The growing global demand for services offered by data centers (DCs) has increased their
total power consumption and carbon emissions. Recent figures revealed that DCs account …

Effective management of ICT (information and communications technology) and cooling is
critical in modern data centres for high energy efficiency. This survey paper gives an …

The advent of petascale computing has introduced new challenges (eg Heterogeneity,
system failure) for programming scalable parallel applications. Increased complexity and …

Scientists are increasingly exploring and utilizing the massive parallelism of general-
purpose accelerators such as GPUs for scientific breakthroughs. As a result, datacenters …

The design and manufacture of present-day CPUs causes inherent variation in
supercomputer architectures such as variation in power and temperature of the chips. The …

Deep reinforcement learning (DRL) has shown good performance in tackling Markov
decision process (MDP) problems. As DRL opti-mizes a long-term reward, it is a promising …

Dynamic voltage and frequency scaling (DVFS) is a well-known technique to reduce the
power and/or energy consumption of various applications. While most processors provide …

Deep reinforcement learning (DRL) has shown good performance in tackling Markov
decision process (MDP) problems. As DRL optimizes a long-term reward, it is a promising …

Large-scale computing systems are increasingly using accelerators such as GPUs to enable
peta-and exa-scale levels of compute to meet the needs of Machine Learning (ML) and …

An overview of the most prominent contemporary parallel processing programming models,
written in a unique tutorial style. With the coming of the parallel computing era, computer …