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Either parallelize calls from within R, or add option in REST API to run model in parallel on server
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We should add 4 arguments for parallelization:
1. One concerning parallelization of the predictions method (which is passed to prediction_vector)
2. One for parallelization of the sampling method…
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Jake & Paul - I've added a jupyter notebook showing how to use the multithreading package in python.
I recommend the outline of the functions to look something like:
1) Splitting function (paral…
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Just curious if parallelization with joblib or dask is in the works. Seems like there is a lot of room for simple parallelization.
Thanks,
Amir
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Eventually we will have too much data to run some of these plots on one processor. We should start thinking about ways to parallelize a lot of these tests.
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Have you looked into parallelizing it? I could not get it to run on my AWS GPU because I had problems with Tensorflow-GPU and CUDA, so I have it running now on my AWS CPU server. But it is slow. I wou…
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Thanks a lot for your work!
Do you have any plan to implement a multiprocessing function (like `n_jobs` in scikit-learn)?
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You can start Julia to use multiple local processors (aka workers) at once by `julia -p 8` where 8 is the number of workers.
But what I'm unclear about is if an update to the code is necessary to sp…
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