[R-SIG-Mac] Different performance with different R versions

Martin Maechler m@echler @ending from @t@t@m@th@ethz@ch
Thu Dec 13 14:37:07 CET 2018

>>>>> Peter Dalgaard 
>>>>>     on Wed, 12 Dec 2018 22:12:34 +0100 writes:

    > I don't think there has been anything mentioned about slowdowns of that magnitude, but it's been 3.5 years since 3.1.3.
    > Would it be possible to narrow down what kind of code has become slow? 

    > Since the OS version is different, I assume the first timing is historical and not easily redone, but if it is now using like 70 times as long as before, chances are that it is spending 69/70 of the time in the same few places.

    > One generic frequent cause of grief with simulations is to keep onto the fitted models in entirety, including model frames etc., causing massive memory build-up.

    > -pd

If the  simulationR-R.R  script is basically reproducible
(i.e. does not use data or other resources that only exist on
 your computer), it would  probably be useful if you "donated"
 it to the R project by making it publicly available.  Some of
 us do have many old R versions still running, and could quickly
 try and see...

Martin Maechler (not a Mac user though)

    >> On 12 Dec 2018, at 17:39 , Cowan, R (MERIT) <r.cowan using maastrichtuniversity.nl> wrote:
    >> I am running a small simulation, and getting very different run times when I use different versions of R. 
    >> Two set-ups using the same machine (MacBook Pro 2013 vintage)
    >> 1. R version 3.1.3  running on system OS X 10.9.5
    >>> system.time(source("simulationR-R.R"))
    >> user  system elapsed 
    >> 3.890   0.061   3.965 
    >> Compared to
    >> 2. R version 3.5.1  running on system OS X 10.12.6
    >>> system.time(source("simulationR-R.R"))
    >> user  system elapsed 
    >> 277.924   2.087 280.841 
    >> The source code is identical. This is a pretty big difference running the same code on the same hardware.
    >> Before submitting the code, is this a known issue?
    >> Thanks,
    >> Robin Cowan
    >> _______________________________________________
    >> R-SIG-Mac mailing list
    >> R-SIG-Mac using r-project.org
    >> https://stat.ethz.ch/mailman/listinfo/r-sig-mac

    > -- 
    > Peter Dalgaard, Professor,
    > Center for Statistics, Copenhagen Business School
    > Solbjerg Plads 3, 2000 Frederiksberg, Denmark
    > Phone: (+45)38153501
    > Office: A 4.23
    > Email: pd.mes using cbs.dk  Priv: PDalgd using gmail.com

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