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Draft: parallelize match computation in pycbc_brute_bank by shrinking multiple templates #4815

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yi-fan-wang
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Opening it here for discussion. I'd like to further parallelize pycbc_brute_bank wherever possible. The idea is to shrink multiple waveforms at once, as many as the parallel processes.

However, it doesn't really work as fast as I expected. It's actually much slower than a serial computation altogether. I suspect it's because of resource contention inside of the multiple processes.

I'd also like to explore the consequences to return inside one of the multiprocessing pools.

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ahnitz commented Jul 17, 2024

@yi-fan-wang I'm not sure this approach will work. I think the most straightforward is simple to parallelize over the proposals themselves and assume that within each proposal set there isn't much overlap.

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