Circuit Optimization via Adjoint Lagrangians

Circuit Optimization via Adjoint Lagrangians (1997)

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by Andrew R. Conn , Ruud A. Haring , Chandu Visweswariah , Chai Wah Wu

Venue:	IEEE INTERNATIONAL CONFERENCE ON COMPUTER-AIDED DESIGN
Citations:	4 - 3 self

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Datum	Value	Source
TITLE	Circuit Optimization via Adjoint Lagrangians	user correction - Legacy Corrections
AUTHOR NAME	Andrew R. Conn	user correction
AUTHOR AFFIL	IBM T. J. Watson Research Center	user correction
AUTHOR ADDR	Yorktown Heights, NY 10598	user correction
AUTHOR NAME	Ruud A. Haring	user correction
AUTHOR AFFIL	IBM T. J. Watson Research Center	user correction
AUTHOR ADDR	Yorktown Heights, NY 10598	user correction
AUTHOR NAME	Chandu Visweswariah	user correction
AUTHOR AFFIL	IBM T. J. Watson Research Center	user correction
AUTHOR ADDR	Yorktown Heights, NY 10598	user correction
AUTHOR NAME	Chai Wah Wu	user correction
AUTHOR AFFIL	IBM T. J. Watson Research Center	user correction
AUTHOR ADDR	Yorktown Heights, NY 10598	user correction
ABSTRACT	The circuit tuning problem is best approached by means of gradient-based nonlinear optimization algorithms. For large circuits, gradient computation can be the bottleneck in the optimization procedure. Traditionally, when the number of measurements is large relative to the number of tunable parameters, the direct method [2] is used to repeatedly solve the associated sensitivity circuit to obtain all the necessary gradients. Likewise, when the parameters outnumber the measurements, the adjoint method [1] is employed to solve the adjoint circuit repeatedly for each measurement to compute the sensitivities. In this paper, we propose the adjoint Lagrangian method, which computes all the gradients necessary for augmented-Lagrangian-based optimization in a single adjoint analysis. After the nominal simulation of the circuit has been carried out, the gradients of the merit function are expressed as the gradients of a weighted sum of circuit measurements. The weights are dependent on the nominal solution and on optimizer quantities such as Lagrange multipliers. By suitably choosing the excitations of the adjoint circuit, the gradients of the merit function are computed via a single adjoint analysis, irrespective of the number of measurements and the number of parameters of the optimization. This procedure requires close integration between the nonlinear optimization software and the circuit simulation program. The adjoint	user correction
YEAR	1997	INFERENCE
VENUE	IEEE INTERNATIONAL CONFERENCE ON COMPUTER-AIDED DESIGN	user correction
VENUE TYPE	CONFERENCE	INFERENCE
PAGES	281--288	INFERENCE
CITATIONS	34 found	ParsCit 1.0