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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迅速提高,庞大的数据集使地理计算更加耗时,尤其是在操作某些复杂算法时。通过利用更多的计算资源,并行计算被视为一种有效的解决方案。稳定可靠的服务在并行计算中扮演着不可替代的角色,尤其是在大规模科学计算中发生错误时。本文提出了一种基于冗余机制的主/从方式实现快速并行重新计算的方法。一旦检测到应用层中的某些错误,则将具有计算错误的原始数据块进一步划分为几个子块,这些子块由尚存的进程同时进行重新计算,以提高故障恢复的效率。采用主进程中的多线程策略来分配数据块,检测错误并同时开始重新计算过程。实验结果表明,所提出的方法能够以更少的额外开销实现更高的性能效率。

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