# Parallel assembly of a finite element sparse matrix

**URL:** <https://discourse.julialang.org/t/parallel-assembly-of-a-finite-element-sparse-matrix/95947>\
**Category:** General Usage\
**Tags:** parallel\
**Created:** [March 12, 2023, 2:11am UTC](https://discourse.julialang.org/t/parallel-assembly-of-a-finite-element-sparse-matrix/95947 "2023-03-12T02:11:37Z")\
**Posts on this page:** 1\
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**Author:** ![termi-official](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/termi-official/32/47815_2.png) [@termi-official](https://discourse.julialang.org/u/termi-official)\
**Post date:** [March 17, 2023, 1:49pm UTC](https://discourse.julialang.org/t/parallel-assembly-of-a-finite-element-sparse-matrix/95947/24 "2023-03-17T13:49:21Z")

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Thanks for investigating this issue further Prof. Krysl. Sorry, I could not find time to come back to the issue linked by Kristoffer yet (but I still follow the thread). From a performance perspective the assembly on a single thread is more or less compute bound. Parallelizing assembly with a low number of threads should not be a big issue (with sufficient memory bandwidth and cache). However, with more threads you increase the pressure on all memory lanes. Here I still think it is a mixture of cache/bandwidth issues (i.e. bad or even conflicting cache access patterns+memory bus cannot keep up with the CPUs read/write access) and frequency boosting (i.e. at lower total load each core has higher frequency). Fore some discussion I highly recommend the WorkStream paper ([dx.doi.org/10.1145/2851488](http://dx.doi.org/10.1145/2851488)), because we basically reproduce Figure 4 from this paper. However, take this with a grain of salt, as I still have to confirm everything in more detailed benchmarks.

Another relevant thread is [How to achieve perfect scaling with Threads (Julia 1.7.1) - #10 by carstenbauer](https://discourse.julialang.org/t/how-to-achieve-perfect-scaling-with-threads-julia-1-7-1/92603/10) which discusses some of the mentioned problems in more detail.

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