What is known as energy-aware computing includes taking into account many different
variables and parameters when designing an application, which makes it necessary to focus …

Evolutionary Algorithms (EAs) are routinely applied to solve a large set of optimization
problems. Traditionally, their performance in solving those problems is analyzed using the …

Recently, energy efficiency has gained attention from researchers interested in optimizing
computing resources. Solving real-world problems using optimization techniques (such as …

The present trend in the development of computer architectures that offer improvements in
both performance and energy efficiency has provided clusters with interconnected nodes …

Abstract When Evolutionary Algorithms (EAs) are applied to optimization problems, two main
measures are taken into account to understand their performance: fitness quality and …

In recent years, the energy-awareness has become one of the most interesting areas in our
environmentally conscious society. Algorithm designers have been part of this, particularly …

Heterogeneous CPU-GPU platforms include resources to benefit from different kinds of
parallelism present in many data mining applications based on evolutionary algorithms that …

Resilience can be defined as a system's capability for returning to normal operation after
having suffered a disruption. This notion is of the foremost interest in many areas, in …

Energy-aware computing is the design and operation of hardware and software systems to
minimize their energy consumption. This requires consideration of many variables and …

The energy consumption of Artificial Intelligence (AI) systems has increased 300,000-fold
from 2012 to now, and data centers running massive AI software produce up to 5-9% of …