14 citations · 52 across the 21 of their papers we have counts for
4 papers · 1 filter
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…
Retrieval-Guided Reinforcement Learning for Boolean Circuit Minimization
Animesh Basak Chowdhury, Marco Romanelli, Benjamin Tan +2
Logic synthesis, a pivotal stage in chip design, entails optimizing chip specifications encoded in hardware description languages like Verilog into highly efficient implementations…
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…
Too Big to Fail? Active Few-Shot Learning Guided Logic Synthesis
Animesh Basak Chowdhury, Benjamin Tan, Ryan Carey +3
Generating sub-optimal synthesis transformation sequences ("synthesis recipe") is an important problem in logic synthesis. Manually crafted synthesis recipes have poor quality. Sta…