Power optimization of variable voltage core-based systems
DAC '98 Proceedings of the 35th annual Design Automation Conference
Voltage scheduling problem for dynamically variable voltage processors
ISLPED '98 Proceedings of the 1998 international symposium on Low power electronics and design
Power conscious fixed priority scheduling for hard real-time systems
Proceedings of the 36th annual ACM/IEEE Design Automation Conference
System-level power optimization: techniques and tools
ISLPED '99 Proceedings of the 1999 international symposium on Low power electronics and design
Scheduling Algorithms for Multiprogramming in a Hard-Real-Time Environment
Journal of the ACM (JACM)
A methodology and algorithms for the design of hard real-time multitasking ASICs
ACM Transactions on Design Automation of Electronic Systems (TODAES)
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
Robust subthreshold logic for ultra-low power operation
IEEE Transactions on Very Large Scale Integration (VLSI) Systems - Special issue on low power electronics and design
Numerical Recipes in C: The Art of Scientific Computing
Numerical Recipes in C: The Art of Scientific Computing
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
Subthreshold leakage modeling and reduction techniques
Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design
Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design
Optimal voltage allocation techniques for dynamically variable voltage processors
Proceedings of the 40th annual Design Automation Conference
A scheduling model for reduced CPU energy
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Optimal Supply and Threshold Scaling for Subthreshold CMOS Circuits
ISVLSI '02 Proceedings of the IEEE Computer Society Annual Symposium on VLSI
RTSS '01 Proceedings of the 22nd IEEE Real-Time Systems Symposium
Convex Optimization
Leakage aware dynamic voltage scaling for real-time embedded systems
Proceedings of the 41st annual Design Automation Conference
Theoretical and practical limits of dynamic voltage scaling
Proceedings of the 41st annual Design Automation Conference
Characterizing and modeling minimum energy operation for subthreshold circuits
Proceedings of the 2004 international symposium on Low power electronics and design
Energy Optimization of Subthreshold-Voltage Sensor Network Processors
Proceedings of the 32nd annual international symposium on Computer Architecture
Energy minimization for real-time systems with non-convex and discrete operation modes
Proceedings of the Conference on Design, Automation and Test in Europe
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Until now, the great majority of research in low-power systems has assumed a convex power model. However, recently, due to the confluence of emerging technological and architectural trends, standard convex models have been invalidated for the proper specification of power models with different execution speeds. For example, the use of a shutdown energy minimization strategy to eliminate leakage power in multiprocessor systems results in a nonconvex trade-off between power and speed. Non-convexity renders the majority of previous power management schemes, algorithms, and even basic theorems invalid. For instance, the main premise that one has to run continuously using a single speed in order to minimize energy consumption for constant computation requirements is not valid anymore. We study techniques for energy minimization where the power versus speed curve has a non-convex shape. We first identify and quantify sources of nonconvexity. Minimizing energy when the power-speed model is non-convex is an NP-complete problem, even in the canonical and simple case where a task is to execute a specified amount of computation without dependencies, in a given amount of time. We address this problem using a non-linear function minimization based approach and demonstrate that on average the new solution saves at least 40% more energy on industrial processors than techniques that follow the convexity paradigm. Then we address common real-time task scenarios where the power-speed model is non-convex. Specifically, we introduce a heuristic for scheduling tasks onto a multiprocessor system with a non-trivial start-up cost and compare its performance to our mixed integer linear programming (MIP) formulation. We experimentally compare our neighbors heuristic with the wellknown average rate algorithm, and find that it results in a 106% improvement while being only 14% worse than the optimal MIP solution.