The increasing use of Advanced Language Models (ALMs) in diverse sectors,
particularly due to their impressive capability to generate top-tier content
following linguistic instructions, forms the core of this investigation. This
study probes into ALMs' deployment in electronic hardware design, with a
specific emphasis on the synthesis and enhancement of Verilog programming. We
introduce an innovative framework, crafted to assess and amplify ALMs'
productivity in this niche. The methodology commences with the initial crafting
of Verilog programming via ALMs, succeeded by a distinct dual-stage refinement
protocol. The premier stage prioritizes augmenting the code's operational and
linguistic precision, while the latter stage is dedicated to aligning the code
with Power-Performance-Area (PPA) benchmarks, a pivotal component in proficient
hardware design. This bifurcated strategy, merging error remediation with PPA
enhancement, has yielded substantial upgrades in the caliber of ALM-created
Verilog programming. Our framework achieves an 81.37% rate in linguistic
accuracy and 62.0% in operational efficacy in programming synthesis, surpassing
current leading-edge techniques, such as 73% in linguistic accuracy and 46% in
operational efficacy. These findings illuminate ALMs' aptitude in tackling
complex technical domains and signal a positive shift in the mechanization of
hardware design operations.

通过一种创新的框架，本研究探索了高级语言模型在电子硬件设计中的应用，特别关注了 Verilog 编程的综合和增强；该框架通过初始通过高级语言模型生成的 Verilog 编程，然后经过两个独立的改进阶段，优化编程的运行效率和语言准确性，并与关键的性能指标进行对齐，从而大幅提升 ALMs 生成的 Verilog 编程的质量，展示出 ALMs 在处理复杂技术领域方面的能力，标志着硬件设计操作的自动化迈出积极的一步。