Difference between revisions of "R MPI Example"

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Example, of using the parallel module to run MPI jobs under SLURM with Rmpi library.
 
Example, of using the parallel module to run MPI jobs under SLURM with Rmpi library.
  
{{#fileAnchor: rmpi_test.R}}
+
<pre>
Download raw source of the [{{#fileLink: rmpi_test.R}} rmpi_test.R] file.
 
<source lang=bash>
 
 
# Load the R MPI package if it is not already loaded.
 
# Load the R MPI package if it is not already loaded.
 
if (!is.loaded("mpi_initialize")) {
 
if (!is.loaded("mpi_initialize")) {
Line 42: Line 40:
 
mpi.close.Rslaves(dellog = FALSE)
 
mpi.close.Rslaves(dellog = FALSE)
 
mpi.quit()
 
mpi.quit()
</source>
+
</pre>
  
  
 
Example job script using rmpi_test.R script.
 
Example job script using rmpi_test.R script.
  
 
+
<pre>
{{#fileAnchor: mpi_job.sh}}
 
Download raw source of the [{{#fileLink: mpi_job.sh}} mpi_job.sh] file.
 
<source lang=bash>
 
 
#!/bin/sh
 
#!/bin/sh
 
#SBATCH --job-name=mpi_job_test # Job name
 
#SBATCH --job-name=mpi_job_test # Job name
#SBATCH --mail-type=ALL # Mail events (NONE, BEGIN, END, FAIL, ALL)
+
#SBATCH --mail-type=END,FAIL # Mail events (NONE, BEGIN, END, FAIL, ALL)
 
#SBATCH --mail-user=ENTER_YOUR_EMAIL_HERE # Where to send mail
 
#SBATCH --mail-user=ENTER_YOUR_EMAIL_HERE # Where to send mail
 
#SBATCH --cpus-per-task=1 # Number of cores per MPI rank  
 
#SBATCH --cpus-per-task=1 # Number of cores per MPI rank  
 
#SBATCH --nodes=2 #Number of nodes
 
#SBATCH --nodes=2 #Number of nodes
#SBATCH --ntasks=24 # Number of MPI ranks
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#SBATCH --ntasks=8 # Number of MPI ranks
#SBATCH --ntasks-per-node=12 #How many tasks on each node
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#SBATCH --ntasks-per-node=4 #How many tasks on each node
#SBATCH --ntasks-per-socket=6 #How many tasks on each CPU or socket
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#SBATCH --ntasks-per-socket=2 #How many tasks on each CPU or socket
 
#SBATCH --distribution=cyclic:cyclic #Distribute tasks cyclically on nodes and sockets
 
#SBATCH --distribution=cyclic:cyclic #Distribute tasks cyclically on nodes and sockets
 
#SBATCH --mem-per-cpu=1gb # Memory per processor
 
#SBATCH --mem-per-cpu=1gb # Memory per processor
Line 68: Line 63:
 
echo "Running example Rmpi script. Using $SLURM_JOB_NUM_NODES nodes with $SLURM_NTASKS  
 
echo "Running example Rmpi script. Using $SLURM_JOB_NUM_NODES nodes with $SLURM_NTASKS  
 
tasks, each with $SLURM_CPUS_PER_TASK cores."
 
tasks, each with $SLURM_CPUS_PER_TASK cores."
module purge; module load intel/2016.0.109 openmpi/1.10.2 Rmpi/3.3.1
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module purge; module load gcc/9 openmpi rmpi
 
 
# Use '-np 1' since Rmpi does its own task management
 
# Make sure the mpi.spawn.Rslaves(nslaves=X) code spawns X slaves
 
# where X is one less than the total number of MPI ranks
 
  
srun --mpi=pmi2 Rscript /ufrc/data/training/SLURM/prime/rmpi_test.R
+
srun --mpi=pmi2 Rscript /data/training/SLURM/rmpi_test.R
  
 
date
 
date
</source>
+
</pre>
 
 
 
 
Example <code>.Rprofile</code> configuration file that must be placed in the working directory:
 
 
 
<source lang=R>
 
 
 
.Rprofile config in the working directory:
 
 
 
# This R profile can be used when a cluster does not allow spawning or a
 
# job scheduler is required to launch any parallel jobs. Saving this
 
# file as .Rprofile in the working directory or root directory. For unix
 
# platform, run mpirexec -n [cpu numbers] R --no-save -q For windows
 
# platform with mpich2, use mpiexec wrapper and specify a working
 
# directory where .Rprofile is inside. Cannot be used as Rprofile.site
 
# because it will not work Following system libraries are not loaded
 
# automatically. So manual loads are needed.
 
  
library(utils)
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For rmpi/4.0 module the following command will work
library(stats)
 
library(datasets)
 
library(grDevices)
 
library(graphics)
 
library(methods)
 
  
if (!invisible(library(Rmpi,logical.return = TRUE))){
+
mpiexec -n ${SLURM_NTASKS} Rscript rmpi_test.R
    warning("Rmpi cannot be loaded")
 
    q(save = "no")
 
