Re: [R] parallel processing in r...
Hi,
On ' how to use "top" inside the R prompt? '
you can use system('top') command.
Thanks,
On Sun, Jul 1, 2018 at 9:53 PM Benoit Vaillant
wrote:
> Hello,
>
> On Sun, Jul 01, 2018 at 11:31:29AM +, akshay kulkarni wrote:
> > I tried "top" at the bash prompt, but it provides a way to measure
> > CPU performance of the existing processes. I want to check the CPU
> > usage of the execution of an R function.
>
> Try to open two bash prompts, in one use R and in the other use top to
> monitor what is going on.
>
> > and at the R prompt I type the function to be executed. But if I
> > type "top" at the R prompt, it says object "top" not found.
>
> top is a shell command, no issue with R not knowing about this.
>
> > So, should I change to bash prompt after running the R function? If
> > yes, how do I do it? If not, how to use "top" inside the R prompt?
>
> Basically, you can't.
>
> > Again, I think this is an OS isuuebut I could'nt find any answer
> > in the Internet. I am an independent researcher and I don't have
> > personal access to experts...this mail list is the only vent I
> > have...
>
> ... (many more dots) Do you think we are experts on your system?
>
> Please do your home work and get back to us once it's done. ;-)
>
> Cheers,
>
> --
> Benoît
> __
> R-help@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.
>
[[alternative HTML version deleted]]
__
R-help@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.
Re: [R] parallel processing in r...
Hello, On Sun, Jul 01, 2018 at 11:31:29AM +, akshay kulkarni wrote: > I tried "top" at the bash prompt, but it provides a way to measure > CPU performance of the existing processes. I want to check the CPU > usage of the execution of an R function. Try to open two bash prompts, in one use R and in the other use top to monitor what is going on. > and at the R prompt I type the function to be executed. But if I > type "top" at the R prompt, it says object "top" not found. top is a shell command, no issue with R not knowing about this. > So, should I change to bash prompt after running the R function? If > yes, how do I do it? If not, how to use "top" inside the R prompt? Basically, you can't. > Again, I think this is an OS isuuebut I could'nt find any answer > in the Internet. I am an independent researcher and I don't have > personal access to experts...this mail list is the only vent I > have... ... (many more dots) Do you think we are experts on your system? Please do your home work and get back to us once it's done. ;-) Cheers, -- Benoît signature.asc Description: PGP signature __ R-help@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.
Re: [R] parallel processing in r...
dear Members, Thanks for the reply..I do have another issue; I will be highly obliged if you answer it: I tried "top" at the bash prompt, but it provides a way to measure CPU performance of the existing processes. I want to check the CPU usage of the execution of an R function. So I start R by this $ R and at the R prompt I type the function to be executed. But if I type "top" at the R prompt, it says object "top" not found. So, should I change to bash prompt after running the R function? If yes, how do I do it? If not, how to use "top" inside the R prompt? Again, I think this is an OS isuuebut I could'nt find any answer in the Internet. I am an independent researcher and I don't have personal access to experts...this mail list is the only vent I have... Very many thanks for your time and effort... Yours sincerely, AKSHAY M KULKARNI From: Jeff Newmiller Sent: Saturday, June 30, 2018 11:46 PM To: r-help@r-project.org; akshay kulkarni; R help Mailing list Subject: Re: [R] parallel processing in r... Use "top" at the bash prompt. Read about the "mc.cores" parameter to mclapply. Make a simplified example version of your analysis and post your question in the context of that example [1][2][3]. You will learn about the issues you are dealing with in the process of trimming your problem, and will have code you can share that demonstrates the issue without exposing private information. Running parallel does not necessarily improve performance because other factors like task switching overhead and Inter-process-communication (data sharing) can drag it down. Read about the real benefits and drawbacks of parallelism... there are many discussions out there out there... you might start with [4]. [1] http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example [2] http://adv-r.had.co.nz/Reproducibility.html [3] https://cran.r-project.org/web/packages/reprex/index.html (read the vignette) [4] https://nceas.github.io/oss-lessons/parallel-computing-in-r/parallel-computing-in-r.html On June 30, 2018 10:07:49 AM PDT, akshay kulkarni wrote: >dear members, >I am using mclapply to parallelize my code. I am using Red Hat Linux in >AWS. > >When I use mclapply, I see no speed increase. I doubt that the Linux OS >is allowing fewer than the maximum number of cores to mclapply ( by >default, mclapply takes all the available cores to it). > >How do you check if the number of workers is less than the output given >by detectCores(), in Linux? Is there any R function for it? > >I do acknowledge that help on an OS is not suitable for this mailing >list, but even Internet could'nt help me. Therefore this mail.. > >very many thanks for your time and effort... >yours sincerely, >AKSHAY M KULKARNI > > [[alternative HTML version deleted]] > >__ >R-help@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. [[alternative HTML version deleted]] __ R-help@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.
Re: [R] parallel processing in r...
