Abstract-Analog synthesis tools have traditionally traded quality for speed, substituting simplified circuit evaluation methods for full simulation in order to accelerate the numerical search for solution candidates. As a result, these tools have failed to migrate into mainstream use primarily because of difficulties in reconciling the simplified models required for synthesis with the industrial-strength simulation environments required for validation. We argue that for synthesis to be practical, it is essential to synthesize a circuit using the same simulation environment created to validate the circuit. In this paper, we develop a new numerical search algorithm efficient enough to allow full circuit simulation of each circuit candidate, and robust enough to find good solutions for difficult circuits. The method combines the population-of-solutions ideas from evolutionary algorithms with a novel variant of pattern search, and supports transparent network parallelism. Comparison of several synthesized cell-level circuits against manual industrial designs demonstrates the utility of the approach.

Abstract

We describe a synthesis system that takes operating range constraints and inter and intracircuit parametric manufacturing variations into account while designing a sized and biased analog circuit. Previous approaches to computer-aided design for analog circuit synthesis have concentrated on nominal analog circuit design, and subsequent optimization of these circuits for statistical fluctuations and operating point ranges. Our approach simultaneously synthesizes and optimizes for operating and manufacturing variations by mapping the circuit design problem into an Infinite Programming problem and solving it using an annealing within annealing formulation. We present circuits designed by this integrated synthesis system, and show that they indeed meet their operating range and parametric manufacturing constraints. And finally, we show that our consideration of variations during the initial optimization-based circuit synthesis leads to better starting points for post-synthesis yield optimization than a classical nominal synthesis approach.

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In the Fall of 1991, after approximately two years of development, the department of Electrical and Computer Engineering (ECE) at Camegie Mellon University (CMU) implemented a new curriculum that differed radically from its predecessor. Key features of this curriculum include: Engineering in the Freshman year, a small core of required classes, area requirements in place of most speciJc course requirements, mandated breadth, depth, design, and coverage across ECE technical areas, a relatively large fraction of free electives, and a single integrated Bachelor of Science degree in Electrical and Computer Engineering. In this paper we review the design of this curriculum, including a taxonomy of problems we needed to address, and a set of general principles we evolved to address them. The new curriculum is described in detail, including new data from an ongoing analysis of its impact on students' curricula choices. 'See [l] for a more detailed, contemporaneous account of this process, and [2] for a more recent review.