A major challenge in modelling and simulation is the need to combine expertise in both
software technologies and a given scientific domain. When High-Performance Computing …

Many modern parallel computing systems are heterogeneous at their node level. Such
nodes may comprise general purpose CPUs and accelerators (such as, GPU, or Intel Xeon …

Recent developments in sensor technology, wearable computing, Internet of Things (IoT),
and wireless communication have given rise to research in ubiquitous healthcare and …

Fully utilizing the power of modern heterogeneous systems requires judiciously dividing
work across all of the available computational devices. Existing approaches for partitioning …

Performance analysis and tuning is an important step in programming multicore-and
manycore-based parallel architectures. While there are several tools to help developers …

Optimized software execution on parallel computing systems demands consideration of
many parameters at run-time. Determining the optimal set of parameters in a given …

An apparatus includes a first processor having a first instruc tion set and a second processor
having a second instruction set that is different than the first instruction set. The appa ratus …

This paper discusses the impact of structured parallel programming methodologies in state-
of-the-art industrial and research parallel programming frameworks. We first recap the main …

Deep learning is an important component of Big Data analytic tools and intelligent
applications, such as self-driving cars, computer vision, speech recognition, or precision …

Energy efficiency is an important aspect of future exascale systems, mainly due to rising
energy cost. Although High performance computing (HPC) applications are compute centric …