52 citations · 54 across the 2 of their papers we have counts for
3 papers
cs.LG2022★ 52 cited
PrefixRL: Optimization of Parallel Prefix Circuits using Deep Reinforcement Learning
Rajarshi Roy, Jonathan Raiman, Neel Kant +6
In this work, we present a reinforcement learning (RL) based approach to designing parallel prefix circuits such as adders or priority encoders that are fundamental to high-perform…
cs.LG2021★ 2 cited
Guiding Global Placement With Reinforcement Learning
Robert Kirby, Kolby Nottingham, Rajarshi Roy +2
Recent advances in GPU accelerated global and detail placement have reduced the time to solution by an order of magnitude. This advancement allows us to leverage data driven optimi…
cs.LG2019
Can -Learning with Graph Networks Learn a Generalizable Branching Heuristic for a SAT Solver?
Vitaly Kurin, Saad Godil, Shimon Whiteson +1
We present Graph--SAT, a branching heuristic for a Boolean SAT solver trained with value-based reinforcement learning (RL) using Graph Neural Networks for function approximation…