Abstract
Energy consumption is a critical issue in parallel and distributed systems. Workflows consist of a number of tasks that need to be executed to complete an application. These tasks typically have precedence relationships that have to be observed during execution for correctness. DAGs (Directed Acyclic Graphs) can be used to represent many such workflows. The static algorithms to schedule for energy minimization under the deadline constraints are based on estimating worst case execution time for each task to guarantee that the application completes by a given deadline. During execution, many tasks may complete earlier than expected during the actual execution. This allows for adjusting the schedule for the tasks that have not yet begun execution to incorporate the extra slack. This has to be done with the dual goal of reducing the energy requirements while still meeting the deadline constraints. In this paper, we present a novel dynamic algorithm for remapping tasks for energy efficient scheduling of DAG based applications for DVS enabled systems. Our experimental results show that the combination of our dynamic assignment and dynamic slack allocation leads to significantly better energy minimization compared to not changing the static schedule and/or only performing dynamic slack allocation. Furthermore, its execution time requirements are small enough to be useful for a large number of applications.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Aydin, H., Melhem, R., Mossé, D., Mejía-Alvarez, P.: Power-Aware Scheduling for Periodic Real-Time Tasks. IEEE Trans. on Computers 53(5), 584–600 (2004)
Chandrakasan, A.P., Sheng, S., Brodersen, R.W.: Low-Power CMOS Digital Design. IEEE J. of Solid-State Circuits 27(4), 473–484 (1992)
Jejurikar, R., Gupta, R.: Dynamic Slack Reclamation with Procrastination Scheduling in Real-Time Embedded Systems. In: Jejurikar, R., Gupta, R. (eds.) Design Automation Conf., pp. 111–116 (2005)
Kang, J., Ranka, S.: Dynamic Algorithms for Energy Minimization on Parallel Machines. In: Euromicro Conf. on Parallel, Distributed and Network-Based Processing, pp. 399–406 (2008)
Kang, J., Ranka, S.: DVS based Energy Minimization Algorithm for Parallel Machines. IEEE Int. Parallel and Distributed Processing Sym., 1–12 (2008)
Kang, J., Ranka, S.: Assignment Algorithm for Energy Minimization on Parallel Machines, University of Florida Technical Report (2008)
Mishra, R., Rastogi, N., Zhu, D., Mossé, D., Melhem, R.: Energy Aware Scheduling for Distributed Real-Time Systems. In: Int. Parallel and Distributed Processing Sym., p. 21b (2003)
Shin, Y., Choi, K.: Power Conscious Fixed Priority Scheduling for Hard Real-Time Systems. In: Design Automation Conf., pp. 134–139 (1999)
Zhang, Y., Sharon Hu, X., Chen, D.Z.: Task Scheduling and Voltage Selection for Energy Minimization. In: Design Automation Conf., pp. 183–188 (2002)
Dataquest, http://data1.cde.ca.gov/dataquest/
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kang, J., Ranka, S. (2008). Energy-Efficient Dynamic Scheduling on Parallel Machines. In: Sadayappan, P., Parashar, M., Badrinath, R., Prasanna, V.K. (eds) High Performance Computing - HiPC 2008. HiPC 2008. Lecture Notes in Computer Science, vol 5374. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89894-8_21
Download citation
DOI: https://doi.org/10.1007/978-3-540-89894-8_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89893-1
Online ISBN: 978-3-540-89894-8
eBook Packages: Computer ScienceComputer Science (R0)