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Analysis here suggests that the queue size is too small to be effective for parallel processing. It's a bit hard to follow the code path, but it seems to be capped at 8*num_threads in the case of LDA. While it isn't obvious what a good default is, this being hard coded seems to be causing issues. It should be a kwarg from infer so users can tune inference.
The text was updated successfully, but these errors were encountered:
For your information: I did manage to compile tomotopy with your proposed changes, however this did not improve the slow inference.
I don't have precise timings or any nice graphs. but it felt as it still took as long as before. I did change 8 to 128. No idea if that is actually a good value, but it didn't seem to change anything anyways, as the CPU was still under high load but not doing much, as it didn't got warm, so I guess it still did spend most of its time waiting …
Analysis here suggests that the queue size is too small to be effective for parallel processing. It's a bit hard to follow the code path, but it seems to be capped at
8*num_threads
in the case of LDA. While it isn't obvious what a good default is, this being hard coded seems to be causing issues. It should be a kwarg frominfer
so users can tune inference.The text was updated successfully, but these errors were encountered: