Argonne National Laboratory

Exploring the Suitability of Remote GPGPU Virtualization for the OpenACC Programming Model using rCUDA

TitleExploring the Suitability of Remote GPGPU Virtualization for the OpenACC Programming Model using rCUDA
Publication TypeConference Paper
Year of Publication2015
AuthorsCastello, A, Mayo, R, Quintana-Orti, ES, Pena, AJ, Balaji, P
Conference NameIEEE Cluster 2015
Date Published09/2015
PublisherIEEE
Conference LocationChicago, IL
Other NumbersANL/MCS-P5276-0115-0315
AbstractOpenACC is an application programming interface (API) that aims to unleash the power of heterogeneous systems composed of CPUs and accelerators such as graphic processing units (GPUs) or Intel Xeon Phi coprocessors. This directive-based programming model is intended to enable developers to accelerate their application’s execution with much less effort. Coprocessors offer significant computing power but in many cases these devices remain largely underused because not all parts of applications match the accelerator architecture. Remote accelerator virtualization frameworks introduce a means to address this problem. In particular, the remote CUDA virtualization middleware rCUDA provides transparent remote access to any GPU installed in a cluster. Combining these two technologies, OpenACC and rCUDA, in a single scenario is naturally appealing. In this work we explore how the different OpenACC directives behave on top of a remote GPGPU virtualization technology in two different hardware configurations. Our experimental evaluation reveals favorable performance results when the two technologies are combined, showing low overhead and similar scaling factors when executing OpenACC-enabled directives.  
DOI10.1109/CLUSTER.2015.23
PDFhttp://www.mcs.anl.gov/papers/P5276-0115.pdf