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Data-Flow reversal and Garbage Collection

Laurent Hascoet 1 
Abstract : Data-Flow reversal is at the heart of Source-Transformation reverse Algorithmic Differentiation (Reverse ST-AD), arguably the most efficient way to obtain gradients of numerical models. However, when the model implementation language uses Garbage Collection (GC), for instance in Java or Python, the notion of address that is needed for Data-Flow reversal disappears. Moreover, GC is asynchronous and does not appear explicitly in the source. We present an extension to the model of Reverse ST-AD suitable for a language with GC. We validate this approach on a Java implementation of a simple Navier-Stokes solver. We compare performance with existing AD tools ADOL-C and Tapenade on an equivalent implementation in C and Fortran.
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Submitted on : Tuesday, July 20, 2021 - 2:44:21 PM
Last modification on : Saturday, June 25, 2022 - 11:51:37 PM
Long-term archiving on: : Thursday, October 21, 2021 - 6:18:46 PM


  • HAL Id : hal-03291836, version 1



Laurent Hascoet. Data-Flow reversal and Garbage Collection. [Research Report] RR-9416, Inria Sophia Antipolis - Méditerranée. 2021, pp.18. ⟨hal-03291836⟩



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