A novel fault-tolerant parallel algorithm

  • Authors:
  • Panfeng Wang;Yunfei Du;Hongyi Fu;Haifang Zhou;Xuejun Yang;Wenjing Yang

  • Affiliations:
  • National Laboratory for Paralleling and Distributed Processing, College of Computer, National University of Defense Technology, Changsha, Hunan, China;National Laboratory for Paralleling and Distributed Processing, College of Computer, National University of Defense Technology, Changsha, Hunan, China;National Laboratory for Paralleling and Distributed Processing, College of Computer, National University of Defense Technology, Changsha, Hunan, China;National Laboratory for Paralleling and Distributed Processing, College of Computer, National University of Defense Technology, Changsha, Hunan, China;National Laboratory for Paralleling and Distributed Processing, College of Computer, National University of Defense Technology, Changsha, Hunan, China;National Laboratory for Paralleling and Distributed Processing, College of Computer, National University of Defense Technology, Changsha, Hunan, China

  • Venue:
  • APPT'07 Proceedings of the 7th international conference on Advanced parallel processing technologies
  • Year:
  • 2007

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Abstract

The mean-time-between-failure of current high-performance computer systems is much shorter than the running times of many computational applications, whereas those applications are the main workload for those systems. Currently, checkpoint/restart is the most commonly used scheme for such applications to tolerate hardware failures. But this scheme has its performance limitation when the number of processors becomes much larger. In this paper, we propose a novel fault-tolerant parallel algorithm FPAPR. First, we introduce the basic idea of FPAPR. Second, we specify the details of how to implement a FPAPR program by using two NPB kernels as examples. Third, we theoretically analyze the overhead of FPAPR, and find out that the overhead of FPAPR decreases with the increase of the number of processors. At last, the experimental results on a 512-CPU cluster show the overhead introduced by the algorithm is very small.