The fault tolerance method currently used in High Performance Computing (HPC) is the rollback-recovery method by using checkpoints. This, like any other fault tolerance method, adds an additional energy consumption to that of the execution of the application. The objective of this work is to determine the factors that affect the energy consumption of the computing nodes on homogeneous cluster, when performing checkpoint and restart operations, on SPMD (Single Program Multiple Data) applications. We have focused on the energetic study of compute nodes, contemplating different configurations of hardware and software parameters. We studied the effect of performance states (states P) and power states (states C) of processors, application problem size, checkpoint software (DMTCP) and distributed file system (NFS) configuration. The results analysis allowed to identify opportunities to reduce the energy consumption of checkpoint and restart operations.

翻译：当前高性能计算（HPC）领域采用的容错方法是通过检查点实现回滚恢复。与其它容错方法类似，该方法会在应用程序执行能耗基础上引入额外能耗。本研究旨在确定在运行SPMD（单程序多数据）应用时，影响同构集群计算节点执行检查点与重启操作能耗的关键因素。我们聚焦于计算节点的能耗特性研究，综合考虑硬件与软件参数的不同配置。具体分析了处理器性能状态（P状态）与功耗状态（C状态）、应用问题规模、检查点软件（DMTCP）及分布式文件系统（NFS）配置对能耗的影响。通过结果分析，我们识别出降低检查点与重启操作能耗的潜在优化路径。