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I do not notice any performance improvements when using GaussianProcessRegressor on a machine which has 8 cores (16 threads), although i do only use physical cores. So I wonder, is the GaussianProcessRegressor class in sklearn.gaussian_process able to take the advantage of multiple processors/cores/threads?

Current scenario

Time on 4 cores case: 0.57
Time on 8 cores case: 0.56

Not a notable speedup. This time just scope fit_transform over data chunks. So no overhead is timed.

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