Automatic Risk-Based Selective Redundancy for Fault-Tolerant Task-Parallel HPC Applications
Workshop: ESPM2 2017: Third International Workshop on Extreme Scale Programming Models and Middleware
Authors: Omer Subasi (Pacific Northwest National Laboratory)
Abstract: Silent data corruption (SDC) and fail-stop errors are the most hazardous error types in high-performance computing (HPC) systems. In this study, we present an automatic, efficient and lightweight redundancy mechanism to mitigate both error types. We propose partial task-replication and checkpointing for task-parallel HPC applications to mitigate silent and fail-stop errors. To avoid the prohibitive costs of complete replication, we introduce a lightweight selective replication mechanism. Using a fully automatic and transparent heuristics, we identify and selectively replicate only the reliability-critical tasks based on a risk metric. Our approach detects and corrects around 70% of silent errors with only 5% average performance overhead. Additionally, the performance overhead of the heuristic itself is negligible.
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