English

EasyCrash: Exploring Non-Volatility of Non-Volatile Memory for High Performance Computing Under Failures

Performance 2019-06-25 v1

Abstract

Emerging non-volatile memory (NVM) is promising for building future HPC. Leveraging the non-volatility of NVM as main memory, we can restart the application using data objects remaining on NVM when the application crashes. This paper explores this solution to handle HPC under failures, based on the observation that many HPC applications have good enough intrinsic fault tolerance. To improve the possibility of successful recomputation with correct outcomes and ignorable performance loss, we introduce EasyCrash, a framework to decide how to selectively persist application data objects during application execution. Our evaluation shows that EasyCrash transforms 54% of crashes that cannot correctly recompute into the correct computation while incurring a negligible performance overhead (1.5% on average). Using EasyCrash and application intrinsic fault tolerance, 82% of crashes can successfully recompute. When EasyCrash is used with a traditional checkpoint scheme, it enables up to 24% improvement (15% on average) in system efficiency.

Keywords

Cite

@article{arxiv.1906.10081,
  title  = {EasyCrash: Exploring Non-Volatility of Non-Volatile Memory for High Performance Computing Under Failures},
  author = {Jie Ren and Kai Wu and Dong Li},
  journal= {arXiv preprint arXiv:1906.10081},
  year   = {2019}
}

Comments

15 pages, 12 figures

R2 v1 2026-06-23T10:02:11.080Z