Starfish: An Efficient P&R Co-Optimization Engine with A*-based Partial Rerouting

Abstract

Placement and routing (P&R) are two important stages in the physical design flow. After circuit components are assigned locations by a placer, routing will take place to make the connections. Defined as two separate problems, placement and routing aim to optimize different objectives. For instance, placement usually focuses on optimizing the half-perimeter wire length (HPWL) and estimated congestion while routing will try to minimize the routed wire length and the number of overflows. The misalignment between the objectives will inevitably lead to a significant degradation in solution quality. Therefore, in this paper, we present Starfish, an efficient P&R co-optimization engine that bridges the gap between placement and routing. To incrementally optimize the routed wire length, Starfish conducts cell movements and reconnects broken nets by A*-based partial rerouting. Experimental results on the ICCAD 2020 contest benchmark suites [1] show that our co-optimizer outperforms all the contestants with better solution quality and much shorter runtime.