | >> - Intel MKL: this is part of Intel Parallel Studio

On point 1): The standard approach seems to favor the reference BLAS for reasons other than speed. For example, vecLib, Apple's multi-threaded BLAS library, is not the default choice for macOS binaries due to concerns about 'precision'. See: https://cloud.r-project.org/bin/macosx/RMacOSX-FAQ.html#Whic h-BLAS-is-used-and-how-can-it-be-changed_003f This doesn't appear to be Mac-

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 First of all, I'm a physicist and therefore I'm not much used to use statistics. So, please forgive me if this is a FAQ or stupid, but I failed to find the answer by myself. I want to use corr.test to test for the correlation of two data sets (actually I have a lot of data set and perform pairwise testing). But I wanted to find sets where the

----- Original Message ---- > From aaronngray.lists at googlemail.com Mon Jul 27 15:14:40 2009 > From: aaronngray.lists at googlemail.com (Aaron Gray) > Date: Mon, 27 Jul 2009 21:14:40 +0100 > Subject: [LLVMdev] llc - generation of native machine code > > > On Mon, Jul 27, 2009 at 8:25 AM, Rudskyy<tema13tema at yahoo.de> wrote: > > > But now I am looking for

From the R Installation and Admin manual: "There is a tendency for re-distributors of R to use ?enhanced? linear algebra libraries without explaining their downsides.? There?s a downside not mentioned in the manual that caught and baffled me for a while. I was using all 64 cores of an AWS instance via parallel::mclapply() and doing matrix multiplications in the parallelized function. If

On 29 October 2017 at 22:01, Kenny Bell wrote: | User here: incorporating Intel's MKL, as MRO does, would be a very welcome | addition. | | I was an MRO user before and it improved my experience with medium data | immensely. | | They did, however, leave behind bugs here and there, especially related to | development with Rcpp, so I switched back to vanilla R. With all due respect: You may

I think the thing that is missing is a simple way for end users on windows to replace blas/lapack libraries with MKL-a package that you install that puts the libraries in the right place. Microsoft provides something for their distro, but we don't have the equivalent if you get R from cran. On 29 October 2017 at 22:01, Kenny Bell wrote: | User here: incorporating Intel's MKL, as MRO