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parallelize #36
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@maxcw Thanks for opening the issue, I agree that it would be a nice option to provide parallelism as part of the available options for computation. I believe this is available via numba, the JIT-compilation library that's an option when using PyNomaly. Since parallel computation is an option when using numba, it may be pretty straight-forward to try and test the following implementation, more specifically take this line: Line 560 in 744fa57
In pass the parameter # parallel is some boolean parameter set earlier, e.g.
parallel = True
compute = numba.jit(self._compute_distance_and_neighbor_matrix,
cache=True, parallel=parallel) if self.use_numba else \
self._compute_distance_and_neighbor_matrix I'll mark this as an |
Work on this issue can now be tracked in #43. |
May be helpful to use a tracing tool like pyinstrument to gauge the effect of certain code changes. |
Implemented in the branch |
It would be great if there's an option for embarrassingly parallel computations, especially if all N^2 distances are calculated.
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