By Chieh Lin
"Mixed-Signal structure iteration innovations brings jointly many rules and methods required to effectively advance and enforce structure new release instruments to deal with many mixed-signal format new release wishes. not just does it offer a finished evaluation of cutting-edge suggestions, it additionally illustrates many options with intuitive examples and pseudo code. Altogether, it enables construction of perception right into a tremendous and complicated zone. when you are new to the world of mixed-signal format iteration, this publication offers a good creation to complicated issues during this zone. A training EDA researcher or software developer may well locate this publication an invaluable reference that mixes classical and new rules. additionally, this publication relates theories to one another and to pragmatic implementations. eventually, the dressmaker, or structure artist, to have an intensive figuring out of primary strategies in mixed-signal structure iteration, can benefit from the self-contained chapters during this publication.
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Additional info for Mixed-Signal Layout Generation Concepts
A recipe is given to derive a (near) optimal best-so-far temperature schedule. ‚ 2000] Cong et al. propose to use a dynamic weighting Monte Carlo approach for floorplanning; they obtain promising results. The essential difference in their approach is an SA algorithm with a stochastic temperature schedule. 2 Simulated Annealing 25 general fashion‚ we can state that function decrease_temperature (T) should be replaced by adjust_temperature (T) in order to maximize the power of SA. The generality of SA comes at the cost of a large amount of computational resources that are required for practical problems.
The following classification might not be optimal‚ but it is one that matches well with contemporary ideas. Furthermore‚ it provides a good impression of the vast body of research activities in this field. ‚ 2001]. 1 Deterministic Algorithms A deterministic algorithm is a recipe that describes which steps have to be taken sequentially‚ in order to transform a set of input values to a set of output values. For such an algorithm no random number generator is needed to execute and find a solution.
We only mention a few interesting concepts and approaches. In [ Boese and Kahng‚ 1994] Boese and Kahng observe that under finite-time conditions‚ the classical monotonically decreasing temperature schedule is not optimal when the best solution seen so far is the output of the SA algorithm‚ as opposed to the last solution seen (that is accepted). A recipe is given to derive a (near) optimal best-so-far temperature schedule. ‚ 2000] Cong et al. propose to use a dynamic weighting Monte Carlo approach for floorplanning; they obtain promising results.
Mixed-Signal Layout Generation Concepts by Chieh Lin