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28
Optimal design of a CMOS opamp via geometric programming
 IEEE Transactions on ComputerAided Design
, 2001
"... We describe a new method for determining component values and transistor dimensions for CMOS operational ampli ers (opamps). 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 ..."
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Cited by 51 (10 self)
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We describe a new method for determining component values and transistor dimensions for CMOS operational ampli ers (opamps). 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 tradeo s among competing performance measures such aspower, openloop 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 tradeo curves relating performance measures such as power dissipation, unitygain bandwidth, and openloop gain. We show how the method can be used to synthesize robust designs, i.e., designs guaranteed to meet the speci cations for a
GPCAD: A Tool for CMOS OpAmp Synthesis
 IN PROCEEDINGS OF THE IEEE/ACM INTERNATIONAL CONFERENCE ON COMPUTER AIDED DESIGN
, 1998
"... 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 g ..."
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Cited by 29 (10 self)
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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. After briefly
On a Homogeneous Algorithm for the Monotone Complementarity Problem
 Mathematical Programming
, 1995
"... We present a generalization of a homogeneous selfdual linear programming (LP) algorithm to solving the monotone complementarity problem (MCP). The algorithm does not need to use any "bigM" parameter or twophase method, and it generates either a solution converging towards feasibility and compleme ..."
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Cited by 26 (3 self)
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We present a generalization of a homogeneous selfdual linear programming (LP) algorithm to solving the monotone complementarity problem (MCP). The algorithm does not need to use any "bigM" parameter or twophase method, and it generates either a solution converging towards feasibility and complementarity simultaneously or a certificate proving infeasibility. Moreover, if the MCP is polynomially solvable with an interior feasible starting point, then it can be polynomially solved without using or knowing such information at all. To our knowledge, this is the first interiorpoint and infeasiblestarting algorithm for solving the MCP that possesses these desired features. Preliminary computational results are presented. Key words: Monotone complementarity problem, homogeneous and selfdual, infeasiblestarting algorithm. Running head: A homogeneous algorithm for MCP. Department of Management, Odense University, Campusvej 55, DK5230 Odense M, Denmark, email: eda@busieco.ou.dk. y De...
Disciplined convex programming
 Global Optimization: From Theory to Implementation, Nonconvex Optimization and Its Application Series
, 2006
"... ..."
Optimal Power Control in Interference Limited Fading Wireless Channels with Outage Probability Specifications
, 2000
"... We propose a new method of power control for interference limited wireless networks with Rayleigh fading of both the desired and interference signals. Our method explictly takes into account the statistical variation of both the received signal and interference power, and optimally allocates powe ..."
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Cited by 16 (2 self)
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We propose a new method of power control for interference limited wireless networks with Rayleigh fading of both the desired and interference signals. Our method explictly takes into account the statistical variation of both the received signal and interference power, and optimally allocates power subject to constraints on the probability of fading induced outage for each transmitter/receiver pair. We establish several results for this type of problem. For the case
A Computational Study of the Homogeneous Algorithm for LargeScale Convex Optimization
, 1997
"... Recently the authors have proposed a homogeneous and selfdual algorithm for solving the monotone complementarity problem (MCP) [5]. The algorithm is a single phase interiorpoint type method, nevertheless it yields either an approximate optimal solution or detects a possible infeasibility of th ..."
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Cited by 14 (1 self)
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Recently the authors have proposed a homogeneous and selfdual algorithm for solving the monotone complementarity problem (MCP) [5]. The algorithm is a single phase interiorpoint type method, nevertheless it yields either an approximate optimal solution or detects a possible infeasibility of the problem. In this paper we specialize the algorithm to the solution of general smooth convex optimization problems that also possess nonlinear inequality constraints and free variables. We discuss an implementation of the algorithm for largescale sparse convex optimization. Moreover, we present computational results for solving quadratically constrained quadratic programming and geometric programming problems, where some of the problems contain more than 100,000 constraints and variables. The results indicate that the proposed algorithm is also practically efficient. Department of Management, Odense University, Campusvej 55, DK5230 Odense M, Denmark. Email: eda@busieco.ou.dk y ...
