Hi Akshay, In addition to all the things Jeff rightly points out, contention for IO resources can be an issue. So if another process was hogging the bandwidth while your program was attempting to read or write to disk, that could also have slowed things down. HTH Loris Jeff Newmiller <jdnewmil at dcn.davis.ca.us> writes:> Wow, you can find almost any explanation on the Internets. That doesn't mean you > should believe all of them. R does not do anything likely to tweak > interrupts... if that is your problem then you need to be on an > operating-system/computer-model-specific forum rather than this OS-agnostic > mailing list. > > It is far more likely that your overall memory usage conditions have changed > since the last time you ran it... or that you didn't actually record all of the > things you did last time in your script. (Newbie R users often do things at the > console without putting them in their scripts.) > > I suggest that you run your script one statement at a time and see where your > problem is. You might also want to make sure that other programs are not using > up a lot of your memory (which could involve some OS-specific tools or just > shutting down some other programs.) > > On June 12, 2018 7:36:40 PM HST, akshay kulkarni <akshay_e4 at hotmail.com> wrote: >>I ran a function in R three days ago and the execution time was about >>4 minutes. I ran the same function yesterday and the execution time was >>more than 6:50 minutes(I aborted the function after that time). >> >>I read in the Internet that this is possible. I also came to know that >>software or hardware interrupts are the main reasons. >> >>How do you know whether the delay was caused by interrupts? Which >>hardware or software triggered the interrupts? In general, how to know >>the exact cause of the delay in execution in R? Are there any packages >>for these analyses? >> >>Very many thanks for your time and effort.... >> >>yours sincerely, >>AKSHAY M KULKARNI >> >> [[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.-- Dr. Loris Bennett (Mr.) ZEDAT, Freie Universit?t Berlin Email loris.bennett at fu-berlin.de
I do felt a little unsettled by your exhortions on the incongruity of posting this question on an OS-agnostic mailing list...I thought that there might be some issues on how R communicates with the OS...and also that some R packages might rectify the issue(in my experience, I have had a R package for every R issue that I had!) Anyway, I ran the same function again and it is executing within limits. Also, I would be using AWS EC2 servers to run my R functions(I am a day trader in india and input some 250 stocks to R functions daily), and I don't think that the issue would persist on Intel Xeon processors and dedicated VMs.... Anyway,thanks for all your concerns tolerating my query on an OS-agnostic mailing list! AKSHAY M KULKARNI ________________________________ From: Loris Bennett <loris.bennett at fu-berlin.de> Sent: Wednesday, June 13, 2018 1:37 PM To: Jeff Newmiller Cc: r-help at r-project.org; akshay kulkarni Subject: Re: [R] on execution time of a function... Hi Akshay, In addition to all the things Jeff rightly points out, contention for IO resources can be an issue. So if another process was hogging the bandwidth while your program was attempting to read or write to disk, that could also have slowed things down. HTH Loris Jeff Newmiller <jdnewmil at dcn.davis.ca.us> writes:> Wow, you can find almost any explanation on the Internets. That doesn't mean you > should believe all of them. R does not do anything likely to tweak > interrupts... if that is your problem then you need to be on an > operating-system/computer-model-specific forum rather than this OS-agnostic > mailing list. > > It is far more likely that your overall memory usage conditions have changed > since the last time you ran it... or that you didn't actually record all of the > things you did last time in your script. (Newbie R users often do things at the > console without putting them in their scripts.) > > I suggest that you run your script one statement at a time and see where your > problem is. You might also want to make sure that other programs are not using > up a lot of your memory (which could involve some OS-specific tools or just > shutting down some other programs.) > > On June 12, 2018 7:36:40 PM HST, akshay kulkarni <akshay_e4 at hotmail.com> wrote: >>I ran a function in R three days ago and the execution time was about >>4 minutes. I ran the same function yesterday and the execution time was >>more than 6:50 minutes(I aborted the function after that time). >> >>I read in the Internet that this is possible. I also came to know that >>software or hardware interrupts are the main reasons. >> >>How do you know whether the delay was caused by interrupts? Which >>hardware or software triggered the interrupts? In general, how to know >>the exact cause of the delay in execution in R? Are there any packages >>for these analyses? >> >>Very many thanks for your time and effort.... >> >>yours sincerely, >>AKSHAY M KULKARNI >> >> [[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.-- Dr. Loris Bennett (Mr.) ZEDAT, Freie Universit?t Berlin Email loris.bennett at fu-berlin.de [[alternative HTML version deleted]]
