使用分层数据流的算法和架构级设计空间探索

H. P. Peixoto, M. Jacome
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引用次数: 15

摘要

在设计过程的早期阶段整合算法和架构关卡设计空间探索可以对最终系统的面积、速度和功耗产生巨大影响。本文提出了一个支持系统级设计空间探索的框架,并讨论了有效支持这种早期设计空间探索所涉及的三个基本问题:适当抽象级别的定义;高保真度系统级指标的定义;并定义了自动化探索过程的机制。第一个问题,即适当的抽象级别的定义,然后详细讨论。具体来说,提出了算法级模型、体系结构级模型和这些模型上的一组操作,旨在有效地支持早期的、积极的系统级设计空间探索。对其他两个主题(度量和自动化)中正在进行的工作进行了讨论,从而结束了本文。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Algorithm and architecture-level design space exploration using hierarchical data flows
Incorporating algorithm and architecture level design space exploration in the early phases of the design process can have a dramatic impact on the area, speed, and power consumption of the resulting systems. This paper proposes a framework for supporting system-level design space exploration and discusses the three fundamental issues involved in effectively supporting such an early design space exploration: definition of an adequate level of abstraction; definition of good fidelity system-level metrics; and definition of mechanisms for automating the exploration process. The first issue, the definition of an adequate level of abstraction is then addressed in detail. Specifically, an algorithm-level model, an architecture-level model, and a set of operations on these models, are proposed, aiming at efficiently supporting an early, aggressive system-level design space exploration. A discussion on work in progress in the other two topics, metrics and automation, concludes the paper.
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