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Question Regarding precompute_conversion Runtime and Multi-threading #1
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Hi Qianhui, Thank you for your interest! It is indeed a very slow process as currently implemented. There is a parallelized implementation, BUT it is very much not resource friendly. When I wrote this I expected the precompute_conversion would be run very rarely. So I allowed it be be pretty slow. I am actively working on improving the speed and efficiency. I am hopeful i'll have a much faster release this coming week. Best, |
Hi Juan, that's very helpful. I think the HPC I'm currently using has a time limit of one week per job. I'll try setting the longest allowed time so the job can finish. Thank you so much! Best, |
Ok. So it is much much faster now and less resource intensive. Both the pre-computation and later the processing of real data. Should now take less than a day. I am putting together the updates and new docs. What graph are you using exactly? |
Cool, thank you so much! I am using hprc_v1_1_mc_chm13.gfa graph genome for now. I noticed that writing to disk becomes slower after reaching 5GB. Could this be due to accumulated memory (RAM) usage? |
Ok. So for the sake of practicality as I am updating the docs. I went ahead and ran the process on hprc_v1_1_mc_chm13. This way you can use that directly without having to regenerate it yourself. I've updated the docs documenting how to generate files needed to do surject real results it and the new method for how to run that surjection. I am setting up the FTP so you can download the essential file. Let me know if the new docs make sense to you |
There are some hangups on how best to host these files. So while we work that out, if you could email me I will send you a box link directly to where you can access the databases files you need. My email is on the read me page at the bottm |
Great, that would be very helpful. I'm sending you an email now. Thank you! |
Hello, I have been running precompute_conversion for CHM13, but it has taken more than 3 days and has only produced about 4GB of output so far. I expect the total output to be around 30GB.
Is there any parameter available to enable multi-threading for this function?
Thank you so much.
Best regards,
Qianhui
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