Concurrent Logic Restructuring and Placement for Timing Closure
 in Proc. IEEE International Conference on Computer Aided Design
, 1999
"... ABSTRACT: In this paper, an algorithm for simultaneous logic restructuring and placement is presented. This algorithm first constructs a set of supercells along the critical paths and then generates the set of noninferior remapping solutions for each supercell. The best mapping and placement solu ..."
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Cited by 13 (0 self)
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ABSTRACT: In this paper, an algorithm for simultaneous logic restructuring and placement is presented. This algorithm first constructs a set of supercells along the critical paths and then generates the set of noninferior remapping solutions for each supercell. The best mapping and placement solutions for all supercells are obtained by solving a generalized geometric programming (GGP) problem. The process of identifying and optimizing the critical paths is iterated until timing closure is achieved. Experimental results on a set of MCNC benchmarks demonstrate the effectiveness of our algorithm. I.
Towards optimal multilevel tiling for stencil computations
 21st IEEE International Parallel and Distributed Processing Symposium (IPDPS
, 2007
"... Stencil computations form the performancecritical core of many applications. Tiling and parallelization are two important optimizations to speed up stencil computations. Many tiling and parallelization strategies are applicable to a given stencil computation. The best strategy depends not only on t ..."
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Cited by 10 (0 self)
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Stencil computations form the performancecritical core of many applications. Tiling and parallelization are two important optimizations to speed up stencil computations. Many tiling and parallelization strategies are applicable to a given stencil computation. The best strategy depends not only on the combination of the two techniques, but also on many parameters: tile and loop sizes in each dimension; computationcommunication balance of the code; processor architecture; message startup costs; etc. The best choices can only be determined through designspace exploration, which is extremely tedious and error prone to do via exhaustive experimentation. We characterize the space of multilevel tilings and parallelizations for 2D/3D GaussSiedel stencil computation. A systematic exploration of a part of this space enabled us to derive a design which is up to a factor of two faster than the standard implementation. 1.
Optimal allocation of local feedback in multistage amplifiers via geometric programming
 IEEE Transactions on Circuits and Systems I
, 2001
"... We consider the problem of optimally allocating local feedback to the stages of a multistage amplifier. The local feedback gains affect many performance indices for the overall amplifier, such as bandwidth, gain, risetime, delay, output signal swing, linearity, and noise performance, in a complicat ..."
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Cited by 7 (4 self)
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We consider the problem of optimally allocating local feedback to the stages of a multistage amplifier. The local feedback gains affect many performance indices for the overall amplifier, such as bandwidth, gain, risetime, delay, output signal swing, linearity, and noise performance, in a complicated and nonlinear fashion, making optimization of the feedback gains a challenging problem. In this paper we show that this problem, though complicated and nonlinear, can be formulated as a special type of optimization problem called geometric programming. Geometric programs can be solved globally and efficiently using recently developed interiorpoint methods. Our method therefore gives a complete solution to the problem of optimally allocating local feedback gains, taking into account a wide variety of constraints. 1 1
Design and optimization of LC oscillators
, 1999
"... We present a method for optimizing and automating component and transistor sizing for CMOS LC oscillators. We observe that the performance measures can be formulated as posynomial functions of the design variables. As a result, the LC oscillator design problems can be posed as a geometric program, ..."
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Cited by 7 (2 self)
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We present a method for optimizing and automating component and transistor sizing for CMOS LC oscillators. We observe that the performance measures can be formulated as posynomial functions of the design variables. As a result, the LC oscillator design problems can be posed as a geometric program, a special type of 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 can rapidly compute globally optimal tradeoff curves between competing objectives such as phase noise and power.