By default, ParallelTable will use all the processors available in a PC. Is there a way to set a limit to the number of processors used by ParallelTable? For example, suppose I am running a Mathematica Script which has a ParallelTable statement on a PC with 8 cores. I want to limit the number of cores used by the script to 4. How can I do this?

  • $\begingroup$ Have you tried setting the parallel kernels from Evaluation->Parallel Kernel configuration -> Parallel tab -> Manual setting $\endgroup$ Apr 9 '15 at 15:59
  • $\begingroup$ @GordonCoale This is a Mathematica script, which will run with no graphical interface. $\endgroup$
    – becko
    Apr 10 '15 at 12:09
  • 1
    $\begingroup$ Its worth noting that if you want to set this persistently then the you can do with code so via Unprotect[$ProcessorCount]; $ProcessorCount = 4; I would presume LaunchKernels is better for most use cases. $\endgroup$ Apr 10 '15 at 13:21

Before evaluating ParallelTable just launch however many kernels you want to use:


By default ParallelTable and the other Parallel* functions call LaunchKernels[] which will launch whatever you have configured(default is essentially LaunchKernels[Min[$ProcessorCount, $MaxLicenseSubprocesses]]).


To demonstrate evaluation in parallel computing on different number of kernels

1)Default list of kernels run for parallel computing

 (*("<<`1` local kernels>>", 6]}*)

2) Run ParallelTable on all kernels:

ParallelTable[Pause[1]; f[i], {i, 6}] // AbsoluteTiming 

  (*{1.009058, {f[1], f[2], f[3], f[4], f[5], f[6]}}*)

This result demonstrates how Pause[1]is distributed on 6 kernels: Total 6 seconds of pause are executed on 6 Kernels in parallel resulting in 1 seconds of execution

3) Run ParallelTable on only two kernels:

ParallelTable[Pause[1]; f[i], {i, 6}] // AbsoluteTiming   

(*{KernelObject[37, "local"], KernelObject[38, "local"]}   *)
    (*{3.004172, {f[1], f[2], f[3], f[4], f[5], f[6]}}*)

This result demonstrates how Pause[1] is distributed on 2 kernels: Total 6 seconds of pause are executed on 2 Kernels in parallel resulting in 3 seconds of execution


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