Zuricho / ParallelFold

Modified version of Alphafold to divide CPU part (MSA and template searching) and GPU part. This can accelerate Alphafold when predicting multiple structures
https://parafold.sjtu.edu.cn
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GPU computing is slow #19

Open chenshixinnb opened 2 years ago

chenshixinnb commented 2 years ago

Same multimer sequence,two chains,in total 646AA.

Use ParallelFold,CPU phase use 1h33min,GPU phase use 5h30min,generate five models.command: -p multimer -m model_1_multimer,model_2_multimer,model_3_multimer,model_4_multimer,model_5_multimer.

Use ParallelFold,CPU phase use 1h27min,GPU phase use 1h25min,generate one models.command: -p multimer -m model_1_multimer

Use Alphafold Docker,total use 2h20min,generate five models

Zuricho commented 2 years ago

When using multimer models, sometimes a collapsed structure may cause the running time and amber relaxation time very long. Did you look into the predicted computed structure? Is it correct or reasonable?

chenshixinnb commented 2 years ago

How can I determine if the calculation structure is reasonable?Do you have any relevant references? Thanks.

Zuricho commented 2 years ago

you can just look at the output structure, is it looked reasonable? like does it have reasonable secondary structure? also, you can check which step took longest time? is it inference or relaxation?