[R] parallel number of cores according to memory?

Jeff Newmiller jdnewm|| @end|ng |rom dcn@d@v|@@c@@u@
Wed Jul 8 06:40:50 CEST 2020


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 using 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]]
>
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-- 
Sent from my phone. Please excuse my brevity.



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