晶体管级语言的通用操作框架

Nicola Dall'Ora, Sadia Azam, Enrico Fraccaroli, André Alberts, F. Fummi
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引用次数: 2

摘要

用于描述晶体管级设计的SPICE语言有很多后继语言。对于它们中的大多数,语义与SPICE的语义相匹配,只有语法发生了变化。其他公司则提供更多默认模型或分析工具。因此,通常需要一个商业工具来模拟、分析,特别是操作这些语言。本文提出了一个框架,该框架依赖于共享语义来读取、写入或操纵晶体管级设计。该框架的最终目标是:读取用特定语法编写的输入设计,然后允许用另一种语法编写相同的设计。首先,输入描述由特定于语言的前端解析,该前端将其转换为遵循公共语义的内存中的抽象语法树。然后,内存中的描述可以服从于构建在一系列API或访问者/侦听器类之上的不同的用户定义操作。最后,描述经过所需的后端,将内存中的描述转换为目标晶体管级语言。作为该框架的一个用例,我们选择了模拟故障注入过程。此活动需要添加、删除或替换节点、组件,甚至整个子电路。因此,该框架完全用c++编写,其api也与python接口。整个框架是开源的,可以在GitHub上获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Common Manipulation Framework for Transistor-Level Languages
There are plentiful successors of SPICE language for describing transistor-level designs. For most of them, the semantic matches those of SPICE, and only the syntax is changed. Others instead provide more default models or analysis tools. Consequently, a commercial tool is usually required for simulating, analyzing, and especially manipulating these languages. This article proposes a framework that relies on the shared semantic for reading, writing, or manipulating transistor-level designs. The ultimate goal of the framework is: reading an input design written in a specific syntax and then allowing to write the same design in another syntax. First, the input description is parsed by a language-specific front-end which turns it into an in-memory abstract syntax tree that follows the common semantic. Then, the in-memory description can be subject to different user-defined manipulations built on top of a series of API or visitor/listener classes. Finally, the description goes through the desired back-end, transforming the in-memory description into the target transistor-level language. As a use-case for the proposed framework, we chose the process of analog fault injection. This activity requires adding, removing, or replacing nodes, components, or even entire sub-circuits. Therefore, the framework is completely written in C++, and its APIs are also interfaced with python. The entire framework is open-source and available on GitHub.
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