Coordinating the use of GPU and CPU for improving performance of compute intensive applications

GPUs have recently evolved into very fast parallel co-processors capable of executing general purpose computations extremely efficiently. At the same time, multi-core CPUs evolution continued and today's CPUs have 4-8 cores. These two trends, however, have followed independent paths in the sense that we are aware of very few works that consider both devices cooperating to solve general computations. In this paper we investigate the coordinated use of CPU and GPU to improve efficiency of applications even further than using either device independently. We use Anthill runtime environment, a data-flow oriented framework in which applications are decomposed into a set of event-driven filters, where for each event, the runtime system can use either GPU or CPU for its processing. For evaluation, we use a histopathology application that uses image analysis techniques to classify tumor images for neuroblastoma prognosis. Our experimental environment includes dual and octa-core machines, a...

• Type: Journal
• Year: 2009
• Where: CLUSTER
• Authors: George Teodoro, Rafael Sachetto Oliveira, Olcay Sertel, Metin N. Gurcan, Wagner Meira Jr., Ümit V. Çatalyürek, Renato Ferreira
• Keywords: CLUSTER 2009, Distributed And Parallel Computing, GPUs, Multi-core Cpus Evolution, Single Core