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I've run the CLAM package with most of the code unchanged
(except for the fix relating to score2percentile:
def score2percentile(score, ref):
percentile = percentileofscore(ref.squeeze(), score.squeeze())
return percentile)
currently, without changing the settings in the config file,
with a v100 and 140gb ram, it takes around ~45-60 min to process a heatmap for 1 svs file.
I've looked at the other discussions and changing vis_level seems to reduce the amount of memory required.
However, are there any other tips regarding speeding up heatmap creation? Does moving the svs files onto an SSD greatly impact the speed of the heatmaps generated?
I would like to create heatmaps for ~200 svs files, which would take ~200 hours.
any suggestions or input would be greatly appreciated!
The text was updated successfully, but these errors were encountered:
Hi,
I've run the CLAM package with most of the code unchanged
(except for the fix relating to score2percentile:
def score2percentile(score, ref):
percentile = percentileofscore(ref.squeeze(), score.squeeze())
return percentile)
currently, without changing the settings in the config file,
with a v100 and 140gb ram, it takes around ~45-60 min to process a heatmap for 1 svs file.
I've looked at the other discussions and changing vis_level seems to reduce the amount of memory required.
However, are there any other tips regarding speeding up heatmap creation? Does moving the svs files onto an SSD greatly impact the speed of the heatmaps generated?
I would like to create heatmaps for ~200 svs files, which would take ~200 hours.
any suggestions or input would be greatly appreciated!
The text was updated successfully, but these errors were encountered: