In this paper, we propose SnuCL, an OpenCL framework for heterogeneous CPU/GPU
clusters. We show that the original OpenCL semantics naturally fits to the heterogeneous …

Heterogeneous parallel computing platforms, which are composed of different processors
(eg, CPUs, GPUs, FPGAs, and DSPs), are widening their user base in all computing …

OpenCL is a standard for parallel programming of heterogeneous systems. The benefits of a
common programming standard are clear; multiple vendors can provide support for …

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 …

In this paper, we propose an OpenCL framework that combines multiple GPUs and treats
them as a single compute device. Providing a single virtual compute device image to the …

The problem of automatically generating hardware modules from a high level representation
of an application has been at the research forefront in the last few years. In this paper, we …

Software engineering (SE) educators have been advocating the use of non-conventional
approaches for SE education since long. In this context, we conducted action-research to …

With its design concept of cross-platform portability, OpenCL can be used not only on GPUs
(for which it is quite popular), but also on CPUs. Whether porting GPU programs to CPUs, or …

In this paper, we address the effect of the work-group size on the performance of OpenCL
kernels. We propose a profiling-based algorithm that finds a good work-group size, in terms …

This paper presents a cooperative heterogeneous computing framework which enables the
efficient utilization of available computing resources of host CPU cores for CUDA kernels …