A predictive system shutdown method for energy saving of event-driven computation
ICCAD '97 Proceedings of the 1997 IEEE/ACM international conference on Computer-aided design
Dynamic power management for non-stationary service requests
DATE '99 Proceedings of the conference on Design, automation and test in Europe
A survey of design techniques for system-level dynamic power management
IEEE Transactions on Very Large Scale Integration (VLSI) Systems - Special section on low-power electronics and design
Dynamic Power Management: Design Techniques and CAD Tools
Dynamic Power Management: Design Techniques and CAD Tools
Latency effects of system level power management algorithms
Proceedings of the 2000 IEEE/ACM international conference on Computer-aided design
Adaptive Hard Disk Power Management on Personal Computers
GLS '99 Proceedings of the Ninth Great Lakes Symposium on VLSI
Online strategies for dynamic power management in systems with multiple power-saving states
ACM Transactions on Embedded Computing Systems (TECS)
Proceedings of the conference on Design, automation and test in Europe
Static-Priority Scheduling on Multiprocessors
RTSS '01 Proceedings of the 22nd IEEE Real-Time Systems Symposium
Worst-case utilization bound for EDF scheduling on real-time multiprocessor systems
Euromicro-RTS'00 Proceedings of the 12th Euromicro conference on Real-time systems
Policy optimization for dynamic power management
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
| Hi-index | 0.00 |
Emerging trends in applications with the requirement of considerable computational performance and decreasing time-to-market have urged the need of multiprocessor systems. With the increase in number of processors, there is an increased demand to efficiently control the energy and power budget of such embedded systems. Dynamic Power Management (DPM) strategies attempt to control this budget by actively changing the power consumption profile of the system. This paper presents a novel DPM strategy for real time applications. It is based on the extraction of inherently present idleness in application’s behavior to make appropriate decisions for state-transition of processors in a multiprocessor system. Experimental results show that conventional DPM approaches often yield suboptimal, if not incorrect, performance in the presence of real time constraints. Our strategy gives better energy consumption performance under the same constraints by 10.40%. Also, it reduces the number of overall state transitions by 74.85% and 59.76% for EDF and LLF scheduling policies respectively.