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cs.LG2024★ 7 cited
Make Every Move Count: LLM-based High-Quality RTL Code Generation Using MCTS
Matthew DeLorenzo, Animesh Basak Chowdhury, Vasudev Gohil +4
Existing large language models (LLMs) for register transfer level code generation face challenges like compilation failures and suboptimal power, performance, and area (PPA) effici…
cs.LG2023
Towards the Imagenets of ML4EDA
Animesh Basak Chowdhury, Shailja Thakur, Hammond Pearce +2
Despite the growing interest in ML-guided EDA tools from RTL to GDSII, there are no standard datasets or prototypical learning tasks defined for the EDA problem domain. Experience…