Presentation
Diffsp: Differentiable Sequence Pair-Based Analog Placement
DescriptionAnalog placement with compact representations is traditionally solved using heuristic or simulated annealing methods that are difficult to integrate with a differentiable optimization engine.
This paper introduces DiffSP, a differentiable sequence-pair-based analog placement method that bridges discrete combinatorial representation with continuous gradient optimization.
We derive a smooth relaxation of the sequence pair constraint graph via Gumbel–Sinkhorn relaxation, which allows area, wirelength, and symmetry objectives to be jointly optimized via automatic gradient calculation.
A MILP-based legalization stage then enforces exact geometric and symmetry constraints.
Experiments on industrial-level OTA benchmarks show that DiffSP achieves better placement quality and post-layout performance metrics than state-of-the-art analog placers with significantly reduced runtime.
This paper introduces DiffSP, a differentiable sequence-pair-based analog placement method that bridges discrete combinatorial representation with continuous gradient optimization.
We derive a smooth relaxation of the sequence pair constraint graph via Gumbel–Sinkhorn relaxation, which allows area, wirelength, and symmetry objectives to be jointly optimized via automatic gradient calculation.
A MILP-based legalization stage then enforces exact geometric and symmetry constraints.
Experiments on industrial-level OTA benchmarks show that DiffSP achieves better placement quality and post-layout performance metrics than state-of-the-art analog placers with significantly reduced runtime.
Event Type
Research Manuscript
TimeWednesday, July 294:30pm - 4:42pm PDT
LocationMtg Room 101B