Good day,
I have a minimal example of bplapply stalling.
results <- lapply(1:20, function(variety)
{
message("Variety", variety)
bplapply(1:100, function(index) {res <- list(sample(20000),
sample(c("Healthy", "Disease"), 20000, replace = TRUE)); res}, BPPARAM =
MulticoreParam(workers = 25))
})
It sometimes stalls on no particular iteration, but other times it runs all 20
iterations and returns to the R command prompt. It's not reproducible when the
stall happens. I am trying to find the cause of a cross-validation loop that
progresses for a few hours, then stalls. When the stall happens, two or three
of the R processes appear to be using 100% CPU whereas the others are finished,
according to the output of top. The server was previously running R 3.1.2 and
Debian 7 and this didn't ever happen. The server has 48 processors.
If I set workers to 5, it always completes the loop and returns to the prompt.
Using mclapply with mc.cores set to 25 also always works, so the problem is
with bplapply.
R version 3.2.3 (2015-12-10)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Debian GNU/Linux 8 (jessie)
locale:
[1] LC_CTYPE=C.UTF-8 LC_NUMERIC=C LC_TIME=C.UTF-8
LC_COLLATE=C.UTF-8
[5] LC_MONETARY=C.UTF-8 LC_MESSAGES=C.UTF-8 LC_PAPER=C.UTF-8
LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=C.UTF-8
LC_IDENTIFICATION=C
attached base packages:
[1] parallel stats graphics grDevices utils datasets methods base
other attached packages:
[1] BiocParallel_1.4.3
loaded via a namespace (and not attached):
[1] futile.logger_1.4.1 lambda.r_1.1.7 futile.options_1.0.0
--------------------------------------
Dario Strbenac
PhD Student
University of Sydney
Camperdown NSW 2050
Australia
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