IEEE Transactions on Parallel and Distributed Systems
Design considerations for battery-powered electronics
Proceedings of the 36th annual ACM/IEEE Design Automation Conference
Battery-aware static scheduling for distributed real-time embedded systems
Proceedings of the 38th annual Design Automation Conference
An analytical high-level battery model for use in energy management of portable electronic systems
Proceedings of the 2001 IEEE/ACM international conference on Computer-aided design
Battery-Driven System Design: A New Frontier in Low Power Design
ASP-DAC '02 Proceedings of the 2002 Asia and South Pacific Design Automation Conference
Energy management for battery-powered embedded systems
ACM Transactions on Embedded Computing Systems (TECS)
Balancing batteries, power, and performance: system issues in cpu speed-setting for mobile computing
Balancing batteries, power, and performance: system issues in cpu speed-setting for mobile computing
CODES+ISSS '05 Proceedings of the 3rd IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
Battery optimization vs energy optimization: which to choose and when?
ICCAD '05 Proceedings of the 2005 IEEE/ACM International conference on Computer-aided design
Energy management for battery-powered reconfigurable computing platforms
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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In this work we consider battery powered portable systems which either have Field Programmable Gate Arrays (FPGA) or voltage and frequency scalable processors as their main processing element. An application is modeled in the form of a precedence task graph at a coarse level of granularity. We assume that for each task in the task graph several unique design-points are available which correspond to different hardware implementations for FPGAs and different voltage-frequency combinations for processors. It is assumed that performance and total power consumption estimates for each design-point are available for any given portable platfrom, including the peripheral components such as memory and display power usage. We present an iterative heuristic algorithm which finds a sequence of tasks along with an appropriate design-point for each task, such that a deadline is met and the amount of battery energy used is as small as possible. A detailed illustrative example along with a case study of a real-world application of a robotic arm controller which demonstrates the usefulness of our algorithm is also presented.