I'm exploring latency overhead of parallel PSOCK workers and noticed
that serializing/unserializing data back to the main R session is
significantly slower on Linux than it is on Windows/MacOS with similar
hardware. Is there a reason for this difference and is there a way to
avoid the apparent additional Linux overhead?
I attempted to isolate the behavior with a test that simply returns an
existing object from the worker back to the main R session.
library(parallel)
library(microbenchmark)
gcinfo(TRUE)
cl <- makeCluster(1)
(x <- microbenchmark(clusterEvalQ(cl, iris), times = 1000, unit = "us"))
plot(x$time, ylab = "microseconds")
head(x$time, n = 10)
On Windows/MacOS, the test runs in 300-500 microseconds depending on
hardware. A few of the 1000 runs are an order of magnitude slower but
this can probably be attributed to garbage collection on the worker.
On Linux, the first 5 or so executions run at comparable speeds but all
subsequent executions are two orders of magnitude slower (~40
milliseconds).
I see this behavior across various platforms and hardware combinations:
Ubuntu 18.04 (Intel Xeon Platinum 8259CL)
Linux Mint 19.3 (AMD Ryzen 7 1800X)
Linux Mint 20 (AMD Ryzen 7 3700X)
Windows 10 (AMD Ryzen 7 4800H)
MacOS 10.15.7 (Intel Core i7-8850H)
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