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What is typically the best way to multi thread the assembly loop in a finite element code? Does anyone have experience with implementing this, that they can share? I can think of a couple of ways of doing it:

  1. Divide the mesh into different cell sets, where the elements in each set does not share dofs, such that the threads can add element-stiffness-matrices to the global stiffness matrix directly (without worrying about them accessing the same data).

  2. Divide the mesh into cell sets and create a separate global stiffness matrix for each thread, and then combine the stiffness-matrices at the end.

  3. Dont divide into cellsets, but rather spawn a new thread/tasks for each cell (this can be good for load balancing, if some of the elements are more expensive than others, while some are still elastic).

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    $\begingroup$ Option 4: don't overthink it. use a thread-safe container to add your sparse matrix triplets in a parallel loop, in whatever order you please. that got my assembly time down to less than 1% of the total runtime. revisit the issue if it becomes a bottleneck! $\endgroup$
    – Charlie S
    Commented Oct 12, 2021 at 1:14

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It turns out that I have just the right paper for you on this subject: https://www.math.colostate.edu/~bangerth/publications/2013-pattern.pdf

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  • $\begingroup$ Thanks, I will definitely read it. Can you summarise what the best approach was? $\endgroup$
    – lijas
    Commented Oct 12, 2021 at 7:42
  • $\begingroup$ If I understood everything correctly, I think that my option 1 was what gave best scalability in your paper. You use some sort of coloring algorithm such that you avoid the need for reduction. $\endgroup$
    – lijas
    Commented Oct 12, 2021 at 11:51
  • $\begingroup$ @iljas No :-) That's what abstract, introduction, and conclusions of the paper are there for :-) $\endgroup$
    – Wolfgang Bangerth
    Commented Oct 12, 2021 at 11:51
  • $\begingroup$ And yes, coloring is what makes it all work. $\endgroup$
    – Wolfgang Bangerth
    Commented Oct 12, 2021 at 11:52

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