[R] Problem parallelizing across cores

Jeff Newmiller jdnewm|| @end|ng |rom dcn@d@v|@@c@@u@
Thu Aug 29 02:10:21 CEST 2019

Your first option is always to serially compute results. When the computation time is long compared to session overhead and data I/O, you can consider parallel computing. You should first consider laying out your independent computation work units as a sequence, and then allocate segments of that sequence to your workers, each of which will perform their respective sub-sequences serially so as to minimize the overhead penalty... so yes, you absolutely can use a method that starts new instances of R ("SNOW"). You also have forking on Linux which has lower overhead, but not zero so the exact same logic can be applied. But if you arbitrarily shorten your serial computations too much then you cannot optimize your use of available processing resources as you have already observed.

However, your lack of reproducible example is a strong indicator that you are not really asking a question about R... so do some reading and focus your next question on R or the base R parallel package per the Posting Guide. (Do read that... posting HTML is a good way
for your message to get scrambled before we see it.) Wide-ranging discussions on computer science and HPC hardware constraints are outside the topic here.

On August 28, 2019 11:06:57 AM PDT, James Spottiswoode <james.spottiswoode using gmail.com> wrote:
>Hi All,
>I have a piece of well optimized R code for doing text analysis running
>under Linux on an AWS instance.  The code first loads a number of
>and some needed data and the actual analysis is done by a function
>say, f(string).  I would like to parallelize calling this function
>the 8 cores of the instance to increase throughput.  I have looked at
>packages doParallel and future but am not clear how to do this.  Any
>that brings up an R instance when the function is called will not work
>me as the time to load the packages and data is comparable to the
>time of the function leading to no speed up.  Therefore I need to keep
>number of instances of the R code running continuously so that the data
>loading only occurs once when the R processes are first started and
>thereafter the function f(string) is ready to run in each instance.  I
>I have put this clearly.
>I’d much appreciate any suggestions.  Thanks in advance,
>James Spottiswoode
>	[[alternative HTML version deleted]]
>R-help using r-project.org mailing list -- To UNSUBSCRIBE and more, see
>PLEASE do read the posting guide
>and provide commented, minimal, self-contained, reproducible code.

Sent from my phone. Please excuse my brevity.

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