在Cell宽带引擎上求解约束问题的并行局部搜索（初步结果）
Parallel local search for solving Constraint Problems on the Cell Broadband Engine (Preliminary Results)
摘要：
我们探讨了使用的细胞宽带引擎（细胞/BE为短）的组合优化的应用：我们提出了一个并行版本的基于约束的本地搜索算法，已实施的多处理器BladeCenter机与双细胞/BE处理器（共16个SPU每个刀片）。之所以选择这种算法，是因为它非常适合Cell/BE架构，既不需要共享内存，也不需要处理器之间的通信，同时保留了紧凑的内存占用。我们研究了几个大型优化基准的性能，并表明这主要是线性时间加速，甚至有时超线性。这是可能的，因为并行实现可以同时探索搜索空间的不同部分，因此更快地收敛到最佳子空间，从而收敛到解。除了获得加速之外，结果时间显示出更小的差异，这有利于及时回复至关重要的应用程序。
英文摘要：
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.
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