The development and application of evolutionary algorithms (EAs) and other metaheuristics
for the optimisation of water resources systems has been an active research field for over …

Since the mid-1990s, researchers have been trying to use machine-learning-based
approaches to solve a number of different compiler optimization problems. These …

Topological data analysis offers a rich source of valuable information to study vision
problems. Yet, so far we lack a theoretically sound connection to popular kernel-based …

In recent years, the heterogeneity of both commodity and supercomputers hardware has
increased sharply. Accelerators, such as GPUs or Intel Xeon Phi co-processors, are often …

This paper provides a broad framework for understanding trends in Operational Data
Analytics (ODA) for High-Performance Computing (HPC) facilities. The goal of ODA is to …

Energy consumption is one of the top challenges for achieving the next generation of
supercomputing. Codesign of hardware and software is critical for improving energy …

Exascale systems will require new approaches to performance observation, analysis, and
runtime decision-making to optimize for performance and efficiency. The standard" first …

In the autonomic computing context, the system is perceived as a set of autonomous
elements capable of self-management, where end-users define high-level goals and the …

Automatic parallelization of sequential programs combined with auto-tuning is an alternative
to manual parallelization. With wider research directions and the increased number of …

We present a two-level implementation of an infrastructure that allows performance
maximization under a power-cap on multi-application environments with minimal user …