[] ls
run.sh snow_test.R
[]$ sbatch run.sh
Submitted batch job 13433495
# jobJob should take less that 10 seconds to complete.
[] ls
run.sh slurm-13433495.out snow_test_13433495.log values.csv snow_test.R
[] cat slurm-13433495.out
SLURM_JOB_ID: 13433495
[]$ cat snow_test_13433495.log
Loading required package: utils
> library(Rmpi)
> library(snow)
>
> simu <- function(rep_worker, n_used) {
+ theta_simu <- c()
+ for (i in 1 : rep_worker) {
+ theta_simu[i] <- mean(rnorm(n_used))
+ }
+ theta_simu
+ }
>
> num_of_processes <- mpi.universe.size()
> sprintf("Num of Processes: %d", num_of_processes)
[1] "Num of Processes: 32"
>
> cluster <- makeCluster(num_of_processes - 1, type = "MPI")
>
> n_used <- 1e4
> rep_worker_list <- rep(1, 100)
>
> theta <- clusterApply(cluster, rep_worker_list, simu, n_used)
>
> theta_cbind <- do.call(cbind, theta)
> write.csv(theta_cbind, file="values.csv")
>
> stopCluster(cluster)
# Output will be of the form:
[]$ cat values.csv
"","V1","V2","V3","V4","V5","V6","V7","V8","V9","V10","V11","V12","V13","V14","V15","V16","V17","V18","V19","V20","V21","V22","V23","V24","V25","V26","V27","V28","V29","V30","V31","V32","V33","V34","V35","V36","V37","V38","V39","V40","V41","V42","V43","V44","V45","V46","V47","V48","V49","V50","V51","V52","V53","V54","V55","V56","V57","V58","V59","V60","V61","V62","V63","V64","V65","V66","V67","V68","V69","V70","V71","V72","V73","V74","V75","V76","V77","V78","V79","V80","V81","V82","V83","V84","V85","V86","V87","V88","V89","V90","V91","V92","V93","V94","V95","V96","V97","V98","V99","V100"
"1",0.0110153488801525,0.00906305581302429,0.00108685858240707,0.00867668055186904,0.00578274342442965,-0.00530732478112944,0.0120954477596871,-0.00359434785869044,0.00835107071072111,2.64364921843532e-05,0.0152691100103968,-0.0135202565458591,0.00241255871463997,0.00137419862397849,0.00115252792794432,-0.0175922825490621,0.00110849307208272,-0.00937694151181359,-0.0131149112354201,0.00596388487426565,0.0219874640222224,-0.00547747285343229,0.00416837900267555,0.0139932426057719,-0.0234641772417162,0.00433451519201003,-0.00525816814860096,0.00414031282343361,0.00130366800166443,0.000413263824619443,0.0104087338213028,0.00149700313038921,0.011502836202072,-0.00715751527844509,0.0119589163613294,0.0220381656609346,-0.016000771903997,-0.00183947331801148,-0.00284276679070134,-0.00694346146022534,-0.0258218986912262,0.00473135994639517,0.00831409717862001,0.0182355174080247,-0.00931334883761317,0.00529566801009098,-0.00302557027855197,0.00346677904211363,0.00571337545701443,-0.00586232060572412,-0.00256997376593396,0.0165929336422106,0.00796493065507422,-0.00438474136670677,0.0062288833102191,-0.0175721248899911,0.00165933692067554,-0.00237930737409138,0.00121451126970138,0.00623046211970692,0.00559793460867063,-0.00412640828783677,-0.00764407338711362,-0.000460569630436792,-0.0107502392297747,-0.00421225031438457,-0.000926513045440252,0.00334739878419211,-0.00452111805160875,-0.0046740544706875,0.0155997050952078,-0.0234192042710321,0.00324579902597707,-0.0151148830758793,-0.000523464705140069,-0.00175640010460385,-0.010243166679217,-0.00668035373700306,-0.0119873621894053,-0.0141762507674786,-0.00783107010368886,0.0115902891884065,-0.00762658494377125,-0.0223384107212392,-0.00379425267947311,0.0138895890210734,0.00392029947365504,0.00248380077423007,-0.0064247327395136,0.00434147149528924,-0.00572841369840578,0.00966805999144852,-0.0122907653345613,0.00596172188548434,-0.0122757100311107,-0.000426327204500513,0.00108879897276763,0.00975469886227781,0.00675195747959386,-0.00288208828533988 |