使用架构瓶颈统计分析方法进行有效的系统设计

Manish Arora, Feng Wang, Bob Rychlik, D. Tullsen
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引用次数: 2

摘要

CPU处理器设计涉及大量日益复杂的设计决策,对所有可能的设计进行全面、准确的模拟通常是不可行的。先前的灵敏度分析技术试图确定最关键的设计参数,但也难以处理越来越大的设计空间。它们可能对设计的起始固定点过于敏感,可能仍然需要大量的模拟,并且不一定考虑到每个设计参数的成本。结构瓶颈统计分析(SAAB)方法同时分析多个参数,并且需要少量的实验。萨博利用了Plackett和Burman的分析方法,但以两种具体方式建立在该技术的基础上。它允许一个参数取多个值,并用成本比例影响值取代无单位影响因子。本文将SAAB方法应用于移动处理器子系统的设计。在设计时考虑了面积和功耗模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient system design using the Statistical Analysis of Architectural Bottlenecks methodology
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.
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