similar to: Process to Incorporate Functions from {parallely} into base R's {parallel} package

FWIW, there are indeed a few low hanging bug fixes in 'parallelly' that should be easy to incorporate into 'parallel' without adding extra maintenance. For example, in parallel::makePSOCKcluster(), it is not possible to disable SSH option '-l USER' so that it can be set in ~/.ssh/config. The remote user name will be the user name of your local machine and if you try to

If these are easy changes, maybe someone will incorporate them. You'll make the argument stronger for doing that if you can explain why it's better to do that than to keep them in parallely. Duncan Murdoch On 07/11/2020 1:39 p.m., Henrik Bengtsson wrote: > FWIW, there are indeed a few low hanging bug fixes in 'parallelly' > that should be easy to incorporate into

On 06/11/2020 4:47 p.m., Balamuta, James Joseph wrote: > Hi all, > > Henrik Bengtsson has done some fantastic work with {future} and, more importantly, greatly improved constructing and deconstructing a parallelized environment within R. It was with great joy that I saw Henrik slowly split off some functionality of {future} into {parallelly} package. Reading over the package?s README, he

Hi all, I am using R-3.0.1 under Linux platform to embed R into my C++ code. I am facing an error while executing more than 1 R-expressions parallelly. I am executing round(X) and abs(X) parallelly on a set of 50 input rows which resulted in segmentation fault after getting the following errors. Error: unprotect_ptr: pointer not found Error: argument to 'findVar' is not an environment

Hey everyone, Thanks for all the input. It's happening again. This time for the packages "DBI", "parallelly", "segmented", "survival", "V8". So, RStudio shows updates for those and updating them via RStudio leads to this output: ``` > install.packages(c("DBI", "parallelly", "segmented", "survival",

I am looking for ways to add points to three different plots in parallel. I generate three scatter plots and name them as s3d1, s3d2 and s3d3 s3d1<-scatterplot3d(mtcars[,3],mtcars[,4],mtcars[,5],main="common",pch=20) s3d2<-scatterplot3d(mtcars[,3],mtcars[,4],mtcars[,5],main="common",pch=20)

Hi R-developers In the package Parallel, the function parLapply(cl, x, f) seems to allow transmission of only one parameter (x) to the function f. Hence in order to compute f(x, y) parallelly, I had to define f(x, y) as f(x) and tried to access y within the function, whereas y was defined outside of f(x). Script: library(parallel) f <- function(x) { z <- 2 * x + .GlobalEnv$y # Try to

Dear XAPIAN developers, I was using xapian to index large than 13 million document about Q & A(Quora similarly). I will share some performance data about indexing and searching, and I will seek some help for improving performance of searching. My computer has 8 i7 at 3.4G CPU and 16G memory, ubuntu 16.04. Dataset include about 13M document, each document will be cut into 35 term(Chinese

Hi, I am a newbie to R and trying to implement parallelism in R. I am currently using R-2.3.1, and Cygwin to run R on Windows xp. ssh and all are working fine, When I try to create a socket connection as makeSOCKcluster(c("localhost","localhost")), it just waits for the other prcess on localhost to get created and respond. But this other process is

Hi all, I recently found out that R does not utilize fully the Duo Core capability when you only run one instance of R. I did some number crunching today and it seems that if I only open 1 R console, it uses 50% of my CPU (either 50-50 or 100-0 on 2 cores). Then, I open the second instance and divide the work into two parts, and run them parallelly, they seems to utilize 100% of my CPU. So, my

Hi, I am attempting to implement a mixed (windows/linux) snow sockets parallelism in R, but am running into difficulties similar to a post made Aug 31, 2006 under the same subject heading. I feel like I may be one or two non-obvious steps away from getting it all working, but I'm stuck. If anyone can shed some light on this (I believe Prof. Tierney stated that he has successfully run a

On 27 January 2017 at 21:54, G?bor Cs?rdi wrote: | On Fri, Jan 27, 2017 at 9:28 PM, Da Zheng <zhengda1936 at gmail.com> wrote: | > What major R platforms does this policy refer to? | > | | Linux, macOS, Windows. | | | > Currently, my package runs in Ubuntu. If it works on both Ubuntu and | > Redhat, does it count as two platforms? | > | | I think that Linux is just one. Is

G'day Philipp, On Fri, 16 Feb 2024 17:33:13 +0100 Philipp Schneider <philipp-schneider at gmx.net> wrote: > Thanks for all the input. It's happening again. This time for the > packages "DBI", "parallelly", "segmented", "survival", "V8". So, > RStudio shows updates for those and updating them via RStudio leads > to this

Hi, Sorry for the hiatus, busy time at my university. :) After a false start and some (hopefully cogent) thought, I am now of the opinion that it will be better to have llvm natively support a somewhat different notion of parallel computation and have the frontend lower OpenMP directives (and possibly other such things) into the same. In short, I propose a intrinsic based approach which hinges

SUMMARY: I'm proposing that R assert that 'connection' options have not changed since first created such that R will produce the following error: > fh <- file("a.txt", open = "w+") > cat("hello\n", file = fh) > close(fh) > fh2 <- file("b.txt", open = "w+") > cat("world\n", file = fh2) >

Dear all, In my package I have a computational expensive Rnw file which can't pass R CMD check. Therefore I set eval=FALSE in the Rnw file. But I would like to have the pdf vignette generated by the Rnw file with eval=TRUE. It seems to me a static pdf vignette is an option. Any suggestions on this? Thanks, Zhu Wang **Connecticut Children's Confidentiality Notice** This e-mail

All, At first glance, a recent commit to R-devel ( https://github.com/wch/r-source/commit/2c182014ecc8c2407a89092c9162d86046bd18da) appears to be related to long vector support. But as Henrik Bengtsson points out at https://github.com/HenrikBengtsson/Wishlist-for-R/issues/97#issuecomment-562659134, writeBin() still prohibits long vectors. Are there any plans to add long vector support to R

AFAIK there is no hashing utility in base R which can create hash digests of arbitrary R objects. However, as also described by Henrik Bengtsson in [1], we have tools::md5sum() which calculates MD5 hashes of files. Calculating hashes of in-memory objects is a very common task in several areas, as demonstrated by the popularity of the 'digest' package (~850.000 downloads/month). Upon

On Thu, May 3, 2018 at 2:42 PM, Henrik Bengtsson <henrik.bengtsson at gmail.com> wrote: > Use mode="wb" when you download the file. See > https://github.com/HenrikBengtsson/Wishlist-for-R/issues/30. > > R core, and others, is there a good argument for why we are not making this > the default download mode? It seems like a such a simple fix to such a > common

Dear Luke and others, I have many R versions on my machine and want to start a particular one when snow builds its cluster. (The same version I start snow from.) It seems that everything is set up correctly in defaultClusterOptions: > mget(ls(defaultClusterOptions), defaultClusterOptions) $homogeneous [1] TRUE $manual [1] FALSE $master nodename "maya.unil.ch" $outfile [1]