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RL for Placement and Partitioning

In: Machine Learning Applications in Electronic Design Automation

Author

Listed:
  • Anna Goldie

    (Google Brain)

  • Azalia Mirhoseini

    (Google Brain)

Abstract

This chapter starts by describing the problem of chip placement, a time-consuming stage in the overall chip design process and a challenging combinatorial optimization problem. Next, this chapter delves briefly into the six decades of prior work on this important topic. The heart of the chapter is an overview of deep RL, a primer on how to formulate chip placement as a deep RL problem, and a detailed description of a recent RL-based approach to chip placement. The chapter concludes with a discussion of other applications for RL-based methods and their implications for the future of chip design.

Suggested Citation

  • Anna Goldie & Azalia Mirhoseini, 2022. "RL for Placement and Partitioning," Springer Books, in: Haoxing Ren & Jiang Hu (ed.), Machine Learning Applications in Electronic Design Automation, chapter 0, pages 205-220, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-13074-8_8
    DOI: 10.1007/978-3-031-13074-8_8
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