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

随着高性能计算（HPC）系统中核心数量的不断增长，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。容错已成为大型高性能计算系统有效使用的关键技术之一。该项目为选定的线性代数计算开发了高效的算法容错技术，以容忍故障停止和故障继续故障。失败停止故障，即失败的计算崩溃，通常是检查点所容忍的。该项目将检查点从所选线性代数计算的容错中移除，因此检查点和回滚都不需要保护这些计算。故障继续故障，即损坏的计算继续进行，但计算结果不再可信，通常通过在计算结束后检查计算结果来离线容忍。本课题设计了一种新颖的在线容错技术，在计算过程中检测故障继续故障，从而在计算过程中及时停止损坏的计算，从而提高计算效率。

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.