Publication

Pattern-based Modeling of Multiresilience Solutions for High-Performance Computing

Pattern composition for detection, containment and mitigation for soft and process failure resilience in GMRES solver.

Citation

Rizwan A. Ashraf, Saurabh Hukerikar, and Christian Engelmann, "Pattern-based Modeling of Multiresilience Solutions for High-Performance Computing," In Proceedings of the 2018 ACM/SPEC International Conference on Performance Engineering (ICPE '18), April 9-13, Berlin, Germany.

Abstract

Resiliency is the ability of large-scale high-performance computing (HPC) applications to gracefully handle errors, and recover from failures. In this paper, we propose a pattern-based approach to constructing resilience solutions that handle multiple error modes. Using resilience patterns, we evaluate the performance and reliability characteristics of detection, containment and mitigation techniques for transient errors that cause silent data corruptions and techniques for fail-stop errors that result in process failures. We demonstrate the design and implementation of the multiresilience solution based on patterns instantiated across multiple layers of the system stack. The patterns are integrated to work together to achieve resiliency to different error types in a performance-efficient manner.

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