Cart (Loading....) | Create Account
Close category search window
 

The Dynamics of Backfilling: Solving the Mystery of Why Increased Inaccuracy May Help

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)
Tsafrir, D. ; Sch. of Comput. Sci. & Eng., Hebrew Univ., Jerusalem ; Feitelson, D.G.

Parallel job scheduling with backfilling requires users to provide runtime estimates, used by the scheduler to better pack the jobs. Studies of the impact of such estimates on performance have modeled them using a "badness factor" f ges 0 in an attempt to capture their inaccuracy (given a runtime r, the estimate is uniformly distributed in [r, (f + 1) middot r]). Surprisingly, inaccurate estimates (f > 0) yielded better performance than accurate ones (f = 0). We explain this by a "heel and toe" dynamics that, with f > 0, cause backfilling to approximate shortest-job first scheduling. We further find the effect of systematically increasing f is V-shaped: average wait time and slowdown initially drop, only to rise later on. This happens because higher fs create bigger "holes" in the schedule (longer jobs can backfill) and increase the randomness (more long jobs appear as short), thus overshadowing the initial heel-and-toe preference for shorter jobs. The bottom line is that artificial inaccuracy generated by multiplying (real or perfect) estimates by a factor is (1) just a scheduling technique that trades off fairness for performance, and is (2) ill-suited for studying the effect of real inaccuracy. Real estimates are modal (90% of the jobs use the same 20 estimates) and bounded by a maximum (usually the most popular estimate). Therefore, when performing an evaluation, "increased inaccuracy" should translate to increased modality. Unlike multiplying, this indeed worsens performance as one would intuitively expect

Published in:

Workload Characterization, 2006 IEEE International Symposium on

Date of Conference:

25-27 Oct. 2006

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.