The development of architecture specifications is an initial and fundamental
stage of the integrated circuit (IC) design process. Traditionally,
architecture specifications are crafted by experienced chip architects, a
process that is not only time-consuming but also error-prone. Mistakes in these
specifications may significantly affect subsequent stages of chip design.
Despite the presence of advanced electronic design automation (EDA) tools,
effective solutions to these specification-related challenges remain scarce.
Since writing architecture specifications is naturally a natural language
processing (NLP) task, this paper pioneers the automation of architecture
specification development with the advanced capabilities of large language
models (LLMs). Leveraging our definition and dataset, we explore the
application of LLMs in two key aspects of architecture specification
development: (1) Generating architecture specifications, which includes both
writing specifications from scratch and converting RTL code into detailed
specifications. (2) Reviewing existing architecture specifications. We got
promising results indicating that LLMs may revolutionize how these critical
specification documents are developed in IC design nowadays. By reducing the
effort required, LLMs open up new possibilities for efficiency and accuracy in
this crucial aspect of chip design