if I understand correctly, R makes a copy of the full environment for each process. thus, even if I have 32 processors, if I only have 64GB of RAM and my R process holds about 10GB, I should probably not spawn 32 processes. has anyone written a function that sets the number of cores for use (in mclapply) to be guessed at by appropriate memory requirements (e.g., "amount-of-RAM"/"RAM held by R")? (it would be even nicer if I could declare my 8GB data frame to be read-only and to be shared among my processes, but this is presumably technically very difficult.) pointers appreciated. /iaw
parallel number of cores according to memory?
5 messages · Jeff Newmiller, ivo welch
Use an operating system that supports forking, like Linux or MacOSX, and use the parallel package mclapply function or similar to share memory for read operations. [1] And stop posting in HTML here. [1] https://cran.r-project.org/web/views/HighPerformanceComputing.html
On July 7, 2020 9:20:39 PM PDT, ivo welch <ivowel at gmail.com> wrote:
if I understand correctly, R makes a copy of the full environment for each process. thus, even if I have 32 processors, if I only have 64GB of RAM and my R process holds about 10GB, I should probably not spawn 32 processes. has anyone written a function that sets the number of cores for use (in mclapply) to be guessed at by appropriate memory requirements (e.g., "amount-of-RAM"/"RAM held by R")? (it would be even nicer if I could declare my 8GB data frame to be read-only and to be shared among my processes, but this is presumably technically very difficult.) pointers appreciated. /iaw [[alternative HTML version deleted]]
______________________________________________ R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Sent from my phone. Please excuse my brevity.
ugghhh---apologies. although in 2020, it would be nice if the mailing list had an automatic html filter (or even bouncer!) I am using macos. alas, my experiments suggest that `mclapply()` on a 32-core intel system with 64GB of RAM, where the input data frame is 8GB and the output is about 500MB per core (to be stitched together into about 16GB), the system starts swapping like crazy, comes to a halt, and then usually crashes. /iaw
The list does strip html, but the quality of what remains varies greatly. Are you using tidyverse functions in your workers? Sounds to me like you are doing something in the workers that is triggering making copies of the input data frame.
On July 7, 2020 10:15:15 PM PDT, ivo welch <ivowel at gmail.com> wrote:
ugghhh---apologies. although in 2020, it would be nice if the mailing list had an automatic html filter (or even bouncer!) I am using macos. alas, my experiments suggest that `mclapply()` on a 32-core intel system with 64GB of RAM, where the input data frame is 8GB and the output is about 500MB per core (to be stitched together into about 16GB), the system starts swapping like crazy, comes to a halt, and then usually crashes. /iaw
Sent from my phone. Please excuse my brevity.
no, I'm not. mostly conventional use afaik. if this should not be happening, I can trace it down to a small reproducible example to figure it out. -- Ivo Welch (ivo.welch at ucla.edu) -- Ivo Welch (ivo.welch at ucla.edu) http://www.ivo-welch.info/ J. Fred Weston Distinguished Professor of Finance, UCLA Anderson
On Tue, Jul 7, 2020 at 10:24 PM Jeff Newmiller <jdnewmil at dcn.davis.ca.us> wrote:
The list does strip html, but the quality of what remains varies greatly. Are you using tidyverse functions in your workers? Sounds to me like you are doing something in the workers that is triggering making copies of the input data frame. On July 7, 2020 10:15:15 PM PDT, ivo welch <ivowel at gmail.com> wrote:
ugghhh---apologies. although in 2020, it would be nice if the mailing list had an automatic html filter (or even bouncer!) I am using macos. alas, my experiments suggest that `mclapply()` on a 32-core intel system with 64GB of RAM, where the input data frame is 8GB and the output is about 500MB per core (to be stitched together into about 16GB), the system starts swapping like crazy, comes to a halt, and then usually crashes. /iaw
-- Sent from my phone. Please excuse my brevity.