Title
Energy-Aware Partitioned Fixed-Priority Scheduling for Chip Multi-processors
Abstract
Energy management is becoming an increasingly important problem in application domains ranging from embedded devices to data centers. In many such systems, multi-core processors are projected as a promising technology to achieve improved performance with a lower power envelope. Managing the application power consumption under timing constraints poses significant challenges in these emerging platforms. In this paper, we study the energy-efficient scheduling of periodic real time tasks with implicit deadlines on chip multi-core processors (CMPs). We specifically consider processors with a single voltage and clock frequency domain, such as the state-of-the-art embedded multi-core NVIDIA Tegra 2processor and enterprise-class processors such as Intel'sItanium 2, i5, i7 and IBM's Power 6 and Power 7series. The major contributions of this work are (i)we prove that Worst-Fit-Decreasing (WFD) task partitioning when Rate-Monotonic Scheduling (RMS) is used has an approximation ratio of 1.71 for the problem of minimizing the schedulable operating frequency with partitioned fixed-priority scheduling, (ii) we illustrate the major shortcoming of WFD with RMS resulting from not considering task periods during allocation, and(iii) we propose a Single-clock domain multi-processor Frequency Assignment Algorithm (SFAA) that determines a globally energy-efficient frequency while including task period relationships. Our evaluation results show that SFAA provides significant energy gains when compared to WFD. In fact SFAA is shown to save up to 55% more power compared to WFD for an octa-core processor.
Year
DOI
Venue
2011
10.1109/RTCSA.2011.75
RTCSA (1)
Keywords
Field
DocType
energy-efficient frequency,energy-aware partitioned fixed-priority scheduling,clock frequency domain,schedulable operating frequency,application power consumption,periodic real time task,lower power envelope,chip multi-processors,state-of-the-art embedded multi-core,fact sfaa,multi-core processor,chip multi-core processor,energy efficient,data center,frequency domain,real time systems,multi core processor,energy management,rate monotonic scheduling
Energy management,Scheduling (computing),Computer science,Real-time computing,Chip,Ranging,Frequency assignment,Energy consumption,Multi-core processor,Clock rate,Embedded system,Distributed computing
Conference
Volume
ISSN
ISBN
1
1533-2306
978-1-4577-1118-3
Citations 
PageRank 
References 
15
0.61
28
Authors
4
Name
Order
Citations
PageRank
Arvind Kandhalu12339.29
Junsung Kim224316.69
Karthik Lakshmanan373231.22
Ragunathan (Raj) Rajkumar42868183.27