Heterogeneous multi-core architectures consisting of CPUs and GPUs are commonplace in
today's embedded systems. These architectures offer potential for energy efficient computing …

The use of heterogeneous systems in supercomputing is on the rise as they improve both
performance and energy efficiency. However, the programming of these machines requires …

Modern standards in High Performance Computing (HPC) have started to consider energy
consumption and power draw as a limiting factor. New and more complex architectures have …

While GPUs are meantime omnipresent for many scientific and technical computations, they
still continue to evolve as processors. An important recent feature is the ability to execute …

Heterogeneous processors integrate very distinct compute resources such as CPUs and
GPUs into the same chip, thus can exploit the advantages and avoid disadvantages of those …

The reduction of the dimensionality is of great interest in the context of big data processing.
Multidimensional scaling methods (MDS) are techniques for dimensionality reduction, where …

Heterogeneous computers require a well-distributed workload to operate efficiently. When
possible, this load balancing procedure should redistribute the workload with minimal …

OpenCL defines a common parallel programming language for all devices, although writing
tasks adapted to the devices, managing communication and load-balancing issues are left …

Automated code generation is an enabling technology for model-based software
development and promises many benefits, including higher quality and reduced turn-around …

Heterogeneous System-on-Chip (SoC) processors are increasingly gaining traction in the
High Performance Computing (HPC) community as alternate building blocks for future …