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glmmTMB, OpenMP and Ubuntu

3 messages · meg@-x m@iii@g oii gmx@@et, J. Marius RAKOTONDRAMANGA, Ben Bolker

Original
meg@-x m@iii@g oii gmx@@et
# 
Dear all,



I am currently fitting a complex model with glmmTMB that involves random
effects and covariance structures (spatiotemporal autocorrelation). I would
like to try the experimental parallel optimization feature
<https://cran.r-project.org/web/packages/glmmTMB/vignettes/parallel.html>
to reduce computation time. To do this I've setup a virtual machine running
Ubuntu 20.04 on 16+ cores. However, I found no information in how to setup
OpenMP, R and glmmTMB. Is there a step by step guide that I can follow?



The Vignette states the following:

"If your OS supports OpenMP parallelization and R was installed using
OpenMP, glmmTMB will automatically pick up the OpenMP flags from R's
Makevars and compile the C++ model with OpenMP support."

I was not able to find any information on how to install R using OpenMP.



Best,



Xaver
J. Marius RAKOTONDRAMANGA
# 
Dear Xaver,

Have a look on these two links, they may help you to install and configure
"openmpi-bin" on Ubuntu and "Rmpi" R packages:
1- https://zoomadmin.com/HowToInstall/UbuntuPackage/openmpi-bin
2- http://webhome.auburn.edu/~zengpen/tutorials/openMPI_with_R.pdf

Best regards,

---------
J. Marius RAKOTONDRAMANGA, MSc
PhD Student in Biostatistics/Biomathematics
Sorbonne Universit? (ex. UPMC)

Le lun. 7 sept. 2020 ? 12:56, <mega-x at gmx.net> a ?crit :

  
  


  


      

    

    

      
      

        


  

        

      Ben Bolker
    

    

      
      #
    

  


  

      
Try running TMB::openmp() . If you already have R installed with 
OpenMP support, that should tell you how many cores OpenMP is configured 
to run with.
    In general R automatically gets built with OpenMP support if a given 
OS/compiler combination supports it; I don't know much about how to 
troubleshoot that if it *doesn't* happen automatically, but there seems 
to be a little information  here

https://cran.r-project.org/web/packages/ProFit/vignettes/ProFit-OpenCL-OpenMP.html

   After it's installed, you could try running some fairly big models 
with glmmTMB(..., control=glmmTMBControl(parallel=xx)) where xx is 
either 1 or >1 (NULL, the default, automatically sets the max number of 
OpenMP threads to the number of available cores on my machine).  Use 
system.time() to check the elapsed time (if you want to be more 
systematic and your examples are fast enough to run several times, you 
can use one of the available R benchmarking package).  I would also 
suggest using 'top' or some system monitoring GUI to check the CPU load 
while your job is running ... the expectation is that the CPU % listed 
for your R process will reflect the number of OpenMP threads being used.

   If you encounter anything particularly interesting you could report 
it at https://github.com/glmmTMB/glmmTMB/issues/620 ...

        
On 9/7/20 5:56 AM, mega-x at gmx.net wrote: