ENERGY-CONSTRAINED VDD HOPPING SCHEME WITH RUN-TIME POWER ESTIMATION FOR LOW-POWER REAL-TIME VLSI SYSTEMS

2002 ◽  
Vol 11 (06) ◽  
pp. 601-620 ◽  
Author(s):  
SEONGSOO LEE ◽  
SEUNGJUN LEE ◽  
TAKAYASU SAKURAI
Keyword(s):  
Power Consumption ◽  
Low Power ◽  
Supply Voltage ◽  
Voltage Scaling ◽  
Dynamic Voltage Scaling ◽  
Multimedia Applications ◽  
Variable Voltage ◽  
Dynamic Voltage ◽  
Energy Constrained ◽  
Variable Voltage Processor

In this paper, we propose a novel dynamic voltage scaling algorithm on a variable-voltage processor. It determines the supply voltage on timeslot-by-timeslot basis within the task boundary, and significantly reduces the power consumption by fully exploiting the slack time. Also, we modify this algorithm and propose an energy-constrained dynamic voltage scaling algorithm for low-power multimedia applications. In the multimedia applications, there are usually several alternative algorithms with different performance and power. Considering the trade-off between performance and power, the proposed algorithm adaptively determines the optimal alternative to achieve optimal performance under given energy constraint. Compared with the conventional algorithms, the power consumption is reduced to 1/14.4 ~ 1/5.6 without performance degradation.

Application-Support Particle Filter for Dynamic Voltage Scaling of Multimedia Applications

2012 ◽  
Vol 61 (9) ◽  
pp. 1256-1269 ◽  
Author(s):  
Jae-Beom Lee ◽  
Myoung-Jin Kim ◽  
Sungroh Yoon ◽  
Eui-Young Chung
Keyword(s):  
Particle Filter ◽  
Voltage Scaling ◽  
Dynamic Voltage Scaling ◽  
Multimedia Applications ◽  
Support Particle ◽  
Dynamic Voltage

scholarly journals Dynamic Voltage Scaling With Reduced Frequency Switching And Preemptions

2012 ◽  
pp. 10-14
Author(s):  
Arya Lekshmi Mohan ◽  
Anju S. Pillai
Keyword(s):  
Power Consumption ◽  
Power Management ◽  
Voltage Scaling ◽  
Dynamic Voltage Scaling ◽  
Discrete Frequency ◽  
Cpu Time ◽  
Innovative Technique ◽  
Reduced Frequency ◽  
Dynamic Voltage

Dynamic Voltage Scaling is an innovative technique for reducing the power consumption of a processor by utilizing its hardware functionality. Dynamic Voltage Scaling processors are mainly focusing on power management. Such processors can be switch between discrete frequency and voltage levels. The main challenges of Dynamic Voltage Scaling are increased number of preemptions and frequency switching. A part of dynamic energy as well as CPU time is lost due to these processes. To limit such processes, an algorithm is proposed which reduces both unwanted frequency switching and preemptions.

scholarly journals LOW POWER SYSTEM DESIGN BY COMBINING SOFTWARE PREFETCHING AND DYNAMIC VOLTAGE SCALING

2007 ◽  
Vol 16 (05) ◽  
pp. 745-767
Author(s):  
SUMITKUMAR N. PAMNANI ◽  
DEEPAK N. AGARWAL ◽  
GANG QU ◽  
DONALD YEUNG
Keyword(s):  
Energy Consumption ◽  
Low Power ◽  
Energy Saving ◽  
System Performance ◽  
Performance Enhancement ◽  
Voltage Scaling ◽  
Dynamic Voltage Scaling ◽  
Dynamic Voltage ◽  
Software Prefetching ◽  
Online Profiling

Performance-enhancement techniques improve CPU speed at the cost of other valuable system resources such as power and energy. Software prefetching is one such technique, tolerating memory latency for high performance. In this article, we quantitatively study this technique's impact on system performance and power/energy consumption. First, we demonstrate that software prefetching achieves an average of 36% performance improvement with 8% additional energy consumption and 69% higher power consumption on six memory-intensive benchmarks. Then we combine software prefetching with a (unrealistic) static voltage scaling technique to show that this performance gain can be converted to an average of 48% energy saving. This suggests that it is promising to build low power systems with techniques traditionally known for performance enhancement. We thus propose a practical online profiling based dynamic voltage scaling (DVS) algorithm. The algorithm monitors system's performance and adapts the voltage level accordingly to save energy while maintaining the observed system performance. Our proposed online profiling DVS algorithm achieves 38% energy saving without any significant performance loss.

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