| タイトル | Parallel Computing Strategies for Irregular Algorithms |
| 本文（外部サイト） | http://hdl.handle.net/2060/20020090950 |
| 著者（英） | Oliker, Leonid; Biswas, Rupak; Biegel, Bryan; Shan, Hongzhang |
| 著者所属（英） | NASA Ames Research Center |
| 発行日 | 2002-09-01 |
| 言語 | eng |
| 内容記述 | Parallel computing promises several orders of magnitude increase in our ability to solve realistic computationally-intensive problems, but relies on their efficient mapping and execution on large-scale multiprocessor architectures. Unfortunately, many important applications are irregular and dynamic in nature, making their effective parallel implementation a daunting task. Moreover, with the proliferation of parallel architectures and programming paradigms, the typical scientist is faced with a plethora of questions that must be answered in order to obtain an acceptable parallel implementation of the solution algorithm. In this paper, we consider three representative irregular applications: unstructured remeshing, sparse matrix computations, and N-body problems, and parallelize them using various popular programming paradigms on a wide spectrum of computer platforms ranging from state-of-the-art supercomputers to PC clusters. We present the underlying problems, the solution algorithms, and the parallel implementation strategies. Smart load-balancing, partitioning, and ordering techniques are used to enhance parallel performance. Overall results demonstrate the complexity of efficiently parallelizing irregular algorithms. |
| NASA分類 | Computer Programming and Software |
| 権利 | Copyright, Distribution as joint owner in the copyright |
| URI | https://repository.exst.jaxa.jp/dspace/handle/a-is/223935 |
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