As discussed below, the optimal number to pass to threads will vary significantly from model to model. It also demonstrates using bbr::test_threads() to find the ideal value for threads for a particular model. This page shows how to parallelize a single model by using bbr::submit_model(. When using bbr, you can easily parallelize your model via the threads value. 2 Tools usedībr Manage, track, and report modeling activities, through simple R objects, with a user-friendly interface between R and NONMEM®. This page demonstrates basic parallelization using bbr, as well as optimizing parallelization for a given model. This strategy effectively spreads the model execution over multiple CPU cores, so that independent parts of the fitting can be done simultaneously.ībr makes it easy to parallelize your NONMEM models. For large or complex models, it is often useful to utilize parallel computing to make the models complete more quickly.
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