Article
Voltage setup problem for embedded systems with multiple voltages
Univ. of Maryland, College Park, MD, USA
IEEE Transactions on Very Large Scale Integration (VLSI) Systems (Impact Factor: 1.22). 08/2005; DOI: 10.1109/TVLSI.2005.850122 Source: IEEE Xplore

Conference Paper: Optimal manufacturing flow to determine minumum operating voltage.
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ABSTRACT: A technique to optimize power determines the minimum operating voltage during manufacturing testing on a per die basis. The die is then programmed to operate at the minimum voltage for the life of the die. Silicon results to evaluate the effectiveness of a variety of techniques to determine the minimum voltage of a die, in a manufacturing environment, are presented. Based on this we propose an adaptive hybrid test flow that is guaranteed to compute the minimum voltage while minimizing test time. Finally, sample data on power optimization achievable using power reduction is provided.2011 IEEE International Test Conference, ITC 2011, Anaheim, CA, USA, September 2022, 2011; 01/2011  [Show abstract] [Hide abstract]
ABSTRACT: In this article, we focus on solving the energy optimization problem for realtime streaming applications on multiprocessor SystemonChip by combining tasklevel coarsegrained software pipelining with DVS (Dynamic Voltage Scaling) and DPM (Dynamic Power Management) considering transition overhead, intercore communication and discrete voltage levels. We propose a twophase approach to solve the problem. In the first phase, we propose a coarsegrained task parallelization algorithm called RDAG to transform a periodic dependent task graph into a set of independent tasks by exploiting the periodic feature of streaming applications. In the second phase, we propose a scheduling algorithm, GeneS, to optimize energy consumption. GeneS is a genetic algorithm that can search and find the best schedule within the solution space generated by gene evolution. We conduct experiments with a set of benchmarks from E3S and TGFF. The experimental results show that our approach can achieve a 24.4% reduction in energy consumption on average compared with the previous work.ACM Trans. Design Autom. Electr. Syst. 01/2011; 16:14.  [Show abstract] [Hide abstract]
ABSTRACT: In this paper, we combine coarsegrained software pipelining with DVS (Dynamic Voltage/Frequency Scaling) for optimizing energy consumption of streambased multimedia applications on multicore embedded systems. By exploiting the potential of multicore architecture and the characteristic of streaming applications, we propose a twophase approach to solve the energy minimization problem for periodic dependent tasks on multicore processors with discrete voltage levels. With our approach, in the first phase, we propose a coarsegrained tasklevel software pipelining algorithm called RDAG to transform the periodic dependent tasks into a set of independent tasks based on the retiming technique (Leiserson and Saxe, Algorithmica 6:5–35, 1991). In the second phase, we propose two DVS scheduling algorithms for energy minimization. For singlecore processors, we propose a pseudopolynomial algorithm based on dynamic programming that can achieve optimal solution. For multicore processors, we propose a novel scheduling algorithm called SpringS which works like a spring and can effectively reduce energy consumption by iteratively adjusting task scheduling and voltage selection. We conduct experiments with a set of benchmarks from E3S (Dick 2008) and TGFF (http://ziyang.ece.northwestern.edu/tgff/) based on the power model of the AMD Mobile Athlon4 DVS processor. The experimental results show that our technique can achieve 12.7% energy saving compared with the algorithms in Zhang et al. (2002) on average.Journal of Signal Processing Systems 01/2009; 57:249262. · 0.55 Impact Factor
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