This work evaluates performance variability in the Cray Aries dragonfly network and characterizes its impact on MPI Allreduce. The execution time of Allreduce is limited by the performance of the slowest participating process, which can vary by more than an order of magnitude. We utilize counters from the network routers to provide a better understanding of how competing workloads can influence performance. Specifically, we examine the relationships between message size, process counts, Aries counters and the Allreduce communication-time. Our results suggest that competing traffic from other jobs can significantly impact performance on the Aries Dragonfly Network. Furthermore, we show that Aries network counters are a valuable tool, explaining up to 70% of the performance variability for our experiments on a large-scale production system.

Nonvolatile processors (NVPs) preserve run-time information when power failure occurs by utilizing nonvolatile memory technologies. This feature enables NVPs to make forward progress continuously under intermittent power supply in energy harvesting systems. This paper builds a gem5 based NVP simulator named NVPsim, which is validated against measured results of a fabricated prototype with reasonable error rate. Furthermore, to demonstrate the capability of NVPsim for architecture exploration, we evaluated performance and energy consumption of different NVP designs varying in the choice of nonvolatile memory for on-chip caches, the backup strategy and the energy buffer size. Experimental results indicate that nvSRAM outperforms other types of nonvolatile memory as the on-chip cache for energy harvesting systems.