By Topic

High-performance computing: clusters, constellations, MPPs, and future directions

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
$31 $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)

In a recent paper, Gordon Bell and Jim Gray (2002) put forth a view of the past, present, and future of high-performance computing (HPC) that is both insightful and thought provoking. Identifying key trends with a grace and candor rarely encountered in a single work, the authors describe an evolutionary past drawn from their vast experience and project an enticing and compelling vision of HPC's future. Yet, the underlying assumptions implicit in their treatment, particularly those related to terminology and dominant trends, conflict with our own experience, common practices, and shared view of HPCs future directions. Taken from our vantage points of the Top500 list," the Lawrence Berkeley National Laboratory NERSC computer center, Beowulf-class computing, and research in petaflops-scale computing architectures, we offer an alternate perspective on several key issues in the form of a constructive counterpoint. One objective of this article is to restore the strength and value of the term "cluster" by degeneralizing its applicability to a restricted subset of parallel computers. We'll further consider this class in conjunction with its complementing terms constellation, Beowulf class, and massively parallel processing systems (MPPs), based on the classification used by the Top500 list, which has tracked the HPC field for more than a decade.

Published in:

Computing in Science & Engineering  (Volume:7 ,  Issue: 2 )