The high-performance computing I/O stack has been complex due to multiple software
layers, the inter-dependencies among these layers, and the different performance tuning …

Scientific computing workloads at HPC facilities have been shifting from traditional
numerical simulations to AI/ML applications for training and inference while processing and …

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 work highlights the significance of I/O bottlenecks that data-intensive HPC workflows
face in serverless environments-an issue that has been largely overlooked by prior works …

Object cloud storage systems are deployed with diverse applications that have varying
latency service level objectives (SLOs), posting challenges for supporting quality of service …

Manually diagnosing the I/O performance bottleneck for a single application (hereinafter
referred to as the" job level'') is a tedious and error-prone procedure requiring domain …

I/O constitutes a significant portion of most of the application run-time. Spawning many such
applications concurrently on an HPC system leads to severe I/O contention. Thus …

Low and stable latency is a critical key to the success of many services, but variable load
and resource sharing in a modern cloud environment introduces resource contention that in …

Characterizing the temporal I/O behavior of an HPC application is a challenging task, but
informing the system about it can be valuable for techniques such as I/O scheduling, burst …

Abstract As most High Performance Computing (HPC) applications deal with large volumes
of data, I/O performance is of critical importance to optimize application performance …