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Issue No. 01 - January (2011 vol. 22)
ISSN: 1045-9219
pp: 69-77
Abhinav Sarje , Iowa State University, Ames
Jaroslaw Zola , Iowa State University, Ames
Srinivas Aluru , Iowa State University, Ames and Indian Institute of Technology Bombay, Mumbai
Direct computation of all pairwise distances or interactions is a fundamental problem that arises in many application areas including particle or atomistic simulations, fluid dynamics, computational electromagnetics, materials science, genomics and systems biology, and clustering and data mining. In this paper, we present methods for performing such pairwise computations efficiently in parallel on Cell processors. This problem is particularly challenging on the Cell processor due to the small sized Local Stores of the Synergistic Processing Elements, the main computational cores of the processor. We present techniques for different variants of this problem including those with large number of entities or when the dimensionality of the information per entity is large. We demonstrate our methods in the context of multiple applications drawn from fluid dynamics, materials science and systems biology, and present detailed experimental results. Our software library is an open source and can be readily used by application scientists to accelerate pairwise computations using Cell accelerators.
Parallel algorithms, computations on matrices, cell broadband engine, pairwise computations, heterogeneous (hybrid) systems, multicore/single-chip multiprocessors.

A. Sarje, S. Aluru and J. Zola, "Accelerating Pairwise Computations on Cell Processors," in IEEE Transactions on Parallel & Distributed Systems, vol. 22, no. , pp. 69-77, 2010.
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