# Launching with JULIA\_NUM\_THREADS=\<max\>

**URL:** <https://discourse.julialang.org/t/launching-with-julia-num-threads-max/52964>\
**Category:** Performance\
**Tags:** question, parallel, threads\
**Created:** [January 6, 2021, 10:57pm UTC](https://discourse.julialang.org/t/launching-with-julia-num-threads-max/52964 "2021-01-06T22:57:18Z")\
**Posts on this page:** 1\
**Showing post:** 3

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**Author:** ![moeddel](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/moeddel/32/18641_2.png) [@moeddel](https://discourse.julialang.org/u/moeddel)\
**Post date:** [January 7, 2021, 6:17pm UTC](https://discourse.julialang.org/t/launching-with-julia-num-threads-max/52964/3 "2021-01-07T18:17:11Z")

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Actually there can julia can also compete with itself if one uses julia treads and BLAS, which by default has its own thread pool

> [@Julia Threads vs BLAS threads](https://discourse.julialang.org/t/julia-threads-vs-blas-threads/8914):
>
> I am experimenting with Julia’s (experimental) multithreading feature recently and like the results so far. One of the problems I need to deal with, involves the multiplication of several pairs (say in the order 5 to 50) of matrices, whose size is average (say linear size in the order 10 - 1000). For that problem, there can be a competition between either using Julia threads (to loop over the different pairs) versus using multithreaded matrix multiplication provided by BLAS, and it will depend …

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