SHF: Small: FTLA: Fault Tolerant Linear Algebra Software for Massively Parallel Architectures

随着高性能计算(HPC)系统中核心数量的持续增长，大型HPC系统的平均故障时间(MTTF)正变得比许多HPC应用程序的执行时间更短。容错正在成为大型HPC系统有效使用的关键技术之一，该项目开发了用于选择线性代数计算的高效算法容错技术，以同时容忍故障-停止和故障-继续故障。故障停止故障，即失败的计算崩溃，通常是检查点可以容忍的。该项目从选定的线性代数计算的容错中删除了检查点，因此不需要检查点或回滚来保护这些计算。失败-继续失败，即被破坏的计算继续取得进展，但计算结果不再可信，通常通过在计算完成后检查计算结果来离线容忍。该项目设计了新颖的在线容错技术来检测计算中途的失败-继续故障，从而通过在计算中途及时停止被破坏的计算来获得更高的效率。

As the number of cores in high performance computing (HPC) systems continues to grow, the mean-time-to-failure (MTTF) for large HPC systems is becoming shorter than the execution time of many HPC applications. Fault tolerance is becoming one of the critical techniques for the effective use of large HPC systems.This project develops highly efficient algorithmic fault tolerance techniques for selected linear algebra computations to tolerate both fail-stop and fail-continue failures. Fail-stop failures, where the failed computation crashes, are often tolerated by checkpoint. This project removes checkpoint from fault tolerance for selected linear algebra computations so that neither checkpoint nor rollback is necessary for the protection of these computations. Fail-continue failures, where the corrupted computation continues to make progress but the computation results cannot be trusted any more, are usually tolerated offline by checking the computation results after the computation finishes. This project designs novel online fault tolerance techniques to detect fail-continue failures in the middle of the computation so that better efficiency can be achieved by stopping the corrupted computations in the middle of the computation in a timely manner.