HPC workload analysis and resource consumption characteristics are the key to driving
better operation practices, system procurement decisions, and designing effective resource …

The increasing complexity of HPC systems has introduced new sources of variability, which
can contribute to significant differences in run-to-run performance of applications. With …

Interference between jobs competing for network bandwidth on a fat-tree cluster can cause
significant variability and degradation in performance. These performance issues can be …

The de-facto standard topology for modern HPC systems and data-centers are Folded Clos
networks, commonly known as Fat-Trees. The number of network endpoints in these …

The era of extremely heterogeneous supercomputing brings with itself the devil of increased
performance variation and reduced reproducibility. There is a lack of understanding in the …

Scalable management of user workloads on large-scale supercomputers remains a
challenge due to the tradeoff between capturing adequate detail for analysis from various …

Resource sharing with its implied mutual interference has been considered a major concern
for running applications of multiple tenants in shared cloud datacenters. Besides its security …

Identifying a suitable network topology and deciding its optimal configuration parameters are
critical aspects of the overall HPC system design, procurement and installation process …

Methods and systems for throttling per-node network bandwidths over time to maximize the
aggregate bandwidth of a distributed cluster of nodes without exceeding a global bandwidth …

Methods and systems for identifying a set of disks within a cluster and then storing a plurality
of data chunks into the set of disks such that the placement of the plurality of data chunks …