mlsanityData to 7 Oct 2026

DRiLLS: Deep Reinforcement Learning for Logic Synthesis

arXiv 1911.04021 ↗First posted 11 Nov 2019cs.AI cs.LG cs.NEcited by 47

Not on the map. Why?

Abstract (arXiv)

Logic synthesis requires extensive tuning of the synthesis optimization flow where the quality of results (QoR) depends on the sequence of optimizations used. Efficient design space exploration is challenging due to the exponential number of possible optimization permutations. Therefore, automating the optimization process is necessary. In this work, we propose a novel reinforcement learning-based methodology that navigates the optimization space without human intervention. We demonstrate the training of an Advantage Actor Critic (A2C) agent that seeks to minimize area subject to a timing constraint. Using the proposed methodology, designs can be optimized autonomously with no-humans in-loop. Evaluation on the comprehensive EPFL benchmark suite shows that the agent outperforms existing exploration methodologies and improves QoRs by an average of 13%.

Key facts. Cited by 47 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Nov 2019.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 5; 2022: 12; 2023: 9; 2024: 13; 2025: 5; 2026: 3.

47 papers.

Sort:

By area:

  1. 2021Machine Learning for Electronic Design Automation: A Surveycited by 71
  2. 2021A Survey of Machine Learning for Computer Architecture and Systemscited by 53
  3. 2023LLM4EDA: Emerging Progress in Large Language Models for Electronic Design Automationcited by 40
  4. 2021OpenABC-D: A Large-Scale Dataset For Machine Learning Guided Integrated Circuit Synthesiscited by 30
  5. 2021BOiLS: Bayesian Optimisation for Logic Synthesiscited by 18
  6. 2023Advanced Large Language Model (LLM)-Driven Verilog Development: Enhancing Power, Performance, and Area Optimization in Code Synthesiscited by 14
  7. 2022Pretraining Graph Neural Networks for few-shot Analog Circuit Modeling and Designcited by 13
  8. 2022DevFormer: A Symmetric Transformer for Context-Aware Device Placementcited by 11
  9. 2022DeepTPI: Test Point Insertion with Deep Reinforcement Learningcited by 10
  10. 2024Retrieval-Guided Reinforcement Learning for Boolean Circuit Minimizationcited by 10
  11. 2024Scalable and Effective Arithmetic Tree Generation for Adder and Multiplier Designscited by 9
  12. 2022LOSTIN: Logic Optimization via Spatio-Temporal Information with Hybrid Graph Modelscited by 7
35 more
  1. 2023A Circuit Domain Generalization Framework for Efficient Logic Synthesis in Chip Designcited by 6
  2. 2024Circuit Transformer: A Transformer That Preserves Logical Equivalencecited by 5
  3. 2025LLM-VeriPPA: Power, Performance, and Area Optimization aware Verilog Code Generation with Large Language Modelscited by 5
  4. 2023AISYN: AI-driven Reinforcement Learning-Based Logic Synthesis Frameworkcited by 4
  5. 2024Logic Synthesis with Generative Deep Neural Networkscited by 4
  6. 2024MapTune: Advancing ASIC Technology Mapping via Reinforcement Learning Guided Library Tuningcited by 4
  7. 2022Reinforcement Learning for Hardware Security: Opportunities, Developments, and Challengescited by 3
  8. 2023INVICTUS: Optimizing Boolean Logic Circuit Synthesis via Synergistic Learning and Searchcited by 3
  9. 2024OpenLS-DGF: An Adaptive Open-Source Dataset Generation Framework for Machine Learning Tasks in Logic Synthesiscited by 3
  10. 2025VeriLoC: Line-of-Code Level Prediction of Hardware Design Quality from Verilog Codecited by 3
  11. 2022Rethinking Reinforcement Learning based Logic Synthesiscited by 2
  12. 2023Adaptive Reconvergence-driven AIG Rewriting via Strategy Learningcited by 2
  13. 2024BoolGebra: Attributed Graph-learning for Boolean Algebraic Manipulationcited by 2
  14. 2024ShortCircuit: AlphaZero-Driven Circuit Designcited by 2
  15. 2024MTLSO: A Multi-Task Learning Approach for Logic Synthesis Optimizationcited by 2
  16. 2022Too Big to Fail? Active Few-Shot Learning Guided Logic Synthesiscited by 1
  17. 2022HybMT: Hybrid Meta-Predictor based ML Algorithm for Fast Test Vector Generationcited by 1
  18. 2022The prediction of the quality of results in Logic Synthesis using Transformer and Graph Neural Networkscited by 1
  19. 2022Neural Combinatorial Logic Circuit Synthesis from Input-Output Examplescited by 1
  20. 2023Towards the Imagenets of ML4EDAcited by 1
  21. 2024Logic Synthesis Optimization with Predictive Self-Supervision via Causal Transformerscited by 1
  22. 2024Boolean-aware Boolean Circuit Classification: A Comprehensive Study on Graph Neural Networkcited by 1
  23. 2025Graph Neural Networks for Automatic Addition of Optimizing Components in Printed Circuit Board Schematicscited by 1
  24. 2026Report for NSF Workshop on AI for Electronic Design Automationcited by 1
  25. 2021Reinforcement Learning for Scalable Logic Optimization with Graph Neural Networkscited by 0
  26. 2022The Dark Side: Security Concerns in Machine Learning for EDAcited by 0
  27. 2022Intelligent Circuit Design and Implementation with Machine Learningcited by 0
  28. 2023Statistical Hardware Design With Multi-model Active Learningcited by 0
  29. 2023GraPhSyM: Graph Physical Synthesis Modelcited by 0
  30. 2024An Open-source End-to-End Logic Optimization Framework for Large-scale Boolean Network with Reinforcement Learningcited by 0
  31. 2024ASCENT: Amplifying Power Side-Channel Resilience via Learning & Monte-Carlo Tree Searchcited by 0
  32. 2025QiMeng: Fully Automated Hardware and Software Design for Processor Chipcited by 0
  33. 2025GENIAL: Generative Design Space Exploration via Network Inversion for Low Power Algorithmic Logic Unitscited by 0
  34. 2026SynAct: A Reasoning-Acting Large Language Model Agent for Adaptive Synthesis Optimizationcited by 0
  35. 2026SKILL: Self-correcting Knowledge-guided Iterative Large Language Model Agent for Logic Optimizationcited by 0