Julia uses only 20-30% of my CPU. What should I do?

Question

I am running a program that does numeric ODE integration in Julia. I am running Windows 10 (64bit), with Intel Core i7-4710MQ @ 2.50Ghz (8 logical processors).

I noticed that when my code was running on julia, only max 30% of CPU is in usage. Going into the parallelazation documentation, I started Julia using: C:\Users\*****\AppData\Local\Julia-0.4.5\bin\julia.exe -p 8 and expected to see improvements. I did not see them however.

Therefore my question is the following: Is there a special way I have to write my code in order for it to use CPU more efficiently? Is this maybe a limitation posed by my operating system (windows 10)?

I submit my code in the julia console with the command: include("C:\\Users\\****\\AppData\\Local\\Julia-0.4.5\\13. Fast Filesaving Format.jl").

Within this code I use some additional packages with: using ODE; using PyPlot; using JLD.

I measure the CPU usage with windows' "Task Manager".

Answer 1

The -p 8 option to julia starts 8 worker processes, and disables multithreading in libraries like BLAS and FFTW so that the workers don't oversubscribe the physical threads on the system – since this kills performance in well-balanced distributed workloads. If you want to get more speed out of -p 8 then you need to distribute work between those workers, e.g. by having each of them do an independent computation, or by having the collaborate on a computation via SharedArrays. You can't just add workers and not change the program. If you are using BLAS (doing lots of matrix multiplies) or FFTW (doing lots of Fourier transforms), then if you don't use the -p flag, you'll automatically get multithreading from those libraries. Otherwise, there is no (non-experimental) user-level threading in Julia yet. There is experimental threading support and version 1.0 will support threading, but I wouldn't recommend that yet unless you're an expert.