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Large array decomposition for parallel processing by array base shifting.

机译:大数组分解,用于通过数组基移进行并行处理。

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The processing of large arrays on parallel systems has many applications. One of these is the solution of partial differential equations using the iterative calculation approach. This method is very computationally intensive, and, depending on the method of partitioning and computation can be very communication intensive. The last definitive work on this subject was done in 1991. The methods now commonly used need to be re-examined to see if there is a method of segmentation, computation and communication that can speed up such a solution on emerging popular MIMD and clustered systems by a significant factor. If so that method could be a large contribution to the present and future use of computers in these problems.; In array segmentation the problem of data communications arises at the boundaries of the segments. Values that must be used in calculation are in different machines and must be accessed to complete the calculations. The conventional approach is to exchange boundary values whenever they are needed, resulting in a high volume of short-length communications. The alternative, developed here, is to do all of the calculations in one segment until no further calculations are possible, then exchange a large piece of the original segment. This has the effect of decreasing the communications volume and increasing the average message length. In parallel machines with slow communications set-up, that results in a solution speed up of better than 3 to 1 and could result in a better than 5 to 1 speedup on clustered systems.
机译:在并行系统上处理大型阵列有许多应用。其中之一是使用迭代计算方法求解偏微分方程。此方法的计算量很大,并且取决于分区和计算的方法,可能会非常消耗通信量。关于该主题的最后一次确定性工作是在1991年完成的。现在需要重新检查现在常用的方法,以查看是否存在可以加快新兴新兴MIMD和集群系统的解决方案速度的分段,计算和通信方法。一个重要的因素。如果是这样的话,那么这些方法可能会对当前和将来使用计算机解决这些问题做出很大贡献。在阵列分段中,数据通信的问题出现在分段的边界处。必须在计算中使用的值在不同的计算机中,并且必须访问这些值才能完成计算。常规方法是在需要边界值时交换边界值,从而导致大量的短长度通信。在此开发的另一种方法是,在一个网段中进行所有计算,直到无法进行进一步的计算,然后交换大块原始网段。这具有减小通信量和增加平均消息长度的效果。在通信设置较慢的并行机中,解决方案的速度提高了3:1以上,而集群系统的速度提高了5:1以上。

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