Nonlinear optimization: complexity issues
Nonlinear optimization: complexity issues
System-level synthesis of low-power hard real-time systems
DAC '97 Proceedings of the 34th annual Design Automation Conference
Power conscious fixed priority scheduling for hard real-time systems
Proceedings of the 36th annual ACM/IEEE Design Automation Conference
Synthesis of embedded software using free-choice Petri nets
Proceedings of the 36th annual ACM/IEEE Design Automation Conference
LEneS: task scheduling for low-energy systems using variable supply voltage processors
Proceedings of the 2001 Asia and South Pacific Design Automation Conference
Intra-Task Voltage Scheduling for Low-Energy, Hard Real-Time Applications
IEEE Design & Test
Software Energy Reduction Techniques for Variable-Voltage Processors
IEEE Design & Test
Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design
Extended quasi-static scheduling for formal synthesis and code generation of embedded software
Proceedings of the tenth international symposium on Hardware/software codesign
Quasi-Static Scheduling for Concurrent Architectures
ACSD '03 Proceedings of the Third International Conference on Application of Concurrency to System Design
A scheduling model for reduced CPU energy
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Template-Based Real-Time Dwell Scheduling with Energy Constraint
RTAS '03 Proceedings of the The 9th IEEE Real-Time and Embedded Technology and Applications Symposium
VLSID '03 Proceedings of the 16th International Conference on VLSI Design
Dynamic and Aggressive Scheduling Techniques for Power-Aware Real-Time Systems
RTSS '01 Proceedings of the 22nd IEEE Real-Time Systems Symposium
An environment for imprecise computations
An environment for imprecise computations
Pareto-optimization-based run-time task scheduling for embedded systems
Proceedings of the 1st IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
Maximizing rewards for real-time applications with energy constraints
ACM Transactions on Embedded Computing Systems (TECS)
Voltage-Clock-Scaling Adaptive Scheduling Techniques for Low Power in Hard Real-Time Systems
IEEE Transactions on Computers
Proceedings of the conference on Design, automation and test in Europe - Volume 1
Quasi-Static Scheduling for Real-Time Systems with Hard and Soft Tasks
Proceedings of the conference on Design, automation and test in Europe - Volume 2
Quasi-Static Voltage Scaling for Energy Minimization with Time Constraints
Proceedings of the conference on Design, Automation and Test in Europe - Volume 1
Proceedings of the 42nd annual Design Automation Conference
ASP-DAC '03 Proceedings of the 2003 Asia and South Pacific Design Automation Conference
Proceedings of the 2008 Asia and South Pacific Design Automation Conference
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Leakage-aware dynamic scheduling for real-time adaptive applications on multiprocessor systems
Proceedings of the 47th Design Automation Conference
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For some realtime systems, it is possible to tradeoff precision for timeliness. For such systems, typically considered under the imprecise computation model, a function assigns reward to the application depending on the amount of computation allotted to it. Also, these systems often have stringent energy constraints since many such applications run on battery powered devices. We address in this paper, the problem of maximizing rewards for imprecise computation systems that have energy constraints, more specifically, the problem of determining the voltage at which each task runs as well as the number of optional cycles such that the total reward is maximal while time and energy constraints are satisfied. We propose a quasi-static approach that is able to exploit, with low online overhead, the dynamic slack that arises from variations in the actual number of task execution cycles. In our quasi-static approach, the problem is solved in two steps: first, at design-time, a set of voltage/optional-cycles assignments are computed and stored (offline phase); second, the selection among the precomputed assignments is left for runtime, based on actual completion times and consumed energy (online phase). The advantages of the approach are demonstrated through numerous experiments with both synthetic examples and a real life application.