If you use gkrellm, you'll get a plot of each core's activity so it's easy to see how many are being used. yum install gkrellm. HTH On 07/01/2018 06:16 AM, Jeff Newmiller wrote: > Use "top" at the bash prompt. > > Read about the "mc.cores" parameter to mclapply. > > Make a simplified example version of your analysis and post your question in > the context of that example [1][2][3]. You will learn about the issues you > are dealing with in the process of trimming your problem, and will have code > you can share that demonstrates the issue without exposing private > information. > > Running parallel does not necessarily improve performance because other > factors like task switching overhead and Inter-process-communication (data > sharing) can drag it down. Read about the real benefits and drawbacks of > parallelism... there are many discussions out there out there... you might > start with [4]. > > > [1] > http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example > > [2] http://adv-r.had.co.nz/Reproducibility.html > > [3] https://cran.r-project.org/web/packages/reprex/index.html (read the > vignette) > > [4] > https://nceas.github.io/oss-lessons/parallel-computing-in-r/parallel-computing-in-r.html > > On June 30, 2018 10:07:49 AM PDT, akshay kulkarni > wrote: >> dear members, >> I am using mclapply to parallelize my code. I am using Red Hat Linux in >> AWS. >> >> When I use mclapply, I see no speed increase. I doubt that the Linux OS >> is allowing fewer than the maximum number of cores to mclapply ( by >> default, mclapply takes all the available cores to it). >> >> How do you check if the number of workers is less than the output given >> by detectCores(), in Linux? Is there any R function for it? >> >> I do acknowledge that help on an OS is not suitable for this mailing >> list, but even Internet could'nt help me. Therefore this mail.. >> >> very many thanks for your time and effort... >> yours sincerely, >> AKSHAY M KULKARNI >> >> [[alternative HTML version deleted]] >> >> __ >> R-help@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. [[alternative HTML version deleted]] __ R-help@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.
Re: [R] parallel processing in r...
Use "top" at the bash prompt. Read about the "mc.cores" parameter to mclapply. Make a simplified example version of your analysis and post your question in the context of that example [1][2][3]. You will learn about the issues you are dealing with in the process of trimming your problem, and will have code you can share that demonstrates the issue without exposing private information. Running parallel does not necessarily improve performance because other factors like task switching overhead and Inter-process-communication (data sharing) can drag it down. Read about the real benefits and drawbacks of parallelism... there are many discussions out there out there... you might start with [4]. [1] http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example [2] http://adv-r.had.co.nz/Reproducibility.html [3] https://cran.r-project.org/web/packages/reprex/index.html (read the vignette) [4] https://nceas.github.io/oss-lessons/parallel-computing-in-r/parallel-computing-in-r.html On June 30, 2018 10:07:49 AM PDT, akshay kulkarni wrote: >dear members, >I am using mclapply to parallelize my code. I am using Red Hat Linux in >AWS. > >When I use mclapply, I see no speed increase. I doubt that the Linux OS >is allowing fewer than the maximum number of cores to mclapply ( by >default, mclapply takes all the available cores to it). > >How do you check if the number of workers is less than the output given >by detectCores(), in Linux? Is there any R function for it? > >I do acknowledge that help on an OS is not suitable for this mailing >list, but even Internet could'nt help me. Therefore this mail.. > >very many thanks for your time and effort... >yours sincerely, >AKSHAY M KULKARNI > > [[alternative HTML version deleted]] > >__ >R-help@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. __ R-help@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.
Re: [R] parallel processing in r...
The effectiveness of parallelizing code, be it with mclapply or otherwise, depends in large part on the code, which you failed to show. I cannot answer your other question. Cheers, Bert 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 Sat, Jun 30, 2018 at 10:07 AM, akshay kulkarni wrote: > dear members, > I am using mclapply to parallelize my code. I > am using Red Hat Linux in AWS. > > When I use mclapply, I see no speed increase. I doubt that the Linux OS is > allowing fewer than the maximum number of cores to mclapply ( by default, > mclapply takes all the available cores to it). > > How do you check if the number of workers is less than the output given by > detectCores(), in Linux? Is there any R function for it? > > I do acknowledge that help on an OS is not suitable for this mailing list, > but even Internet could'nt help me. Therefore this mail.. > > very many thanks for your time and effort... > yours sincerely, > AKSHAY M KULKARNI > > [[alternative HTML version deleted]] > > __ > R-help@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. > [[alternative HTML version deleted]] __ R-help@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.
[R] parallel processing in r...
dear members, I am using mclapply to parallelize my code. I am using Red Hat Linux in AWS. When I use mclapply, I see no speed increase. I doubt that the Linux OS is allowing fewer than the maximum number of cores to mclapply ( by default, mclapply takes all the available cores to it). How do you check if the number of workers is less than the output given by detectCores(), in Linux? Is there any R function for it? I do acknowledge that help on an OS is not suitable for this mailing list, but even Internet could'nt help me. Therefore this mail.. very many thanks for your time and effort... yours sincerely, AKSHAY M KULKARNI [[alternative HTML version deleted]] __ R-help@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.
