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Improvement of the Embarrassingly Parallel Search for Data Centers

机译:尴尬地并行搜索数据中心

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We propose an adaptation of the Embarrassingly Parallel Search (EPS) method for data centers. EPS is a simple but efficient method for parallel solving of CSPs. EPS decomposes the problem in many distinct subproblems which are then solved independently by workers. EPS performed well on multi-cores machines (40), but some issues arise when using more cores in a datacenter. Here, we identify the decomposition as the cause of the degradation and propose a parallel decomposition to address this issue. Thanks to it, EPS gives almost linear speedup and outperforms work stealing by orders of magnitude using the Gecode solver.
机译:我们提出了一种适用于数据中心的尴尬并行搜索(EPS)方法的改编方案。 EPS是用于并行求解CSP的一种简单而有效的方法。 EPS将问题分解为许多不同的子问题,然后由工人独立解决。 EPS在多核计算机上表现良好(40),但是在数据中心中使用更多的核时会出现一些问题。在这里,我们将分解确定为退化的原因,并提出了并行分解来解决此问题。借助它,EPS使用Gecode求解器几乎可以实现线性加速,并比偷窃工作好几个数量级。

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