Title :
GPU clusters for high-performance computing
Author :
Kindratenko, Volodymyr V. ; Enos, Jeremy J. ; Shi, Guochun ; Showerman, Michael T. ; Arnold, Galen W. ; Stone, John E. ; Phillips, James C. ; Hwu, Wen-Mei
Author_Institution :
Nat. Center for Supercomput. Applic., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
fDate :
Aug. 31 2009-Sept. 4 2009
Abstract :
Large-scale GPU clusters are gaining popularity in the scientific computing community. However, their deployment and production use are associated with a number of new challenges. In this paper, we present our efforts to address some of the challenges with building and running GPU clusters in HPC environments. We touch upon such issues as balanced cluster architecture, resource sharing in a cluster environment, programming models, and applications for GPU clusters.
Keywords :
computer graphic equipment; workstation clusters; balanced cluster architecture; graphics processing units; high-performance computing; large-scale GPU clusters; programming models; resource sharing; scientific computing community; Bandwidth; Computational biophysics; Computer architecture; Data security; Hardware; Parallel programming; Production; Quadratic programming; Resource management; Space cooling;
Conference_Titel :
Cluster Computing and Workshops, 2009. CLUSTER '09. IEEE International Conference on
Conference_Location :
New Orleans, LA
Print_ISBN :
978-1-4244-5011-4
Electronic_ISBN :
1552-5244
DOI :
10.1109/CLUSTR.2009.5289128
