Research in floorplanning and block-packing has generated a variety of data structures to represent spatial configurations of circuit modules. Much of this work focuses on the geometry of module shapes and seeks tighter packing, as well as improvements in the asymptotic worst-case complexity of algorithms for standard tasks. In this work we consider the implications of interconnect optimization on the value of floorplan representations and establish a framework for comparing different representations. By analyzing performance bottlenecks in block packing and properties of floorplan representations, we show that many of the mathematical results in floorplanning do not translate into better VLSI layouts. This is confirmed by extensive empirical data for stand-alone floorplanners and integrated applications.

We propose a new floorplanner BloBB based on multi-level branch-andbound. It is competitive with annealers in terms of runtime and solution quality. We empirically quantify the gap between optimal slicing and non-slicing floorplans by comparing optimal packings and best seen results. Optimal slicing and non-slicing packings for apte, xerox and hp are reported. We also discover that the soft versions of all MCNC benchmarks, except for apte, and all GSRC benchmarks can be packed with zero dead-space.Additionally, realistic floorplans often have blocks with similar dimensions, if design blocks, such as memories, are reused. We show that this greatly reduces the complexity of black-packing.

This paper describes a method of interactively visualizing and directing the process of translating a sentence. The method allows a user to explore a model of syntax-based statistical machine translation (MT), to understand the model's strengths and weaknesses, and to compare it to other MT systems. Using this visualization method, we can find and address conceptual and practical problems in an MT system. In our demonstration at ACL, new users of our tool will drive a syntaxbased decoder for themselves.

In this invited note we describe Capo, an open-source software tool for cell placement, mixed-size placement and floorplanning with emphasis on routability. Capo is among the fastest academic placers and scales to millions of movable objects. This note surveys the overall structure of Capo, discusses recent improvements and describes ongoing research.