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Approximating a Multi-Grid Solver

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10.1109/PMBS.2018.8641651
 
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hdl:2117/133927

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Le Fèvre, Valentin
Bautista-Gomez, Leonardo
Unsal, Osman
Casas, MarcMés informació
Document typeConference lecture
Defense date2019-02-14
PublisherIEEE
Rights accessOpen Access
Attribution-NonCommercial-NoDerivs 3.0 Spain
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain
ProjectDURO - DURO: Deep-memory Ubiquity, Reliability and Optimization (EC-H2020-708566)
Abstract
Multi-grid methods are numerical algorithms used in parallel and distributed processing. The main idea of multigrid solvers is to speedup the convergence of an iterative method by reducing the problem to a coarser grid a number of times. Multi-grid methods are widely exploited in many application domains, thus it is important to improve their performance and energy efficiency. This paper aims to reach this objective based on the following observation: Given that the intermediary steps do not require full accuracy, it is possible to save time and energy by reducing precision during some steps while keeping the final result within the targeted accuracy. To achieve this goal, we first introduce a cycle shape different from the classic V-cycle used in multi-grid solvers. Then, we propose to dynamically change the floating-point precision used during runtime according to the accuracy needed for each intermediary step. Our evaluation considering a state-of-the-art multi-grid solver implementation demonstrates that it is possible to trade temporary precision for time to completion without hurting the quality of the final result. In particular, we are able to reach the same accuracy results as with full double-precision while gaining between 15% and 30% execution time improvement.
CitationLe Fèvre, V. [et al.]. Approximating a Multi-Grid Solver. A: "2018 IEEE/ACM Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems (PMBS)". IEEE, 2019, p. 97-107. 
URIhttp://hdl.handle.net/2117/133927
DOI10.1109/PMBS.2018.8641651
ISBN978-1-7281-0182-8
Publisher versionhttps://ieeexplore.ieee.org/document/8641651
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  • Computer Sciences - Ponències/Comunicacions de congressos [459]
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