google-deepmind / google-deepmind/alphafold
Increased memory usage while folding multiple proteins one after another
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- Python
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Description
I am trying to predict the structures of multiple multimers but I find that if I fold them one after another, the memory consumption increases. For example, folding one multimer consumes about 8GB memory but when I fold 30 multimers one after another it uses about 28 GB memory. Why is that the case? Is there a way to reduce that?
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