Large-scale applications typically spend a large fraction of their execution time performing
I/O to a parallel storage system. However, with rapid progress in compute and storage …

As high-performance computing infrastructures move towards exascale, the role of resource
and job management systems is more critical now than ever. Simulating batch systems to …

For job allocation decision, current batch schedulers have access to and use only
information on the number of nodes and runtime because it is readily available at …

Untolerated load instruction latencies often have a significant impact on overall program
performance. As one means of mitigating this effect we present an aggressive hardware …

Many contemporary HPC systems expose their jobs to substantial amounts of interference,
leading to significant run-to-run variation. For example, application runtimes on Theta, a …

HPC systems have shifted to burst buffer storage and high radix interconnect topologies in
order to meet the challenges of large-scale, data-intensive scientific computing. Both of …

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 …

Scientific discoveries are increasingly dependent upon the analysis of large volumes of data
from observations and simulations of complex phenomena. Scientists compose the complex …

Large-scale parallel applications are highly data-intensive and perform terabytes of I/O
routinely. Unfortunately, on a large-scale system where multiple applications run …

Burst buffers (BBs) are increasingly exploited in contemporary supercomputers to bridge the
performance gap between compute and storage systems. The design of BBs, particularly the …