Many extreme scale scientific applications have workloads comprised of a large number of
individual high-performance tasks. The Pilot abstraction decouples workload specification …

Monitoring and analyzing a wide range of I/O activities in an HPC cluster is important in
maintaining mission-critical performance in a large-scale, multi-user, parallel storage …

This paper presents a comprehensive investigation on optimizing I/O performance in the
access to distributed I/O resources in high-performance computing (HPC) environments. I/O …

HPC datacenters offer a backbone to the modern digital society. Increasingly, they run
Machine Learning (ML) jobs next to generic, compute-intensive workloads, supporting …

Modern science and engineering computing environments often feature storage systems of
different types, from parallel file systems in high-performance computing centers to object …

Modern applications are highly data-intensive, leading to the well-known I/O bottleneck
problem. Scientists have proposed the placement of fast intermediate storage resources …

Users' limited understanding of the storage system architecture prevents them from fully
utilizing the parallel I/O capability of the storage system, leading to a negative impact on the …

Supercomputer scheduling policies commonly result in many transient idle nodes, a
phenomenon that is only partially alleviated by backfill scheduling methods that promote …

The demand for high-performance computing (HPC) resources in computing fields such as
machine learning has increased significantly in recent years. Computing power has been …

Research has become increasingly reliant on software, serving as the driving force behind
bioinformatics, high performance computing, physics, machine learning and artificial …