Precise Scheduling of DAG Tasks with Dynamic Power Management

Ashikahmed Bhuiyan, Mohammad Pivezhandi, Zhishan Guo, Jing Li, Venkata Prashant Modekurthy, Abusayeed Saifullah

Research output: Chapter in Book/Report/Conference proceedingConference contribution


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.

Original languageEnglish (US)
Title of host publication35th Euromicro Conference on Real-Time Systems, ECRTS 2023
EditorsAlessandro V. Papadopoulos
PublisherSchloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
ISBN (Electronic)9783959772808
StatePublished - Jul 2023
Externally publishedYes
Event35th Euromicro Conference on Real-Time Systems, ECRTS 2023 - Vienna, Austria
Duration: Jul 11 2023Jul 14 2023

Publication series

NameLeibniz International Proceedings in Informatics, LIPIcs
ISSN (Print)1868-8969


Conference35th Euromicro Conference on Real-Time Systems, ECRTS 2023

All Science Journal Classification (ASJC) codes

  • Software


  • Parallel task
  • cluster-based platform
  • dynamic power management
  • energy minimization
  • mixed-criticality scheduling


Dive into the research topics of 'Precise Scheduling of DAG Tasks with Dynamic Power Management'. Together they form a unique fingerprint.

Cite this