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Efficient System Design using the Statistical Analysis of Architectural Bottlenecks Methodology

By Manish Arora, Feng Wang, Bob Rychlik and Dean M. Tullsen


Abstract—CPU processor design involves a large set of increasingly complex design decisions Doing full, accurate simulation of all possible designs is typically not feasible. Prior techniques for sensitivity analysis seek to identify the most critical design parameters, but also struggle to handle the increasing design space well. They can be overly sensitive to the starting fixed point of the design, can still require a large number of simulations, and do not necessarily account for the cost of each design parameter. The Statistical Analysis of Architectural Bottlenecks (SAAB) methodology simultaneously analyzes multiple parameters and requires a small number of experiments. SAAB leverages the Plackett and Burman analysis method, but builds upon the technique in two specific ways. It allows a parameter to take multiple values and replaces the unit-less impact factor with a cost-proportional impact value. This paper applies the SAAB methodology to the design of a mobile processor sub-system. It considers area and power cost models for the design

Topics: Index Terms—Plackett and Burman, Bottleneck Analysis, Cost Optimized Design
Year: 2013
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