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Performance Analysis for Fast Parallel Recomputing Algorithm under DTA

机译:DTA下快速并行重新计算算法的性能分析

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摘要

With the rapid increasing of spatial data resolution, the huge volume of datasets makes the geo-computation more time-consuming especially in operating some complex algorithms. Parallel computing is regarded as an efficient solution by utilizing more computing resource. The stable and credible services play an irreplaceable role in parallel computing, especially when an error occurs in the large-scale science computing. In this paper, a master/slave approach of implementing the fast parallel recomputing is proposed based on redundancy mechanism. Once some errors in application layer are detected, the original data block with computation errors is further partitioned into several sub-blocks which are recomputed by the surviving processes concurrently to improve the efficiency of failure recovery. The multi-thread strategy in main process is adopted to distribute data block, detect errors and start recomputing procedure concurrently. The experimental results show that the proposed method can achieve better performance efficiency with fewer additional overhead.
机译:随着空间数据分辨率的快速增加,大量的数据集使得地理计算更耗时,特别是在操作一些复杂的算法时。并行计算通过利用更多计算资源被视为有效的解决方案。稳定且可信的服务在并行计算中发挥着不可替代的作用,特别是当大规模的科学计算中发生错误时。本文基于冗余机制提出了一种实现快速并行重新计算的主/从方法。一旦检测到应用层中的某些错误,就具有计算错误的原始数据块进一步划分为几个子块,该块被幸存的过程同时重新计算以提高故​​障恢复的效率。采用主要过程中的多线程策略分发数据块,检测错误并同时启动重新计算过程。实验结果表明,该方法可以通过较少的额外开销来实现更好的性能效率。

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