5 papers
LLM4RTL: Tool-Assisted LLM for RTL Generation
Jing Jin, Robert Chu, Ning Yan +1
Large language models (LLMs) have facilitated impressive progress in software engineering, code generation, tooling, and systems. Concurrently, a significant body of research has d…
AlloyVAE: A generative model for complex probabilistic field-to-field relationships in alloys
Ningyu Yan, Zhuocheng Xie, Kai Guo +3
The inherent compositional heterogeneity of multi-principal element alloys (MPEAs) gives rise to complex, spatially varying mechanical fields that cannot be uniquely determined fro…
CORE: Constraint-Aware One-Step Reinforcement Learning for Simulation-Guided Neural Network Accelerator Design
Yifeng Xiao, Yurong Xu, Ning Yan +2
Simulation-based design space exploration (DSE) aims to efficiently optimize high-dimensional structured designs under complex constraints and expensive evaluation costs. Existing…
Inverse Design in Distributed Circuits Using Single-Step Reinforcement Learning
Jiayu Li, Masood Mortazavi, Ning Yan +2
The goal of inverse design in distributed circuits is to generate near-optimal designs that meet a desirable transfer function specification. Existing design exploration methods us…
Theta-Resonance: A Single-Step Reinforcement Learning Method for Design Space Exploration
Masood S. Mortazavi, Tiancheng Qin, Ning Yan
Given an environment (e.g., a simulator) for evaluating samples in a specified design space and a set of weighted evaluation metrics -- one can use Theta-Resonance, a single-step M…