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Performance in Windows 10 about orange3 HOT 2 OPEN

mrahmadt avatar mrahmadt commented on August 28, 2024
Performance in Windows 10

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Comments (2)

thocevar avatar thocevar commented on August 28, 2024

My experiments on Windows show that running cross validation or random sampling in Test & Score does not run the threads in parallel utilizing all CPUs.

Random forest and other trivially parallelizable methods (e.g. XGBoost) could be parallelized with the n_jobs parameter even for a single training/prediction call (such as testing on test data) but are not.

The combination of both could be problematic by spawning more threads than there are processors. The only exception that I found is Logistic Regression, which always utilizes all CPUs, but probably on some lower level.

This needs further discussion.

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thocevar avatar thocevar commented on August 28, 2024

Parallelization in Test & Score was intentionally removed in 1f8d008.

The easiest way of re-introducing parallelization would be on the level of individual models (e.g. random forest), where scikit-learn takes care of it (n_jobs=-1).

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