it is not just the list that is OS-agnostic... R itself is quite OS-agnostic. However, depending on where you get your packages from they may have something unusual going on in their compiled C or Fortran code. It is just that for a computationally-oriented application like R code that messed with hardware interrupts seem out of place. I suppose that a bug in a CUDA-related package could screw up interrupts... but the whole point of having an OS as hardware drivers/APIs is to insulate user-level programs like R from those issues, and at best you would post the details of your code and packages and someone might pick up on an odd package and point you toward a more appropriate forum for debugging it. On June 12, 2018 11:39:40 PM HST, akshay kulkarni <akshay_e4 at hotmail.com> wrote:>I do felt a little unsettled by your exhortions on the incongruity of >posting this question on an OS-agnostic mailing list...I thought that >there might be some issues on how R communicates with the OS...and also >that some R packages might rectify the issue(in my experience, I have >had a R package for every R issue that I had!) > >Anyway, I ran the same function again and it is executing within >limits. Also, I would be using AWS EC2 servers to run my R functions(I >am a day trader in india and input some 250 stocks to R functions >daily), and I don't think that the issue would persist on Intel Xeon >processors and dedicated VMs.... > >Anyway,thanks for all your concerns tolerating my query on an >OS-agnostic mailing list! > >AKSHAY M KULKARNI >________________________________ >From: Loris Bennett <loris.bennett at fu-berlin.de> >Sent: Wednesday, June 13, 2018 1:37 PM >To: Jeff Newmiller >Cc: r-help at r-project.org; akshay kulkarni >Subject: Re: [R] on execution time of a function... > >Hi Akshay, > >In addition to all the things Jeff rightly points out, contention for >IO >resources can be an issue. So if another process was hogging the >bandwidth while your program was attempting to read or write to disk, >that could also have slowed things down. > >HTH > >Loris > >Jeff Newmiller <jdnewmil at dcn.davis.ca.us> writes: > >> Wow, you can find almost any explanation on the Internets. That >doesn't mean you >> should believe all of them. R does not do anything likely to tweak >> interrupts... if that is your problem then you need to be on an >> operating-system/computer-model-specific forum rather than this >OS-agnostic >> mailing list. >> >> It is far more likely that your overall memory usage conditions have >changed >> since the last time you ran it... or that you didn't actually record >all of the >> things you did last time in your script. (Newbie R users often do >things at the >> console without putting them in their scripts.) >> >> I suggest that you run your script one statement at a time and see >where your >> problem is. You might also want to make sure that other programs are >not using >> up a lot of your memory (which could involve some OS-specific tools >or just >> shutting down some other programs.) >> >> On June 12, 2018 7:36:40 PM HST, akshay kulkarni ><akshay_e4 at hotmail.com> wrote: >>>I ran a function in R three days ago and the execution time was >about >>>4 minutes. I ran the same function yesterday and the execution time >was >>>more than 6:50 minutes(I aborted the function after that time). >>> >>>I read in the Internet that this is possible. I also came to know >that >>>software or hardware interrupts are the main reasons. >>> >>>How do you know whether the delay was caused by interrupts? Which >>>hardware or software triggered the interrupts? In general, how to >know >>>the exact cause of the delay in execution in R? Are there any >packages >>>for these analyses? >>> >>>Very many thanks for your time and effort.... >>> >>>yours sincerely, >>>AKSHAY M KULKARNI >>> >>> [[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. >-- >Dr. Loris Bennett (Mr.) >ZEDAT, Freie Universit?t Berlin Email >loris.bennett at fu-berlin.de-- Sent from my phone. Please excuse my brevity.