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

We describe the experience of converting a CUDA implementation of a high-order epistasis
detection algorithm to SYCL. The goals are for our work to be useful to application and …

Our goal is to have a better understanding of performance portability of SYCL kernels on a
GPU. Toward this goal, we migrate representative kernels in bioinformatics applications from …

Heterogeneous platforms composed of multiple different types of computing devices (such
as CPUs, GPUs, and Intel MICs) have been widely used recently. However, most of parallel …

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 …

Homomorphisms (traditionally defined on lists) are functions that can be parallelized by the
divide-and-conquer paradigm. In this paper, we introduce an extension of the traditional …

SYCL allows for deployment and use of accelerators across vendors' platforms. In this work,
we describe the experience of deploying graph analytics on vendors' GPUs using SYCL. We …

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

We describe the experience of converting a CUDA implementation of a parallel graph
coloring algorithm to SYCL. The goals are for our work to be useful to application and …

Heterogeneous devices require much more work from programmers than traditional CPUs,
particularly when there are several of them, as each one has its own memory space. Multi …