High-performance computing relies on performance-oriented infrastructures with access to
powerful computing resources to complete tasks that contribute to solve complex problems …

The increasing complexity of modern high-performance computing (HPC) systems
necessitates the introduction of automated and data-driven methodologies to support system …

Digital twins are an excellent tool to model, visualize, and simulate complex systems, to
understand and optimize their operation. In this work, we present the technical challenges of …

Performance variations caused by anomalies in modern High Performance Computing
(HPC) systems lead to decreased efficiency, impaired application performance, and …

In this paper, we explore the use of Graph Neural Networks (GNNs) for anomaly anticipation
in high performance computing (HPC) systems. We propose a GNN-based approach that …

At the core of the predictive analytics applied to High Performance Computing (HPC), the
most prominent tasks are the prediction of job runtimes and the prediction of job queue …

The new open and royalty-free RISC-V ISA is attracting interest across the whole computing
continuum, from microcontrollers to supercomputers. High-performance RISC-V processors …

Compute nodes in modern HPC systems are growing in size and their hardware has
become ever more diverse. Still, many HPC centers allocate the resources of full nodes …

Decision-making is the process of selecting a course of action from several alternatives on
the basis of preferences, values and available information. As decisions become …

Automated and data-driven methodologies are being introduced to assist system
administrators in managing increasingly complex modern HPC systems. Anomaly detection …