search for: 5e3

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2016 Aug 01
2
R, OpenBLAS and OMP_NUM_THREEADS
...e thread per available CPU, which isn't ideal for machines more than a couple of CPUs. Setting the environment (OMP_NUM_THREADS or OPENBLAS_NUM_THREADS) in the shell works: $ OMP_NUM_THREADS=1 R > Sys.getenv("OMP_NUM_THREADS") [1] "1" > system.time({x <- replicate(5e3, rnorm(5e3)); tcrossprod(x) }) [runs in one thread] but adding it to /etc/R/Renviron.site doesn't: $ R > Sys.getenv("OMP_NUM_THREADS") [1] "1" > system.time({x <- replicate(5e3, rnorm(5e3)); tcrossprod(x) }) [runs multi-threaded] (nor does setting the variable at...
2012 Jun 07
2
How to build a large identity matrix faster?
Hello, I am trying to build a large size identity matrix using diag(). The size is around 23000 and I've tried diag(23000), that took a long time. Since I have to use this operation several times in my program, the running time is too long to be tolerable. Are there any alternative for diag(N)? Thanks Cheers, yct [[alternative HTML version deleted]]
2016 Aug 02
0
R, OpenBLAS and OMP_NUM_THREEADS
...n't ideal for machines more than a couple of CPUs. > > Setting the environment (OMP_NUM_THREADS or OPENBLAS_NUM_THREADS) in the > shell works: > > $ OMP_NUM_THREADS=1 R >> Sys.getenv("OMP_NUM_THREADS") > [1] "1" >> system.time({x <- replicate(5e3, rnorm(5e3)); tcrossprod(x) }) > [runs in one thread] > > but adding it to /etc/R/Renviron.site doesn't: > > $ R >> Sys.getenv("OMP_NUM_THREADS") > [1] "1" >> system.time({x <- replicate(5e3, rnorm(5e3)); tcrossprod(x) }) > [runs multi-thr...
2016 Aug 03
2
R, OpenBLAS and OMP_NUM_THREADS
...than a couple of CPUs. >> >> Setting the environment (OMP_NUM_THREADS or OPENBLAS_NUM_THREADS) in the >> shell works: >> >> $ OMP_NUM_THREADS=1 R >>> Sys.getenv("OMP_NUM_THREADS") >> [1] "1" >>> system.time({x <- replicate(5e3, rnorm(5e3)); tcrossprod(x) }) >> [runs in one thread] >> >> but adding it to /etc/R/Renviron.site doesn't: >> >> $ R >>> Sys.getenv("OMP_NUM_THREADS") >> [1] "1" >>> system.time({x <- replicate(5e3, rnorm(5e3)); tcros...
2010 Aug 25
1
Trying to configure R to use acml_mp
Hi, I'm following up to a post I made to r-help here: http://r.789695.n4.nabble.com/Trouble-configuring-R-to-use-ACML-tt2337193.html#a2337193 I have verified that LD_LIBRARY_PATH is set... I set it in /etc/bash.bashrc (is that ok?) and it shows up when I echo $LD_LIBRARY_PATH I also tried adding the paths to the ld.so cache as Prof Ripley had suggested. I get the same results when running
2010 Feb 25
1
locfit: max number of predictors?
Hi All, In another thread Andy Liaw, who CRAN lists as locfit maintainer; said: <quote> From: "Liaw, Andy" <andy_liaw at merck.com> To: "Guy Green" <guygreen at netvigator.com>; <r-help at r-project.org> Subject: Re: Alternatives to linear regression with multiple variables Date: 22 February 2010 17:50 You can try the locfit package, which I believe
2009 Apr 01
0
回复: R-help Digest, Vol 73, Issue 32
...a serious > consideration) Wacek's apply method looks to be about 1.4 times > *faster* than > the do.call/pmax method. hmm, since i was called by name (i'm grateful, rolf), i feel obliged to check the matters myself:     # dummy data, presumably a 'large matrix'?     n = 5e3     m = matrix(rnorm(n^2), n, n)     # what is to be benchmarked...     waku = expression(matrix(apply(m, 1, max), nrow(m)))     bert = expression(do.call(pmax,data.frame(m)))     # to be benchmarked     library(rbenchmark)     benchmark(replications=10, order='elapsed', columns=c('te...