By Majid Sarrafzadeh
This article treats the actual layout of very huge scale built-in circuits progressively and systematically. It examines the layout challenge and the layout method with the purpose of comparing the potency of automated layout platforms via algorithmic research. The structure challenge is considered as a set of sub-problems that are separately solved successfully after which successfully mixed. Initially,the textual content experiences VLSI know-how after which examines format ideas and phone iteration innovations.
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Extra resources for An Introduction to VLSI Physical Design
Input format . The first line contains the grid size (the first coordinate is the x-coordinate) . The second line has coordinates of the source and the sink, and the rest of the lines contain coordinates of the obstacles . The northwest location is coordinate (0, 0) . The input format is : grid 5 4 s-t (1,4) (3,2) obs (2,2) (2,3) (3,3) Output format . 2. Consider a set of horizontal and vertical line segments in the plane . Design an algorithm for finding the maximum number of pairwise independent segments .
Next, design a more sophisticated algorithm for the same problem . Compare the running time and quality of the two algorithms . CHAPTER 2 THE TOP-DOWN APPROACH: PLACEMENT In this chapter, we discuss the top-down approach to the VLSI layout problem . The circuit layout problem is partitioned into a collection of subproblems . Each subproblem should be solved efficiently to make subsequent steps easy . There are two major subproblems, placement and routing . This chapter focuses on the placement problem and the next chapter focuses on the routing problem .
INTRODUCTION 21 Throughout this book, the quality and time complexity of various algorithms will be analyzed for a number of problems in VLSI layout . This will further illustrate the natural trade-off between quality and time complexity of algorithms . 8 ALGORITHMIC PARADIGMS As discussed, most layout problems are NP-hard, that is, they (most probably) require exponential time to be solved exactly . Because of the size of the problems involved, exponential time is not affordable . Alternatively, suboptimal algorithms, those that are fast and produce good quality solutions, have been designed .
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