By Topic

Retargeting PLAPACK to clusters with hardware accelerators

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Manuel Fogué ; Depto. de Ingeniería y Ciencia de Computadores, Universidad Jaume I, 12071, Castellón, Spain ; Francisco D. Igual ; Enrique S. Quintana-Ortí ; Robert A. van de Geijn

Hardware accelerators are becoming a highly appealing approach to boost the raw performance as well as the price-performance and power-performance ratios of current clusters. In this paper we present a strategy to retarget PLAPACK, a library initially designed for clusters of nodes equipped with general-purpose processors and a single address space per node, to clusters equipped with graphics processors (GPUs). In our approach data are kept in the device memory and only retrieved to main memory when they have to be communicated to a different node. Here we benefit from the object-based orientation of PLAPACK which allows all communication between host and device to be embedded within a pair of routines, providing a clean abstraction that enables an efficient and direct port of all the contents of the library. Our experiments in a cluster consisting of 16 nodes with two NVIDIA Quadro FX5800 GPUs each show the performance of our approach.

Published in:

High Performance Computing and Simulation (HPCS), 2010 International Conference on

Date of Conference:

June 28 2010-July 2 2010