The design (synthesis) of analog electrical circuits starts with a highlevel statement of the circuit's desired behavior and requires creating a circuit that satisfies the specified design goals. Analog circuit synthesis entails the creation of both the topology and the sizing (numerical values) of all of the circuit's components. The difficulty of the problem of analog circuit synthesis is well known and there is no previously known general automated technique for synthesizing an analog circuit from a high-level statement of the circuit's desired behavior. This paper presents a single uniform approach using genetic programming for the automatic synthesis of both the topology and sizing of a suite of eight different prototypical analog circuits, including a lowpass filter, a crossover (woofer and tweeter) filter, a source identification circuit, an amplifier, a computational circuit, a timeoptimal controller circuit, a temperature-sensing circuit, and a voltage reference circuit. The problem-specific information required for each of the eight problems is minimal and consists primarily of the number of inputs and outputs of the desired circuit, the types of available components, and a fitness measure that restates the highlevel

This paper describes an automated process for designing electrical circuits in which "What You Want Is What You Get " ("WYWIWYG " – pronounced "wow-eee-wig"). The design process uses genetic programming to produce both the topology of the desired circuit and the sizing (numerical values) for all the components of a circuit. Genetic programming successfully evolves both the topology and the sizing for an asymmetric bandpass filter that was described as being difficult-to-design in a leading electrical engineering journal. This evolved circuit is another instance in which a genetically evolved solution to a non-trivial problem is competitive with human performance. 1.

: This paper describes an automated process for designing analog electrical circuits based on the principles of natural selection, sexual recombination, and developmental biology. The design process starts with the random creation of a large population of program trees composed of circuit-constructing functions. Each program tree specifies the steps by which a fully developed circuit is to be progressively developed from a common embryonic circuit appropriate for the type of circuit that the user wishes to design. Each fully developed circuit is translated into a netlist, simulated using a modified version of SPICE, and evaluated as to how well it satisfies the user's design requirements. The fitness measure is a user-written computer program that may incorporate any calculable characteristic or combination of characteristics of the circuit, including the circuit's behavior in the time domain, its behavior in the frequency domain, its power consumption, the number of components, cost o...

Abstract – It would be desirable if computers could solve problems without the need for a human to write the detailed programmatic steps. That is, it would be desirable to have a domain-independent automatic programming technique in which "What You Want Is What You Get " ("WYWIWYG " – pronounced "woweee-wig"). Genetic programming is such a technique. This paper surveys three recent examples of problems (from the fields of cellular automata and molecular biology) in which genetic programming evolved a computer program that produced results that were slightly better than human performance for the same problem. This paper then discusses the problem of electronic circuit synthesis in greater detail. It shows how genetic programming can evolve both the topology of a desired electrical circuit and the sizing (numerical values) for each component in a crossover (woofer and tweeter) filter. Genetic programming has also evolved the design for a lowpass filter, the design of an amplifier, and the design for an asymmetric bandpass filter that was described as being difficult-to-design in an article in a leading electrical engineering journal.

Analog synthesis 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. MAELSTROM is a new approach that synthesizes a circuit using the same simulation environment created to validate the circuit. We introduce a novel genetic/ annealing optimizer, and leverage network parallelism to achieve efficient simulator-in-the-loop analog synthesis.

A persistent criticism of analog synthesis techniques is that they cannot cope with the complexity of realistic industrial designs, especially system-level designs. We show how recent advances in simulation-based synthesis can be augmented, via appropriate macromodeling, to attack complex analog blocks. To support this claim, we resynthesize from scratch, in several different styles, a complex equalizer/filter block from the frontend of a commercial ADSL CODEC, and verify by full simulation that it matches its original design specifications. As a result, we argue that synthesis has significant potential in both custom and analog IP reuse scenarios.

Abstract: This paper describes an automated process for designing analog electrical circuits based on the principles of natural selection, sexual recombination, and developmental biology. The design process starts with the random creation of a large population of program trees composed of circuit-constructing functions. Each program tree specifies the steps by which a fully developed circuit is to be progressively developed from a common embryonic circuit appropriate for the type of circuit that the user wishes to design. Each fully developed circuit is translated into a netlist, simulated using a modified version of SPICE, and evaluated as to how well it satisfies the user's design requirements. The fitness measure is a user-written computer program that may incorporate any calculable characteristic or combination of characteristics of the circuit, including the circuit's behavior in the time domain, its behavior in the frequency domain, its power consumption, the number of components, cost of components, or surface area occupied by its components. The population of program trees is genetically bred over a series of many generations using genetic programming. Genetic programming is driven by a fitness measure and employs genetic operations such as Darwinian reproduction,

As chip complexity explodes and compressed product development cycles relentlessly scale time-tomarket pressures, designers must accomplish more ambitious objectives in less time. For an increasing number of designers, the secret to quickly building highly integrated systems on a chip (SoCs) in a shrinking development cycle lies in the extensive reuse of silicon-proven megafunctions or blocks.

This paper introduces a complete methodology for retargeting of transistor-level circuits to different sets of specifications. By careful integration of the device sizing and layout generation tasks, fully functional designs are generated in a few minutes of CPU time. The methodology is illustrated via the retargeting of a fully-differential Miller-compensated two-stage operational amplifier for a new set of specifications. 1.

This paper introduces a complete methodology for retargeting of analogue blocks to different sets of specifications. By careful integration of the size tuning of devices and layout generation tasks, fully functional designs are generated in a few minutes of CPU time. 1.