This article presents a GPU-based single-unit deadlock detection methodology and its algorithm, GPU-OSDDA. Our GPU-based design utilizes parallel hardware of GPU to perform computations and thus is able to overcome the major limitation of prior hardware-based approaches by having the capability of handling thousands of processes and resources, whilst achieving real-world run-times. By utilizing...

General purpose computing on GPUs provides a way for certain applications to benefit from a commonly available massively parallel architecture. As such deployment becomes more widespread, multiple GPU applications will have to execute on the same hardware in systems that have only one GPU. The aggregate loads of the GPU and CPU impact the performance of each application. This work investigates ...

Graphics processing units (GPUs) have been adopted by major cloud vendors, as GPUs provide ordersof-magnitude speedup for computation-intensive dataparallel applications. In the cloud, efficiently sharing GPU resources among multiple virtual machines (VMs) is not so straightforward. Recent research has been conducted to develop GPU virtualization technologies, making it feasible for VMs to shar...

GPU computing has emerged in recent years as a viable execution platform for throughput oriented applications or regions of code. GPUs started out as independent units for program execution but there are clear trends towards tight-knit CPU-GPU integration. In this work, we will examine existing research directions and future opportunities for chip integrated CPU-GPU systems. We first seek to un...

Graphics processing units (GPUs) can act as an attractive alternative to CPUs for general purpose computation in certain scenarios. Traditionally, the GPU has been developed to offload graphics processing from the CPU. In recent years the GPU has continued to become a more flexible and powerful device, responding to the demand of the games industry to execute more and more complex custom graphi...

Graphics processing units (GPUs) have attracted enormous interest over the past decade due to substantial increases in both performance and programmability. Programmers can potentially leverage GPUs for substantial performance gains, but at the cost of significant software engineering effort. In practice, most GPU applications do not effectively utilize all of the available resources in a syste...

We have developed a graphics processor unit (GPU-) based high-speed fully 3D system for diffuse optical tomography (DOT). The reduction in execution time of 3D DOT algorithm, a severely ill-posed problem, is made possible through the use of (1) an algorithmic improvement that uses Broyden approach for updating the Jacobian matrix and thereby updating the parameter matrix and (2) the multinode m...

High performance computing with low cost machines becomes a reality with GPU. Unfortunately, high performances are achieved when the programmer exploits the architectural specificities of the GPU processors: he has to focus on inter-GPU communications, task allocations among the GPUs, task scheduling, external memory prefetching, and synchronization. In this paper, we propose and evaluate a com...