IEEE MLCAD 2025 Symposium Submissions

EDA Tool Parameter Optimization Through Fast and Reliable Machine-Learning based Rank Prediction Model
Doyeon Won, Taewhan Kim
- Published: 08 Jul 2025, Last Modified: 08 Jul 2025
- MLCAD 2025
- Readers: Everyone
Context-Enhanced Architectural Specification Generation for SoC Designs
Md Rubel Ahmed, Sadiba Nusrat Nur, Rickard Ewetz
- Published: 08 Jul 2025, Last Modified: 08 Jul 2025
- MLCAD 2025
- Readers: Everyone
hdl2v: A Code Translation Dataset for Enhanced LLM Verilog Generation
Charles Hong, Brendan Roberts, Huijae An, Alex Um, Advay Ratan, Sophia Shao
- Published: 08 Jul 2025, Last Modified: 08 Jul 2025
- MLCAD 2025
- Readers: Everyone
BeyondPPA: Human-Inspired Reinforcement Learning for Post-Route Reliability Aware Macro Placement
Ishraq Tashdid, Valentina Terry, Jordan Merkel, Tasnuva Farheen, Sazadur Rahman
- Published: 08 Jul 2025, Last Modified: 08 Jul 2025
- MLCAD 2025
- Readers: Everyone
LASSO: LLM-Aided Security Property Generation for Assertion-based SoC Verification
Dinesh Reddy Ankireddy, Sudipta Paria, Aritra Dasgupta, Sandip Ray, Swarup Bhunia
- Published: 08 Jul 2025, Last Modified: 08 Jul 2025
- MLCAD 2025
- Readers: Everyone
Multimodal Learning-Based Thermal Solver for 3DICs with Arbitrary Chip Dimensions and Power Distributions
Zelin Lu, Akhilesh Kumar, Norman Chang, Haiyang He, LANG LIN, Wenbo Xia, Jie Yang, Gang Qu
- Published: 08 Jul 2025, Last Modified: 08 Jul 2025
- MLCAD 2025
- Readers: Everyone
ML-Enhanced Performance and Power Estimation for DNNs on Heterogeneous SoCs
Surya Selvam, Jacob R. Stevens, Sujit Dey, Anand Raghunathan
- Published: 08 Jul 2025, Last Modified: 08 Jul 2025
- MLCAD 2025
- Readers: Everyone
Prompting for Power: Benchmarking Large Language Models for Low-Power RTL Design Generation
Kevin Immanuel Gubbi, Marcus Halm, Sarbani Kumar, Arvind Sudarshan, Pavan Dheeraj Kota, Mohammadnavid Tarighat, Avesta Sasan, Houman Homayoun
- Published: 08 Jul 2025, Last Modified: 08 Jul 2025
- MLCAD 2025
- Readers: Everyone
LLM-VeriPPA: Power, Performance, and Area Optimization aware Verilog Code Generation with Large Language Models
Kiran Thorat, Jiahui Zhao, Yaotian Liu, Amit Hasan, Hongwu Peng, Xi Xie, Bin Lei, Caiwen Ding
- Published: 08 Jul 2025, Last Modified: 08 Jul 2025
- MLCAD 2025
- Readers: Everyone
Hybrid-NL2SVA: Integrating RAG and Finetuning for LLM-based NL2SVA
Weihua Xiao, Derek Ekberg, Siddharth Garg, Ramesh Karri
- Published: 08 Jul 2025, Last Modified: 08 Jul 2025
- MLCAD 2025
- Readers: Everyone
ArchXBench: A Complex Digital Systems Benchmark Suite for LLM Driven RTL Synthesis
Suresh Purini, Siddhant Garg, Mudit Gaur, Sankalp Bhat, Sohan Mupparapu, Arun Ravindran
- Published: 08 Jul 2025, Last Modified: 08 Jul 2025
- MLCAD 2025
- Readers: Everyone
HR$^2$: A PVT Aware Hierarchical RL Based Sizing Framework for Robust Analog Circuit Design
Jaeheon Jung, Dongwoo Lew, JangSeok Yu, Jongsun Park
- Published: 08 Jul 2025, Last Modified: 08 Jul 2025
- MLCAD 2025
- Readers: Everyone
Mapping Fusion: Improving FPGA Technology Mapping with ASIC Mapper
