Arpra: an arbitrary precision range analysis library

Turner, James Paul and Nowotny, Thomas (2021) Arpra: an arbitrary precision range analysis library. Frontiers in Neuroinformatics, 15. a632729 1-21. ISSN 1662-5196

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Abstract

Motivated by the challenge of investigating the reproducibility of spiking neural network simulations, we have developed the Arpra library: an open source C library for arbitrary precision range analysis based on the mixed Interval Arithmetic (IA)/Affine Arithmetic (AA) method. Arpra builds on this method by implementing a novel mixed trimmed IA/AA, in which the error terms of AA ranges are minimised using information from IA ranges. Overhead rounding error is minimised by computing intermediate values as extended precision variables using the MPFR library. This optimisation is most useful in cases where the ratio of overhead error to range width is high. Three novel affine term reduction strategies improve memory efficiency by merging affine terms of lesser significance. We also investigate the viability of using mixed trimmed IA/AA and other AA methods for studying reproducibility in unstable spiking neural network simulations.

Item Type: Article
Schools and Departments: School of Engineering and Informatics > Informatics
SWORD Depositor: Mx Elements Account
Depositing User: Mx Elements Account
Date Deposited: 14 Jun 2021 08:29
Last Modified: 28 Feb 2022 16:29
URI: http://sro.sussex.ac.uk/id/eprint/99764

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Project NameSussex Project NumberFunderFunder Ref
Brains on Board: Neuromorphic Control of Flying RobotsG1980EPSRC-ENGINEERING & PHYSICAL SCIENCES RESEARCH COUNCILEP/P006094/1
HBP SGA3 - Human Brain Project Specific Grant Agreement 3G2945EUROPEAN UNION945539
Human Brain Project Specific Grant Agreement 2 — HBP SGA2G2410EUROPEAN UNION785907