}
 
  
options(error=quote(assign(".mpi.err", FALSE, env = .GlobalEnv)))
 
  
if (mpi.comm.size(0) > 1)
+
Link the /apps/rmpi/conf/Rprofile as .Rprofile in the current directory configuration file that must be placed in the working directory if the rmpi module doesn't add a symlink automatically.
    invisible(mpi.comm.dup(0,1))
 
  
if (mpi.comm.rank(0) > 0){
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<pre>
    options(echo=FALSE)
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ln -s /apps/rmpi/conf/Rprofile .Rprofile
    .comm <- 1
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</pre>
    mpi.barrier(0)
 
    repeat
 
    try(eval(mpi.bcast.cmd(rank=0,comm=.comm)),TRUE)
 
    if (is.loaded("mpi_comm_disconnect"))
 
        mpi.comm.disconnect(.comm)
 
    else mpi.comm.free(.comm)
 
        mpi.quit()
 
}
 
 
 
if (mpi.comm.rank(0)==0) {
 
    options(echo=TRUE)
 
    mpi.barrier(0)
 
    if(mpi.comm.size(0) > 1)
 
        slave.hostinfo(1)
 
}
 
 
 
.Last <- function(){
 
    if (is.loaded("mpi_initialize")){
 
        if (mpi.comm.size(1) > 1){
 
            print("Please use mpi.close.Rslaves() to close slaves")
 
            mpi.close.Rslaves(comm=1)
 
        }
 
    }
 
    print("Please use mpi.quit() to quit R")
 
    mpi.quit()
 
}
 
</source>
 

Latest revision as of 13:54, 30 September 2020

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Example, of using the parallel module to run MPI jobs under SLURM with Rmpi library.

# Load the R MPI package if it is not already loaded.
if (!is.loaded("mpi_initialize")) {
    library("Rmpi")
    }

ns <- mpi.universe.size() - 1
mpi.spawn.Rslaves(nslaves=ns)
#
# In case R exits unexpectedly, have it automatically clean up
# resources taken up by Rmpi (slaves, memory, etc...)
.Last <- function(){
       if (is.loaded("mpi_initialize")){
           if (mpi.comm.size(1) > 0){
               print("Please use mpi.close.Rslaves() to close slaves.")
               mpi.close.Rslaves()
           }
           print("Please use mpi.quit() to quit R")
           .Call("mpi_finalize")
       }
}
# Tell all slaves to return a message identifying themselves
mpi.bcast.cmd( id <- mpi.comm.rank() )
mpi.bcast.cmd( ns <- mpi.comm.size() )
mpi.bcast.cmd( host <- mpi.get.processor.name() )
mpi.remote.exec(paste("I am",mpi.comm.rank(),"of",mpi.comm.size()))

# Test computations
x <- 5
x <- mpi.remote.exec(rnorm, x)
length(x)
x

# Tell all slaves to close down, and exit the program
mpi.close.Rslaves(dellog = FALSE)
mpi.quit()


Example job script using rmpi_test.R script.

#!/bin/sh
#SBATCH --job-name=mpi_job_test # Job name
#SBATCH --mail-type=END,FAIL # Mail events (NONE, BEGIN, END, FAIL, ALL)
#SBATCH --mail-user=ENTER_YOUR_EMAIL_HERE # Where to send mail	
#SBATCH --cpus-per-task=1 # Number of cores per MPI rank 
#SBATCH --nodes=2 #Number of nodes
#SBATCH --ntasks=8 # Number of MPI ranks
#SBATCH --ntasks-per-node=4 #How many tasks on each node
#SBATCH --ntasks-per-socket=2 #How many tasks on each CPU or socket
#SBATCH --distribution=cyclic:cyclic #Distribute tasks cyclically on nodes and sockets
#SBATCH --mem-per-cpu=1gb # Memory per processor
#SBATCH --time=00:05:00 # Time limit hrs:min:sec
#SBATCH --output=mpi_test_%j.out # Standard output and error log
pwd; hostname; date

echo "Running example Rmpi script. Using $SLURM_JOB_NUM_NODES nodes with $SLURM_NTASKS 
tasks, each with $SLURM_CPUS_PER_TASK cores."
module purge; module load gcc/9 openmpi rmpi

srun --mpi=pmi2 Rscript /data/training/SLURM/rmpi_test.R

date

For rmpi/4.0 module the following command will work

mpiexec -n ${SLURM_NTASKS} Rscript rmpi_test.R


Link the /apps/rmpi/conf/Rprofile as .Rprofile in the current directory configuration file that must be placed in the working directory if the rmpi module doesn't add a symlink automatically.

ln -s /apps/rmpi/conf/Rprofile .Rprofile