We describe a new method for determining component values and transistor dimensions for CMOS operational ampli ers (op-amps). We observe that a wide variety of design objectives and constraints have a special form, i.e., they are posynomial functions of the design variables. As a result the ampli er design problem can be expressed as a special form of optimization problem called geometric programming, for which very e cient global optimization methods have been developed. As a consequence we can e ciently determine globally optimal ampli er designs, or globally optimal trade-o s among competing performance measures such aspower, open-loop gain, and bandwidth. Our method therefore yields completely automated synthesis of (globally) optimal CMOS ampli ers, directly from speci cations. In this paper we apply this method to a speci c, widely used operational ampli er architecture, showing in detail how to formulate the design problem as a geometric program. We compute globally optimal trade-o curves relating performance measures such as power dissipation, unity-gain bandwidth, and open-loop gain. We show how the method can be used to synthesize robust designs, i.e., designs guaranteed to meet the speci cations for a

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.

The research presented in this paper is concerned with the design automation of analog integrated circuits, simply called analog synthesis. A new algorithm, namely a simulated annealing algorithm with multi-molecule (SAMM), is proposed to solve analog synthesis problems. Besides inheriting the global convergence of the traditional simulated annealing algorithm (SA), SAMM can avoid the excessively time-consuming final iterations of SA, which makes it more efficient and suitable for analog synthesis. Several analog synthesis examples are also given in this paper to demonstrate the efficiency and validity of SAMM.

We present a method for optimizing and automating component and transistor sizing for CMOS operational amplifiers. We observe that a wide variety of performance measures can be formulated as posynomial functions of the design variables. As a result, amplifier design problems can be formulated as a geometric program, a special type of convex optimization problem for which very efficient global optimization methods have recently been developed. The synthesis method is therefore fast, and determines the globally optimal design; in particular the final solution is completely independent of the starting point (which can even be infeasible), and infeasible specifications are unambiguously detected.

We present a method for optimizing and automating component and transistor sizing in CMOS operational amplifiers. We observe that a wide variety of performance measures can be formulated as posynomial functions of the design variables. As a result, amplifier design problems can be expressed as geometric programs, as special type of convex problems for which very efficient global optimization methods exist. A side benefit of using convex optimization is that a sensitivity analysis is obtained with the final solution with no additional computation. This information is of great interest to analog circuit designers. The method we present can be applied to a wide variety of amplifier architectures, but in this paper we apply the method to a specific two-stage amplifier architecture.