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Starts 6 June 2025 12:09

Ends 6 June 2025

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Language Model Guided Synthesis for Lifting

Explore how language models and program synthesis can be combined to automatically lift code to domain-specific languages, enabling efficient code generation for heterogeneous hardware.
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Simons Institute

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48 minutes

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Overview

Explore how language models and program synthesis can be combined to automatically lift code to domain-specific languages, enabling efficient code generation for heterogeneous hardware.

Syllabus

  • Introduction to Language Models and Program Synthesis
  • Overview of Language Models in AI
    Fundamentals of Program Synthesis
    Applications in Code Generation
  • Basics of Domain-Specific Languages (DSLs)
  • Understanding DSLs: Definitions and Characteristics
    Benefits of Using DSLs in Code Generation
    Examples of Popular DSLs
  • Language Models for Code Generation
  • Historical Context and Evolution
    State-of-the-Art Language Models
    Case Studies of Language Models in Code Generation
  • Program Synthesis Techniques
  • Syntax-Guided Synthesis
    Inductive Program Synthesis
    Machine Learning Approaches to Synthesis
  • Integration of Language Models and Program Synthesis
  • Synergies between Language Models and Synthesis
    Frameworks and Tools for Integration
    Challenges in Integrating Language Models with Synthesis
  • Lifting Code to Domain-Specific Languages
  • Techniques for Code Lifting
    Automation of DSL Code Generation
    Optimizing for Heterogeneous Hardware
  • Practical Applications and Case Studies
  • Real-world Examples of Code Lifting
    Industry Adoption and Use Cases
    Comparative Analysis of DSLs in Different Domains
  • Hands-on Project
  • Selecting a Domain-Specific Language
    Applying Language Model Guided Synthesis
    Evaluating Performance on Heterogeneous Hardware
  • Future Directions in Language Model Guided Synthesis
  • Trends and Emerging Research
    Opportunities for Innovation in This Field
    Long-term Impact on Software Development
  • Review and Course Conclusion
  • Recap of Key Concepts
    Discussion on Potential Advances
    Feedback and Course Evaluation

Subjects

Computer Science