CUNXI YU
- Published: 09 Jul 2025, Last Modified: 09 Jul 2025
- MLCAD 2025
- Readers: Everyone
Priority-Aware Routing Optimization with Full-Path Delay Prediction Using Machine Learning
Hyunmin Jo, Heechun Park
- Published: 08 Jul 2025, Last Modified: 08 Jul 2025
- MLCAD 2025
- Readers: Everyone
Recurrent CircuitSAT Sampling for Sequential Circuits
Arash Ardakani, Kevin He, John Wawrzynek
- Published: 08 Jul 2025, Last Modified: 08 Jul 2025
- MLCAD 2025
- Readers: Everyone
Post-Routing Path Statistical Delay Estimation Based on SGAT-GRU Prediction Framework
Jingjing Guo, Xuejie Ning, Suohang Yang, Jun Yang, Zhikuang Cai
- Published: 08 Jul 2025, Last Modified: 08 Jul 2025
- MLCAD 2025
- Readers: Everyone
ORFS-agent: Tool-Using Agents for Chip Design Optimization
Amur Ghose, Andrew Kahng, Sayak Kundu, Zhiang Wang
- Published: 08 Jul 2025, Last Modified: 08 Jul 2025
- MLCAD 2025
- Readers: Everyone
Netlistify: Transforming Circuit Schematics into Netlists with Deep Learning
Chun-Yen Huang, Hsuan-I Chen, Hao-Wen Ho, Pei-Hsin Kang, Mark Po-Hung Lin, Wen-Hao Liu, Haoxing Ren
- Published: 08 Jul 2025, Last Modified: 08 Jul 2025
- MLCAD 2025
- Readers: Everyone
TuRTLe: A Unified Evaluation of LLMs for RTL Generation
Dario Garcia-Gasulla, Gokcen Kestor, Emanuele Parisi, Miquel Albertí-Binimelis, Cristian Gutierrez, Razine Moundir Ghorab, Orlando Montenegro, Bernat Homs, Miquel Moreto
- Published: 08 Jul 2025, Last Modified: 08 Jul 2025
- MLCAD 2025
- Readers: Everyone
Trusting the Machine: How Secure is LLM-Generated RTL Code?
Zahin Ibnat, Paul E. Calzada, Dipayan Saha, Hasan Al-Shaikh, Sujan Kumar Saha, Jingbo Zhou, Farimah Farahmandi, Mark Tehranipoor
- Published: 08 Jul 2025, Last Modified: 08 Jul 2025
- MLCAD 2025
- Readers: Everyone
A Hybrid Optimization Framework for Power-Efficient Pulsed Latch Utilization in Clock Networks
Yuntao Lu, Dehua Liang, Siting Liu, Yuhao Ji, Yu Zhang, Xuanqi Chen, Xia Lin, Jinlei Lu, Weihua Sheng, Bei Yu
- Published: 08 Jul 2025, Last Modified: 08 Jul 2025
- MLCAD 2025
- Readers: Everyone
ScaleRTL: Scaling LLMs with Reasoning Data and Test-Time Compute for Accurate RTL Code Generation
Chenhui Deng, Yun-Da Tsai, Guan-Ting Liu, Zhongzhi Yu, Haoxing Ren
- Published: 08 Jul 2025, Last Modified: 08 Jul 2025
- MLCAD 2025
- Readers: Everyone
Pieceformer: Similarity-Driven Knowledge Transfer via Scalable Graph Transformer in VLSI
Hang Yang, Callie Hao, Yong Liu, Yusheng Hu
- Published: 08 Jul 2025, Last Modified: 08 Jul 2025
- MLCAD 2025
- Readers: Everyone
NeuroSim Agent: Automated Compute-in-Memory Accelerator Deployment with Transferable Reinforcement Learning and Dynamic Design Space Pruning
Ming-Yen Lee, Shimeng Yu
- Published: 08 Jul 2025, Last Modified: 08 Jul 2025
- MLCAD 2025
- Readers: Everyone
RTLExplain: A Structured Approach to RTL Code Summarization and Question Answering for Medium-to-Large Designs Using LLMs
Ting-Hsun Chi, Charles Mackin, Luyao Shi, Prashanth Vijayaraghavan, Hsinyu Tsai, Ehsan Degan
- Published: 08 Jul 2025, Last Modified: 08 Jul 2025
- MLCAD 2025
- Readers: Everyone