Heterogeneity among the computational resources within a single machine has significantly
increased in high performance computing to exploit the tremendous potential of graphics …

Graphics processing units (GPUs) are gradually becoming mainstream in high-performance
computing, as their capabilities for enhancing performance of a large spectrum of scientific …

With the improvement of GPU's general computing capacity, the use of parallel computing to
solve some difficult problems with large amount of data and intensive computing tasks has …

The performance optimization of scientific applications usually requires an in-depth
knowledge of the hardware and software. A performance tuning mechanism is suggested to …

Micromagnetics is a field of study considering the magnetization behavior in magnetic
materials and devices accounting for a wide set of interactions and describing the …

We optimize parameters in OpenACC clauses for a stencil evaluation kernel executed on
Graphical Processing Units (GPUs) using a variety of machine learning and optimization …

A scalable parallelization algorithm to port an explicit marching-on-in-time (MOT)-based time
domain volume integral equation (TDVIE) solver onto multi-GPUs is described. The …

In this paper, we present an efficient parallel algorithm for calculating cumulative integration
based on Simpson's rule. The proposed parallel algorithm exploits two Blelloch's prefix …