Today's high-performance computing (HPC) platforms are still dominated by batch jobs.
Accordingly, effective batch job scheduling is crucial to obtain high system efficiency …

Machine/deep learning models have been widely adopted to predict the configuration
performance of software systems. However, a crucial yet unaddressed challenge is how to …

This work seeks to advance the state of the art in HPC I/O performance analysis and
interpretation. In particular, we demonstrate effective techniques to:(1) model output …

Parallel file systems are at the core of HPC I/O infrastructures. Those systems minimize the
I/O time of applications by separating files into fixed-size chunks and distributing them …

Large-scale high performance computing (HPC) systems typically consist of many
thousands of CPUs and storage units used by hundreds to thousands of users …

In high-performance computing (HPC), scientific applications often manage a massive
amount of data using I/O libraries. These libraries provide convenient data model …

I/O bandwidth is a critical resource in an HPC cluster. As with all shared resources, its
availability is impacted significantly by the users and the applications they execute. Without …

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 …

Large-scale high performance computing (HPC) systems typically consist of many
thousands of CPUs and storage units used by hundreds to thousands of users …

In high performance computing architectures, the I/O forwarding technique is often used to
alleviate contention in the access to the shared parallel file system servers. Intermediate I/O …