A Parallel Task-Based Approach to Linear Algebra

Tousimojarad, A. and Vanderbauwhede, W. (2014) A Parallel Task-Based Approach to Linear Algebra. In: IEEE 13th International Symposium on Parallel and Distributed Computing (ISPDC), Marseilles, France, 24-27 Jun 2014, pp. 59-66. ISBN 9781479959181 (doi: 10.1109/ISPDC.2014.11)

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Abstract

Processors with large numbers of cores are becoming commonplace. In order to take advantage of the available resources in these systems, the programming paradigm has to move towards increased parallelism. However, increasing the level of concurrency in the program does not necessarily lead to better performance. Parallel programming models have to provide flexible ways of defining parallel tasks and at the same time, efficiently managing the created tasks. OpenMP is a widely accepted programming model for shared-memory architectures. In this paper we highlight some of the drawbacks in the OpenMP tasking approach, and propose an alternative model based on the Glasgow Parallel Reduction Machine (GPRM) programming framework. As the main focus of this study, we deploy our model to solve a fundamental linear algebra problem, LU factorisation of sparse matrices. We have used the SparseLU benchmark from the BOTS benchmark suite, and compared the results obtained from our model to those of the OpenMP tasking approach. The TILEPro64 system has been used to run the experiments. The results are very promising, not only because of the performance improvement for this particular problem, but also because they verify the task management efficiency, stability, and flexibility of our model, which can be applied to solve problems in future many-core systems.

Item Type:Conference Proceedings
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Vanderbauwhede, Professor Wim and Tousimojarad, Dr Ashkan
Authors: Tousimojarad, A., and Vanderbauwhede, W.
College/School:College of Science and Engineering > School of Computing Science
ISBN:9781479959181
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