Optimizing Hardware Capacity, Utilizing Automatic Differentiation to Efficiently Compute Derivatives in Parallel Programming Models

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A technical paper titled “Scalable Automatic Differentiation of Multiple Parallel Paradigms through Compiler Augmentation” was published by researchers at MIT (CSAIL), Argonne National Lab, and TU Munich. The paper was a Best Paper Finalist and a Best Student Paper winner at SuperComputing 2022.

Find the technical paper here. Published November 2022.

The work “demonstrates how Enzyme optimizes hardware capacity, utilizing automatic differentiation to efficiently compute derivatives in various parallel programming models,” according to this MIT CSAIL news article.

W. Moses, et al., “Scalable Automatic Differentiation of Multiple Parallel Paradigms through Compiler Augmentation,” in 2022 SC22: International Conference for High Performance Computing, Networking, Storage and Analysis (SC) (SC), Dallas, TX, US, 2022 pp. 859-876.



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