Supercomputers are the most powerful computing machines available to society. They play
a central role in economic, industrial, and societal development. While they are used by …

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

High Performance Computing (HPC) systems are complex machines that need to be
operated at their maximum potential to recoup their investment cost and to mitigate their …

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 …

The main limitation of applying predictive tools to large-scale supercomputers is the
complexity of deploying Artificial Intelligence (AI) services in production and modeling …

Anomaly detection across critical infrastructures is not only a key step towards detecting
threats but also gives early warnings of the likelihood of potential cyber-attacks, faults, or …

Anomaly detection in distributed systems such as High-Performance Computing (HPC)
clusters is vital for early fault detection, performance optimisation, security monitoring …

Supercomputers are highly sophisticated computing systems designed to handle complex
and computationally intensive tasks. Despite their tremendous efficiency, performance …

This work critically examines several approaches to temperature prediction for High-
Performance Computing (HPC) systems, focusing on component-level and holistic models …

Modeling and understanding an expensive next-generation data center operating at a
sustainable exascale performance remains a challenge yet to solve. The paper presents the …