examples/alphafold2.md
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@@ -120,6 +120,14 @@ Memory is going to be an issue with larger protein sizes. The original publicati
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"The memory usage is approximately quadratic in the number of residues, so a 2,500 residue protein involves using unified memory so that we can greatly exceed the memory of a single V100. In our cloud setup, a single V100 is used for computation on a 2,500 residue protein but we requested four GPUs to have sufficient memory."
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+The following environment variable settings may help with larger polypeptide calculations (> 1,200 aa).
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+
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+```
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+TF_FORCE_UNIFIED_MEMORY=1
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+XLA_PYTHON_CLIENT_MEM_FRACTION=0.5
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+XLA_PYTHON_CLIENT_ALLOCATOR=platform
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+```
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+*Thanks Ci Ji Lim at Wisconsin for suggesting and testing these.*
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### pTM scores
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The pTM scores are not calculated using the default model. To get pTM scored models you need to change the model names in the input. We have provided a template wrapper script (https://sbgrid.org//wiki/examples/alphafold2) which you can change to your requirements. To get pTM scores you will need to change the model_name line to "model_1_ptm,model_2_ptm" etc.
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