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Abstract

We will present the current state of the Stan ecosystem, highlight some of the advances that improved the performance of Stan in the past few years, and discuss what is still to come in the not-so-distant future. You will hear about the core modules of Stan, how they all fit together, and how the various interfaces bring that core to life in different ways to make your Stan models run. If your models have been compiling and running faster recently and you were wondering why, we will present the improvements that were made in Stan over the last few years that sped up those pesky gradient evaluations. If you feel that your models are still running slowly, we will provide a few tips on how to identify the computational (non-modeling) reasons why that may be the case, and what are some of the things you can do to speed up computation.

About the speaker

Rok Češnovar is a Stan developer and a PhD student at the University of Ljubljana who is interested in making Bayesian inference faster using parallelism on GPUs and multi-core CPUs. He joined the Stan development team while working on adding GPU support with the team of prof. Štrumbelj at UL, but quickly became interested in almost all aspects of Stan. In addition to working on adding the GPU support, he has co-authored the cmdstanr R package, added profiling for Stan, and implemented the language side of reduce_sum and the new ODE interface. He has also been managing and coordinating Stan & CmdStan releases for the last two years.

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