CoEvoP&R addresses limitations with a large language model (LLM)-based framework that automatically evolves analytical placement objectives and reduces post-route routed wirelength and congestion across eight ChiP-Bench Nangate45 designs and three seeds.
Ruogu Chen, W. Xiao, Ramesh Karri et al.· arXiv.org· 0 citations
Can large language models generate not just correct, but fast hardware? This paper investigates the question in financial FPGA design, where 5-10 nanoseconds of latency determines competitive advantage and designs iterate continuously as protocols, strategies, and regulations evolve. FinHardBench, a benchmark of 33 fin...
Weimin Fu, He-Jia Zhang, Ming-Hao Shao et al.· 0 citations
A unified analysis of attacks on chiplet systems, the integration of Large Language Models into Electronic Design Automation (EDA) flows, and how LLM systems can advance hardware security efforts for modern systems, including chiplets is provided.
J. Knechtel, Ozgur Sinanoglu, Paul V. Gratz et al.· 0 citations
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