In the past decade, Graphics Processing Units have played an important role in the field of
high-performance computing and they still advance new fields such as IoT, autonomous …

The recently introduced roofline model plots the performance of executed code against its
operational intensity (operations count divided by memory traffic). It also includes two …

Performance and energy are the two most important objectives for optimization on modern
parallel platforms. In this article, we show that moving from single-objective optimization for …

The potential of FPGAs as accelerators for high‐performance computing applications is very
large, but many factors are involved in their performance. The design for FPGAs and the …

Automated coastline extraction from optical satellites is fundamental to coastal mapping, and
sea-land segmentation is the core technology of coastline extraction. Deep convolutional …

Optimization, portability and development of GPGPU applications are not trivial tasks, since
the capabilities and organization of GPU processing elements and memory subsystem …

Local search metaheuristics (LSMs) are efficient methods for solving hard optimization
problems in science, engineering, economics and technology. By using LSMs, we could …

In this letter, a multi-GPU accelerated one-step leapfrog alternative-direction-implicit finite-
difference time-domain (ADI-FDTD) based on parallel SPIKE tridiagonal systems solver is …

Multiplication of a sparse matrix to a dense matrix (SpDM) is widely used in many areas like
scientific computing and machine learning. However, existing work under-looks the …

High-performance computing on heterogeneous platforms in general and those with FPGAs
in particular presents a significant programming challenge. We contend that compiler …