[R] R & RStudio hardware Utilization

[Jeff Newmiller]

The actual question posed was whether R behaves differently than RStudio at parallel computation, which is like asking whether apple pies grow better than apple trees.

The answer is that RStudio doesn't do any computation... it is a programming environment that hands off all computation to a separately-installed copy of the R software. Read the messages in the console right after you start RStudio instead of ignoring them. 
-- 
Sent from my phone. Please excuse my brevity.

On August 20, 2017 10:43:52 AM PDT, Bert Gunter <bgunter.4567 at gmail.com> wrote:
>Inline.
>Bert Gunter
>
>"The trouble with having an open mind is that people keep coming along
>and sticking things into it."
>-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
>
>
>On Sun, Aug 20, 2017 at 7:39 AM, Vasilis Bardakos via R-help
><r-help at r-project.org> wrote:
>> I am going to attend MSc Data Science in September, so I consider
>upgrading my system to be more efficient with my projects.I used
>RStudio for my Macroeconomics Undergraduate Thesis and I had a couple
>of loops which needed almost 30 minutes to occur.
>> My system specifications are the following:
>>
>>    - CPU: i7 4970k @ 4.0 GHz
>>    - RAM: 8GB DDR3
>>    - Hard Drive: SSD M.2 950 PRO
>>
>> Since I have only used RStudio, is there any dramatic difference
>between R and RStudio in terms of system resources used?
>> Does R utilizes all Cores? If it does, is it better to go for more
>cores or faster CPU?I know that RAM has a great impact. However, I
>don't really know how much do I really need for individual projects.
>Invest to 32GB or just go for fast 16GB?At the moment, my SSD seems
>fine in terms of speed.
>> Sorry for the trouble but there is not any clear answer in the
>internet.
>
>Nonsense!! Searching on "Does R use multiple cores on a multicore CPU"
>immediately brought this up:
>
>https://stackoverflow.com/questions/4775098/r-package-that-automatically-uses-several-cores
>
>This appears to answer all your questions! Note in particular the
>pointers to CRAN's "High Performance Computing" task view, which
>should provide up to date answers and packages.
>
>Cheers,
>Bert
>
>
>
>
>> Thank you in advance,William
>>
>>         [[alternative HTML version deleted]]
>>
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>> and provide commented, minimal, self-contained, reproducible code.
>
>______________________________________________
>R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
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>and provide commented, minimal, self-contained, reproducible code.

-- 
Sent from my phone. Please excuse my brevity.