Comments (3)
Hi @chenxf611
In our benchmarks with a 16-core CPU instance with a P100 GPU, we observe a rate of 2.93 ZMW/second for 11kb HiFi read length reads. This isn't far from your 1.622 ZMW/second, and the difference can potentially be explained by a different GPU and/or different read lengths.
So it does not look like you are doing anything out of the ordinary which is making your results slower. When we run DeepConsensus, we horizontally scale across multiple machines.
I understand that the amount of compute time required is the largest pain point for users to run DeepConsensus. We are working on further improvements that we hope will substantially reduce compute for further versions. From DeepConsensus v0.1 to v0.2 there is a ~10x speed improvement, and we are targeting similar magnitudes of improvement for future releases.
from deepconsensus.
Hi @chenxf611 ,
Please see this documentation available with v0.3 release that answers your questions about batch size vs performance: https://github.com/google/deepconsensus/blob/r0.3/docs/yield_metrics.md
With v0.3 you can also adjust the --skip_windows_above
parameter for faster processing and pre-processing with --min-rq 0.88
halves the amount of ZMWs needs to be processed. Hope this helps.
from deepconsensus.
Hi @chenxf611 ,
I'll close this issue now. But feel free to reopen (or open a new one) if you have more quesions.
from deepconsensus.
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from deepconsensus.