Environmental-aware optimization of MPI checkpointing intervals

H. Jitsumoto, Toshio Endo, S. Matsuoka
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Abstract

Fault-tolerance for HPC systems with long-running applications of massive and growing scale is now essential. Although checkpointing with rollback recovery is a popular technique, automated checkpointing is becoming troublesome in a real system, due to the extremely large size of collective application memory. Therefore, automated optimization of the checkpoint interval is essential, but the optimal point depends on hardware failure rates and I/O bandwidth. Our new model and an algorithm, which is an extension of Vaidyapsilas model, solve the problem by taking such parameters into account. Prototype implementation on our fault-tolerant MPI framework ABARIS showed approximately 5.5% improvement over statically user-determined cases.
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MPI检查点间隔的环境感知优化
对于长期运行且规模不断扩大的高性能计算系统来说,容错是必不可少的。虽然带回滚恢复的检查点是一种流行的技术,但是由于应用程序的集体内存非常大,在实际系统中自动检查点变得很麻烦。因此,检查点间隔的自动优化是必要的,但最优点取决于硬件故障率和I/O带宽。我们的新模型和算法是Vaidyapsilas模型的扩展,通过考虑这些参数来解决问题。在我们的容错MPI框架ABARIS上的原型实现比静态用户确定的情况下改进了大约5.5%。
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