Routability driven white space allocation for fixed-die standard-cell placement

Abstract

The use of white space in fixed-die standard-cell placement is an effective way to improve routability. In this paper, we present a white space allocation approach that dynamically assigns white space according to the congestion distribution of the placement. In the topdown placement flow, white space is assigned to congested regions using a smooth allocating function. A post allocation optimization step is taken to further improve placement quality. Experimental results show that the proposed allocation approach, combined with a multilevel placement flow, significantly improves placement routability and layout quality.In our experiments, we compared our placement tool with two other fixed-die placers using an industrial place and route flow. Placements created by all three tools have been routed with an industrial router (Warp Route of Cadence). Compared with a leadingedge industrial tool, our placer produces placements with similar or better routability and on average 8.8% shorter routed wirelength. Furthermore, our tool produces placement that runs faster through the Warp Route compared with the industrial tool. Compared with a state-of-the-art academic placement tool (Capo/MetaPlacer), our placer shows ability to produce more routable placements: for 15 out of all 16 benchmarks our placer's outputs are routable while Capo/MetaPlacer only creates 4 routable placements.

Capo: Congestion-Driven Placement for Standard-cell and RTL Netlists with Incremental Capability

“…They chose the FastSteiner [22] evaluator for global placement based on its reasonable runtime and consistent performance on large nets. Empirical results show the use of FastSteiner leads to a reduction of StWL by 3% on average on the IBMv2 benchmarks [41] (with a reduction of routed wirelength up to 7%) while using less than 30% additional runtime [35].…”

“…Capo's overall performance was on par with commercial tools, however an ISPD 2002 paper [41] proposed a new set of benchmarks on which Capo was less successful compared to a newer tool, Dragon. Dragon found routable placements in most cases by building congestion maps and biasing the placement process accordingly.…”

Routability-driven placement and white space allocation

“…Unlike Dragon's two-step allocation approach [22], we assign appropriate amounts of white space to congested regions in a hierarchical flow. We first construct a slicing tree based on the geometric locations of all cells.…”

“…In [23], expansion of congested regions is formulated as an integer programming problem. Congestion-driven Dragon [22] allocates white space by two steps. White space is first distributed into rows and further into bins within a row.…”

“…Experiments show that it can significantly improve routability of placements generated by various latest placement tools. Combined with our global placement, we achieve placements with the best routability among the publicly available placement tools, with all IBM v2 easy and hard benchmark circuits [22] successfully routed .…”