liew@ARAMIS.RUTGERS.EDU.UUCP (03/26/87)
The next design colloquim will be held on Thursday (march 26th) at 1:30pm in TCB 103. Most of you are unfamiliar with the location of TCB 103 so we will meet at Hill 423 at 1:15 and proceed from there. The speaker will be Wayne Wolf of ATT Bell Laboratories and the title of his talk is "Artificial Intelligence, Mathematical Programming and VLSI Design". The suggested readings are: Wolf, Kowalski, McFarland "Knowledge Engineering Issues in VLSI Synthesis", AAAI-86. Brayton, et al., "Multiple-Level Logic Optimization System", ICCAD-86, pp. 356-360. Gregory, et al., "SOCRATES: A System for Automatically Synthesizing and Optimizing Combinational Logic", DAC-86, pp. 79-85. Shin and Sangiovanni-Vincentelli, "MIGHTY: A Rip-Up and Reroute Detailed Router", ICCAD-86, pp. 2-5. Joobani, "WEAVER: A Knowledge-Based Routing Expert", PhD dissertation, CMU, 1985. ---------------------------------------------------------------------- Abstract: Title: Artificial Intelligence, Mathematical Programming, and VLSI Design Speaker: Wayne Wolf, AT&T Bell Laboratories, Murray Hill Artifical intelligence techniques have found their greatest success in diagnosis and classification problems. The application of AI to design problems is relatively new. In this talk I want to consider how the intellectual tools that AI brings to the design problem can best be used by contrasting two paradigms: artificial intelligence and mathematical programming. I will argue that mathematical programming is a more powerful paradigm than AI for a lot of synthesis problems because mathematical programming a) allows better application of brute force; b) encourages us to formulate solvable problems. I will argue that AI is a more powerful paradigm for knowledge representation because it provides a lot of tools for separating particular pieces of knowledge from the engines used to maintain them. The talk will be in three parts: 1) The VLSI design problem: what is hard about VLSI design; what tools people need to make bigger, better designs; what people would do with VLSI synthesis if they had it. 2) Synthesis and search: search in AI and mathematical programming; problem formulation and search; results in application of AI and mathematical programming techniques to some design problems. 3) Synthesis and knowledge representation: why knowledge representation is important; examples of KR problems and solutions from Fred, the database; how AI knowledge representation and mathematical programming complement each other in Lucy, the controller designer.