Abstract
Understanding workload characteristics is critical
for optimizing and improving the performance of current systems
and software, and architecting new storage systems based on
observed workload patterns. In this paper, we characterize the
scientific workloads of the world’s fastest HPC (High Performance
Computing) storage cluster, Spider, at the Oak Ridge
Leadership Computing Facility (OLCF). Spider provides an
aggregate bandwidth of over 240 GB/s with over 10 petabytes of
RAID 6 formatted capacity. OLCFs flagship petascale simulation
platform, Jaguar, and other large HPC clusters, in total over 250
thousands compute cores, depend on Spider for their I/O needs.
We characterize the system utilization, the demands of reads
and writes, idle time, and the distribution of read requests to
write requests for the storage system observed over a period of 6
months. From this study we develop synthesized workloads and
we show that the read and write I/O bandwidth usage as well
as the inter-arrival time of requests can be modeled as a Pareto
distribution.