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MODEL_MULTI_CORES = True

I created a new virtual environment in ubuntu20 and Python 3.8.10
Then I changed this setting to True and built it with the command below.
python3 setup.py install

I confirmed that Prophet 1.1.2 version was installed in my virtual environment without an error message.

After making all conditions, including the dataset, as identical as possible, I measured the usage of each Core/Thread used by Prophet and how much time spent on computation was reduced.

However, disappointingly, multi-core was not used and the computation time was almost the same.

Did I make a mistake?

Does there seem to be a problem with my environment?

...
cmdstanpy 1.0.4
pystan 2.19.1.1
pandas 1.5.3
prophet 1.1.2

MODEL_MULTI_CORES = True

I created a new virtual environment in ubuntu20 and Python 3.8.10

Then I changed this setting to True and built it with the command below.

python3 setup.py install

I confirmed that Prophet 1.1.2 version was installed in my virtual environment without an error message.

After making all conditions, including the dataset, as identical as possible, I measured the usage of each Core/Thread used by Prophet and how much time spent on computation was reduced.

However, disappointingly, multi-core was not used and the computation time was almost the same.

Did I make a mistake?

Does there seem to be a problem with my environment?

...

cmdstanpy 1.0.4

pystan 2.19.1.1

pandas 1.5.3

prophet 1.1.2

Thanks for checking it out! As of now, only a few functions in Stan utilize opencl and multithreading. So this can create a faster execution time, but will not run the whole model on multiple cores. I made a version that did just that, but the execution time was way worse as it had to copy the data into memory multiple times.

I also made a version that runs 10x faster and uses cuda (30/40 series cards) for some of the functions that do not use opencl. Check it out: https://github.com/StoffAudioLLC/CuProphet