A Foundation for the Accurate Prediction of the Soft Error Vulnerability of Scientific Applications
Understanding the soft error vulnerability of supercomputer applications is critical as these systems are using ever larger numbers of devices that have decreasing feature sizes and, thus, increasing frequency of soft errors. As many large scale parallel scientific applications use BLAS and LAPACK linear algebra routines, the soft error vulnerability of these methods constitutes a large fraction of the applications overall vulnerability. This paper analyzes the vulnerability of these routines to soft errors by characterizing how their outputs are affected by injected errors and by evaluating several techniques for predicting how errors propagate from the input to the output of each routine. The resulting error profiles can be used to understand the fault vulnerability of full applications that use these routines.
- Research Organization:
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- W-7405-ENG-48
- OSTI ID:
- 951170
- Report Number(s):
- LLNL-CONF-410635; TRN: US200911%%364
- Resource Relation:
- Conference: Presented at: IEEE Workshop on Silicon Errors in Logic - System Effects, Stanford, CA, United States, Mar 24 - Mar 25, 2009
- Country of Publication:
- United States
- Language:
- English
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