Hi all, I have two questions.
What are the recommended values of the env variables (
MKL/OPENBLAS_NUM_THREADS, …) if I want to speed up my code using
To what should I set those variables (the former ones plus
addprocs(x)) if, instead, I would like to use
pmapto get more performance?
The heaviest parts of my scripts usually involve diagonalizing very large Hermitian matrices and/or BLAS operations. Also (3.), is there any possibility to mix multithreading code within parallel loops and still improve performance, or should I avoid using multithreading when I am already using parallel and vice-verse?
For more information, the Julia version I am using is
>>> versioninfo() Julia Version 1.1.0 Commit 80516ca202* (2019-01-21 21:24 UTC) Platform Info: OS: Linux (x86_64-linux-gnu) CPU: Intel(R) Xeon(R) W-2145 CPU @ 3.70GHz WORD_SIZE: 64 LIBM: libopenlibm LLVM: libLLVM-6.0.1 (ORCJIT, skylake) Environment: JULIA_NUM_THREADS = 12
W-2145 CPU @ 3.70GHz I reached this page, where it says I have 8 cores and 16 threads. Should the answer for 1. be
JULIA_NUM_THREADS=16 and the answer for 2. be
addprocs(8)? What about