The University of Southampton
University of Southampton Institutional Repository

Reinforcement learning-based DPM-DVFS trade-off for thermal-aware power optimization of embedded systems

Reinforcement learning-based DPM-DVFS trade-off for thermal-aware power optimization of embedded systems
Reinforcement learning-based DPM-DVFS trade-off for thermal-aware power optimization of embedded systems
Das, Anup K.
2a0d6cea-309b-4053-a62e-234807f89306
Walker, Mathew J.
9a55e5d4-22c2-4115-8d9a-d905c362210c
Merrett, Geoff V.
89b3a696-41de-44c3-89aa-b0aa29f54020
Hashimi, B.M.
0b29c671-a6d2-459c-af68-c4614dce3b5d
Das, Anup K.
2a0d6cea-309b-4053-a62e-234807f89306
Walker, Mathew J.
9a55e5d4-22c2-4115-8d9a-d905c362210c
Merrett, Geoff V.
89b3a696-41de-44c3-89aa-b0aa29f54020
Hashimi, B.M.
0b29c671-a6d2-459c-af68-c4614dce3b5d

Das, Anup K., Walker, Mathew J., Merrett, Geoff V. and Hashimi, B.M. (2015) Reinforcement learning-based DPM-DVFS trade-off for thermal-aware power optimization of embedded systems At WIP at Design Automation Conference (DAC), United States. 07 - 11 Jun 2015.

Record type: Conference or Workshop Item (Paper)

Full text not available from this repository.

More information

Accepted/In Press date: February 2015
Venue - Dates: WIP at Design Automation Conference (DAC), United States, 2015-06-07 - 2015-06-11
Organisations: EEE

Identifiers

Local EPrints ID: 374557
URI: http://eprints.soton.ac.uk/id/eprint/374557
PURE UUID: f6b49526-01f7-4f99-ae35-aeeb1e67858d
ORCID for Geoff V. Merrett: ORCID iD orcid.org/0000-0003-4980-3894

Catalogue record

Date deposited: 20 Feb 2015 15:03
Last modified: 17 Jul 2017 21:26

Export record

Contributors

Author: Anup K. Das
Author: Mathew J. Walker
Author: Geoff V. Merrett ORCID iD
Author: B.M. Hashimi

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×