Early work on modeling computational sprinting

None, None; None, None; None, None; None, None; None, None

Early work on modeling computational sprinting

Conference Paper (2017)

Author(s)

Nathaniel Morris (The Ohio State University)

Christopher Stewart (The Ohio State University)

Robert Birke (Zurich Lab)

Lydia Chen (Zurich Lab)

Jaimie Kelley (Denison University)

Simulation Resource management Prediction accuracy Computational sprinting CPU throttling Queuing models

DOI related publication

https://doi.org/10.1145/3127479.3132691 Final published version

To reference this document use

https://resolver.tudelft.nl/uuid:8d5733f8-dcf7-423e-b27e-35505125d387

More Info

expand_more

Publication Year

2017

Language

English

Pages (from-to)

1

ISBN (electronic)

9781450350280

Event

Downloads counter

132

Abstract

Ever tightening power caps constrain the sustained processing speed of modern processors. With computational sprinting, processors reserve a small power budget that can be used to increase processing speed for short bursts. Computational sprinting speeds up query executions that would otherwise yield slow response time. Common mechanisms used for sprinting include DVFS, core scaling, CPU throttling and application-specific accelerators.