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FT-ISort: Efficient Fault Tolerance for Introsort

  • Sihuan Li
  • , Hongbo Li
  • , Xin Liang
  • , Jieyang Chen
  • , Elisabeth Giem
  • , Kaiming Ouyang

Research output: Contribution to journal › Article › peer-review

Abstract

Introspective sorting is a ubiquitous sorting algorithm which underlies many large scale distributed systems. Hardware-mediated soft errors can result in comparison and memory errors, and thus cause introsort to generate incorrect output, which in turn disrupts systems built upon introsort; hence, it is critical to incorporate fault tolerance capability within introsort. This paper proposes the first theoretically-sound, practical fault tolerant introsort with negligible overhead: FT-iSort. To tolerate comparison errors, we use minimal TMR protection via exploiting the properties of the effects of soft errors on introsort. This algorithm-based selective protection incurs far less overhead than nave TMR protection designed to protect an entire application. To tolerate memory errors that escape DRAM error correcting code, we propose XOR-based re-execution. We incorporate our fault tolerance method into the well-known parallel sorting implementation HykSort, and we find that fault tolerant HykSort incurs negligible overhead and obtains nearly the same scalability as unprotected HykSort.

Keywords

  • Algorithm based Fault Tolerance
  • Comparison Errors
  • Fault Tolerant Sorting
  • Introsort
  • Soft Errors

Disciplines

  • Computer Sciences

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