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Handbook of algorithms for physical design automation part 63

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Handbook of Algorithms for Physical Design Automation part 63 provides a detailed overview of VLSI physical design automation, emphasizing state-of-the-art techniques, trends and improvements that have emerged during the previous decade. After a brief introduction to the modern physical design problem, basic algorithmic techniques, and partitioning, the book discusses significant advances in floorplanning representations and describes recent formulations of the floorplanning problem. The text also addresses issues of placement, net layout and optimization, routing multiple signal nets, manufacturability, physical synthesis, special nets, and designing for specialized technologies. It includes a personal perspective from Ralph Otten as he looks back on. | 602 Handbook of Algorithms for Physical Design Automation have at least one pin inside a bin to the perimeter of the bin SPK03 . This metric ignores the routing demand for all intrabin nets as well as the global wires routed through the bin that do not connect to any pin inside the bin. It captures the expected congestion at the boundary of the bin rather than that within the bin in contrast to the pin density metric. However this metric lends itself to very efficient approximation using Rent s rule LR71 . 30.3.2 Probabilistic Estimation Methods Probabilistic estimation methods also referred to as stochastic methods have been developed as a fast way to approximate the behavior of global routers. Instead of attempting to find a unique route for each net probabilistic estimation methods assume that all reasonable routes for a net are equally likely and consider all these routes while computing the congestion contribution of a net to the bins that it may be routed through. Different flavors of probabilistic congestion maps use different notions for what constitutes a reasonable route. Because probabilistic estimation techniques avoid choosing between the different routes possible for a given net or even enumerating these routes they also avoid the combinatorial optimization problem that a global router attempts to solve while routing the nets. In particular probabilistic estimation is independent of the order in which the nets are considered. As a result these techniques are considerably faster than global routing. However this computational efficiency is obtained at the cost of accuracy real-world global routers can diverge significantly from the simple routing behavior that these techniques model. Yet in spite of all the inaccuracies in probabilistic congestion map estimation these techniques are good candidates for use during the later stages of placement. To model the behavior of routers probabilistic estimation techniques consider shortest path routes because .