As both CPUs and GPUs become employed in a wide range of applications, it has been
acknowledged that both of these Processing Units (PUs) have their unique features and …

Heterogeneous many-cores are now an integral part of modern computing systems ranging
from embedding systems to supercomputers. While heterogeneous many-core design offers …

GPUs have become ubiquitous in the cloud due to the dramatic performance gains they
enable in domains such as machine learning and computer vision. However, offloading …

Across embedded, mobile, enterprise, and high performance computing systems, computer
architectures are becoming more heterogeneous and complex. This complexity is causing a …

Programming heterogeneous computing systems with Graphics Processing Units (GPU) and
multi-core CPUs in them is complex and time-consuming. OpenCL has emerged as an …

Drug screening is an important part of the drug development pipeline for the pharmaceutical
industry. Traditional, lab-based methods are increasingly being augmented with …

In this work, we present a C ompiler-integrated, E xtensible D omain Specific System on
Chip R untime (CEDR) ecosystem to facilitate research toward addressing the challenges of …

In this paper we detail the key features, architectural design, and implementation of rCUDA,
an advanced framework to enable remote and transparent GPGPU acceleration in HPC …

Unleashing the full potential of heterogeneous systems, consisting of multi-core CPUs and
GPUs, is a challenging task due to the difference in processing capabilities, memory …

Applications are migrating en masse to the cloud, while accelerators such as GPUs, TPUs,
and FPGAs proliferate in the wake of Moore's Law. These trends are in conflict: cloud …