Heya,

quick update: I was able to reproduce the effects described by Zach
with a simple test model[1], which breaks down (i.e. sends my test
machine into swapping with just 60 simulation entities) at 100k time
steps.

On 07:41 Fri 19 Aug     , Hartmut Kaiser wrote:
> To make a long story short, I'd suggest to change all dataflow(...) function
> calls in DGSWEM/HPX with dataflow(hpx::launch::fork, ...) and see if this
> helps the issue. It actually should - it would be nice to see whether theory
> and practice are actually the same for a change ;)

I did measure hpx::launch::async and hpx::launch::fork for less than
100k time steps (results attached). async broke down at ~75k time
steps, fork did mitigate this effect up to ~95k time steps but broke
down as well.

I then implemented a simple chunked approach with a barrier every
"chunkSize" time steps. This is terrible as it forces all cores to
drain prior to generating more work, but my tries to overlap dataflow
generation with work were unsuccessful (I spent 2h on this but only
got deadlocks. I'd be happy to merge a PR that would this issue).
chunkSize is configurable, though, so the actual effect shouldn't be
too bad. With this change I can easily go up to 300k time steps
without seeing any degradation of the time taken per time step.

Cheers
-Andi

[1] 
https://github.com/gentryx/libgeodecomp/commit/c7fa53f4462b3562a189a2f521221e6ddb22cafc
[2] 
https://github.com/gentryx/libgeodecomp/commit/6a4a6a747484476b291d00a23fe515ffcd49b8d2


-- 
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Andreas Schäfer
HPC and Supercomputing
Institute for Multiscale Simulation
Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany
+49 9131 85-20866
PGP/GPG key via keyserver
http://www.libgeodecomp.org
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