By Topic

The performance of the Cedar multistage switching network

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

2 Author(s)
Torrellas, J. ; Center for Supercomput. Res. & Dev., Illinois Univ., Urbana, IL, USA ; Zheng Zhang

While multistage switching networks for vector multiprocessors have been studied extensively, detailed evaluations of their performance are rare. Indeed, analytical models, simulations with pseudosynthetic loads, studies focused on average-value parameters, and measurements of networks disconnected from the machine, all provide limited information. In this paper, instead, we present an in-depth empirical analysis of a multistage switching network in a realistic setting: We use hardware probes to examine the performance of the omega network of the Cedar shared-memory machine executing real applications. The machine is configured with 16 vector processors. The analysis suggests that the performance of multistage switching networks is limited by traffic nonuniformities. We identify two major nonuniformities that degrade Cedar's performance and are likely to slow down other networks too. The first one is the contention caused by the return messages in a vector access as they converge from the memories to one processor port. This traffic convergence penalizes vector reads and, more importantly, causes tree saturation. The second nonuniformity is the uneven contention delays induced by a relatively fair scheme to resolve message collisions. Based on our observations, we argue that intuitive optimizations for multistage switching networks may not be the most cost-effective ones. Instead, we suggest changes to increase the network bandwidth at the root of the traffic convergence tree and to delay traffic convergence up until the final stages of the network

Published in:

Parallel and Distributed Systems, IEEE Transactions on  (Volume:8 ,  Issue: 4 )