Comments (2)
Parallelizing ProPhasm, local greedy or global greedy will be quite challenging IMHO and definitely require a lot of care. The program may also need more memory. This is because when extending several local paths (simplitigs or pseudosimplitigs) in parallel, one needs to lock individual k-mers so that no two threads will add any k-mer at once.
Likewise, global greedy in the hash-table implementation may be parallelized by searching for length-d overlaps in parallel, again using locking on individual k-mers that are merged.
from prophasm2.
This is actually an interesting question.
I think we don't need to parallelize the actual computation of simplitigs (it's quite fast at its own I believe), but other levels:
- simultaneous reading from multiple files
- parallelized reading of individual files (eg individual sequences)
Some relevant experiments regarding parallelization and optimized reading were done here:
https://github.com/lh3/kmer-cnt
from prophasm2.
Related Issues (9)
- Step 1: Efficient computation from KmerCamel tailored to simplitigs
- Step 2: intersections & deletions; interface mimicked from ProphAsm 1
- Feature request: Support for k-mer frequencies
- Feature request: Rolling hashing HOT 1
- Feature request: k-mer length >32 with `-large` version included HOT 2
- Feature request: Reduce memory requirements for each simplitig by printing the right extensions directly to output.
- 2x slower with k=18 HOT 3
- Support for k-mer sizes > 64
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from prophasm2.