"Precise Scheduling of DAG Tasks with Dynamic Power Management" by Ashikahmed Bhuiyan, Mohammad Pivezhandi et al.
 

Precise Scheduling of DAG Tasks with Dynamic Power Management

Document Type

Conference Proceeding

Publication Date

7-1-2023

Abstract

The rigid timing requirement of real-time applications biases the analysis to focus on the worst-case performances. Such a focus cannot provide enough information to optimize the system’s typical resource and energy consumption. In this work, we study the real-time scheduling of parallel tasks on a multi-speed heterogeneous platform while minimizing their typical-case CPU energy consumption. Dynamic power management (DPM) policy is integrated to determine the minimum number of cores required for each task while guaranteeing worst-case execution requirements (under all circumstances). A Hungarian Algorithm-based task partitioning technique is proposed for clustered multi-core platforms, where all cores within the same cluster run at the same speed at any time, while different clusters may run at different speeds. To our knowledge, this is the first work aiming to minimize typical-case CPU energy consumption (while ensuring the worst-case timing correctness for all tasks under any execution condition) through DPM for parallel tasks in a clustered platform. We demonstrate the effectiveness of the proposed approach with existing power management techniques using experimental results and simulations. The experimental results conducted on the Intel Xeon 2680 v3 12-core platform show around 7%-30% additional energy savings.

Identifier

85165997927 (Scopus)

ISBN

[9783959772808]

Publication Title

Leibniz International Proceedings in Informatics Lipics

External Full Text Location

https://doi.org/10.4230/LIPIcs.ECRTS.2023.8

ISSN

18688969

Volume

262

Grant

CAREER-2306486

Fund Ref

University of Nevada, Las Vegas

This document is currently not available here.

Share

COinS