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Adaptive executions of hyperbolic block-structured AMR applications on GPU systems

Raghavan, Hari K and Vadhiyar, Sathish S (2015) Adaptive executions of hyperbolic block-structured AMR applications on GPU systems. In: INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS, 29 (2). pp. 135-153.

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Official URL: http://dx.doi.org/10.1177/1094342014545546

Abstract

A block-structured adaptive mesh refinement (AMR) technique has been used to obtain numerical solutions for many scientific applications. Some block-structured AMR approaches have focused on forming patches of non-uniform sizes where the size of a patch can be tuned to the geometry of a region of interest. In this paper, we develop strategies for adaptive execution of block-structured AMR applications on GPUs, for hyperbolic directionally split solvers. While effective hybrid execution strategies exist for applications with uniform patches, our work considers efficient execution of non-uniform patches with different workloads. Our techniques include bin-packing work units to load balance GPU computations, adaptive asynchronism between CPU and GPU executions using a knapsack formulation, and scheduling communications for multi-GPU executions. Our experiments with synthetic and real data, for single-GPU and multi-GPU executions, on Tesla S1070 and Fermi C2070 clusters, show that our strategies result in up to a 3.23 speedup in performance over existing strategies.

Item Type: Journal Article
Additional Information: Copy right for this article belongs to the SAGE PUBLICATIONS LTD, 1 OLIVERS YARD, 55 CITY ROAD, LONDON EC1Y 1SP, ENGLAND
Keywords: Adaptive mesh refinement; GPU executions; dynamic load balancing; asynchronous executions of CPUs and GPUs; coalesced access
Department/Centre: Division of Interdisciplinary Research > Supercomputer Education & Research Centre
Depositing User: Id for Latest eprints
Date Deposited: 22 May 2015 07:09
Last Modified: 22 May 2015 07:09
URI: http://eprints.iisc.ac.in/id/eprint/51546

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