The landscape of exascale research: A data-driven literature analysis

S Heldens, P Hijma, BV Werkhoven… - ACM Computing …, 2020 - dl.acm.org
The next generation of supercomputers will break the exascale barrier. Soon we will have
systems capable of at least one quintillion (billion billion) floating-point operations per …

Continuous learning of HPC infrastructure models using big data analytics and in-memory processing tools

F Beneventi, A Bartolini, C Cavazzoni… - Design, Automation & …, 2017 - ieeexplore.ieee.org
Exascale computing represents the next leap in the HPC race. Reaching this level of
performance is subject to several engineering challenges such as energy consumption …

Examon-x: a predictive maintenance framework for automatic monitoring in industrial iot systems

A Borghesi, A Burrello, A Bartolini - IEEE Internet of Things …, 2021 - ieeexplore.ieee.org
In recent years, the Industrial Internet of Things (IIoT) has led to significant steps forward in
many industries, thanks to the exploitation of several technologies, ranging from Big Data …

Energy and power aware job scheduling and resource management: Global survey—initial analysis

M Maiterth, G Koenig, K Pedretti, S Jana… - 2018 IEEE …, 2018 - ieeexplore.ieee.org
This work describes the motivation and methodology of a first-of-its-kind global survey of
HPC centers actively employing Energy and Power Aware Scheduling and Resource …

Paving the way toward energy-aware and automated datacentre

A Bartolini, F Beneventi, A Borghesi… - … Proceedings of the …, 2019 - dl.acm.org
Energy efficiency and datacentre automation are critical targets of the research and
deployment agenda of CINECA and its research partners in the Energy Efficient System …

Production hardware overprovisioning: Real-world performance optimization using an extensible power-aware resource management framework

R Sakamoto, T Cao, M Kondo, K Inoue… - 2017 IEEE …, 2017 - ieeexplore.ieee.org
Limited power budgets will be one of the biggest challenges for deploying future exascale
supercomputers. One of the promising ways to deal with this challenge is hardware over …

Scheduling-based power cap** in high performance computing systems

A Borghesi, A Bartolini, M Lombardi, M Milano… - … Informatics and Systems, 2018 - Elsevier
Supercomputer installed capacity worldwide increased for many years and further growth is
expected in the future. The next goal for high performance computing (HPC) systems is …

Predicting job power consumption based on rjms submission data in hpc systems

T Saillant, JC Weill, M Mougeot - … 2020, Frankfurt/Main, Germany, June 22 …, 2020 - Springer
Power-aware scheduling is a promising solution to the resource usage monitoring of High-
Performance Computing facility electrical power consumption. This kind of solution needs a …

Improving prediction of computational job execution times with machine learning

B Balis, T Lelek, J Bodera, M Grabowski… - Concurrency and …, 2024 - Wiley Online Library
Predicting resource consumption and run time of computational workloads is crucial for
efficient resource allocation, or cost and energy optimization. In this paper, we evaluate …

Data-driven job dispatching in HPC systems

C Galleguillos, A Sîrbu, Z Kiziltan, O Babaoglu… - … , Optimization, and Big …, 2018 - Springer
Abstract As High Performance Computing (HPC) systems get closer to exascale
performance, job dispatching strategies become critical for kee** system utilization high …