Dynamic Pipeline Scaling

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Title: Dynamic Pipeline Scaling
Author: Ramrakhyani, Prakash Shyamlal
Advisors: Dr. Alexander G. Dean, Committee Member
Dr. Wm. Rhett Davis, Committee Member
Dr. Thomas M. Conte, Committee Member
Dr. Eric Rotenberg, Committee Chair
Abstract: The classic problem of balancing power and performance continues to exist, as technology progresses. Fortunately, high performance is not a constant requirement in a system. When the performance requirement is not at its peak, the processor can be configured to conserve power, while providing just enough performance. Parameters like voltage, frequency, and cache structure have been proposed to be made dynamically scalable, to conserve power. This thesis analyzes the effects of dynamically scaling a new processor parameter, pipeline depth. We propose Dynamic Pipeline Scaling, a technique to conserve energy at low frequencies when voltage is invariable. When frequency can be lowered enough, adjacent pipeline stages can be merged to form a shallow pipeline. At equal voltage and frequency, the shallow pipeline is more energy-efficient than the deep pipeline. This is because the shallow pipeline has fewer data dependence stalls and a lower branch misprediction penalty. Thus, there are fewer wasteful transitions in a shallow pipeline, which translates directly to lower energy consumption. On a variable-voltage processor, the shallow pipeline requires a higher operating voltage than the deep pipeline for the same frequency. Since energy depends on the square of voltage and depends linearly on the total number of transitions, on a variable-voltage processor, a deep pipeline is typically more energy-efficient than a shallow pipeline. However, there may be situations where variable voltage is not desired. For example, if the latency to switch voltage is large, voltage scaling may not be beneficial in a real-time system with tight deadlines. On such a system, dynamic pipeline scaling can yield energy benefits, in spite of not scaling voltage.
Date: 2003-06-04
Degree: MS
Discipline: Computer Engineering
URI: http://www.lib.ncsu.edu/resolver/1840.16/2106


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