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Massively Parallel Constraint Programming for Supercomputers: Challenges and Initial Results

机译:超级计算机的大规模并行约束编程:挑战和初步结果

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In this paper we present initial results for implementing a constraint programming solver on a massively parallel supercomputer where coordination between processing elements is achieved through message passing. Previous work on message passing based constraint programming has been targeted towards clusters of computers (see [1,2] for some examples). Our target hardware platform is the IBM Blue Gene supercomputer. Blue Gene is designed to use a large number of relatively slow (800MHz) processors in order to achieve lower power consumption, compared to other supercomputing platforms. Blue Gene/P, the second generation of Blue Gene, can run continuously at 1 PFLOPS and can be scaled to 884,736-processors to achieve 3 PFLOPS performance. We present a dynamic scheme for allocating sub-problems to processors in a parallel, limited discrepancy tree search [3]. We evaluate this parallelization scheme on resource constrained project scheduling problems from PSPLIB [4].
机译:在本文中,我们介绍了在大规模并行超级计算机上实施约束编程求解器的初步结果,该处理机之间的协调是通过消息传递实现的。以前基于消息传递的约束编程的工作已针对计算机集群(有关示例,请参见[1,2])。我们的目标硬件平台是IBM Blue Gene超级计算机。与其他超级计算平台相比,Blue Gene设计为使用大量相对较慢的(800MHz)处理器,以实现更低的功耗。 Blue Gene / P是Blue Gene的第二代产品,可以以1 PFLOPS的速度连续运行,并可扩展至884,736个处理器,以实现3 PFLOPS的性能。我们提出了一种在并行,有限差异树搜索中为处理器分配子问题的动态方案[3]。我们从PSPLIB [4]对资源受限的项目调度问题评估了这种并行化方案。

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