Salvator Abreu (Universidade de Évora and CENTRIA FCT/UNL) |
Daniel Diaz (Université de Paris 1-Sorbonne) |
Philippe Codognet (JFLI/CNRS and University of Tokyo) |
We explore the use of the Cell Broadband Engine (Cell/BE for short)
for combinatorial optimization applications: we present a parallel version of a constraint-based local search algorithm that has been implemented on a multiprocessor BladeCenter machine with twin Cell/BE processors (total of 16 SPUs per blade). This algorithm was chosen because it fits very well the Cell/BE architecture and requires neither shared memory nor communication between processors, while retaining a compact memory footprint. We study the performance on several large optimization benchmarks and show that this achieves mostly linear time speedups, even sometimes super-linear. This is possible because the parallel implementation might explore simultaneously different parts of the search space and therefore converge faster towards the best sub-space and thus towards a solution. Besides getting speedups, the resulting times exhibit a much smaller variance, which benefits applications where a timely reply is critical. |
ArXived at: https://dx.doi.org/10.4204/EPTCS.5.8 | bibtex | |
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