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The Smith-Waterman algorithm they made an accelerator for was probably chosen because it is highly parallelizable. On a CPU it is more accurate but a lot slower
by alephnil 6y ago
The Smith-Waterman algorithm they made an accelerator for was probably chosen because it is highly parallelizable. On a CPU it is more accurate but a lot slower than the BLAST algorithm, which is more commonly used to search for similar DNA or Protein sequences. One could think that this chip would make the more accurate Smith-Waterman algorithm more attractive to use, but I suspect the difference is not large enough to get biologists invest in specialized hardware. I think this is more of a showcase of what you can do with accelerators, and they picked a problem that would give impressive numbers.
- borramakot 6y agoI don't know much about genomics, but I think there are at least FPGA based accelerators in production, for example, Illumina's DRAGEN. https://www.illumina.com/products/by-type/informatics-products/dragen-bio-it-platform.html https://www.illumina.com/products/by-type/informatics-produc...
- glangdale 6y agoSmith-Waterman seems like it's begging for better algorithms on the CPU side as well. In my experience, these papers often involve disparate amounts of ingenuity and/or "risk tolerance" (i.e. do something that works pragmatically for the inputs you have) on the h/w vs the s/w side. The analogous thing for regex would be, say, extract a literal factor that probably won't appear in the input and suppress the regex execution if that nice even occurs - but only do it on the h/w implementation. Voila, 1000x speedup - on the "nice" input at least. It would be interesting to see what the expected limits are for fair comparisons in extremely hardware-acceleration friendly cases. I don't think GPUs, for example, run 15,000x faster than pure CPU based graphics rendering, but am not sure.