An SQP method for general nonlinear programs using only equality constrained subproblems
Mathematical Programming: Series A and B
Revisiting Asynchronous Parallel Pattern Search for Nonlinear Optimization
SIAM Journal on Optimization
Algorithm 856: APPSPACK 4.0: asynchronous parallel pattern search for derivative-free optimization
ACM Transactions on Mathematical Software (TOMS)
Combinatorial algorithms for fast clock mesh optimization
Proceedings of the 2006 IEEE/ACM international conference on Computer-aided design
Analysis of large clock meshes via harmonic-weighted model order reduction and port sliding
Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design
Multicore parallelization of min-cost flow for CAD applications
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems - Special section on the ACM IEEE international conference on formal methods and models for codesign (MEMOCODE) 2009
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Mesh-based clock distribution network has been employed in many high-performance microprocessor designs due to its favorable properties such as low clock skew and robustness. Such clock distributions are usually highly complex. While the simulation of clock meshes is already time consuming, tuning such networks under tight performance constraints is a more daunting task. In this paper, we address the challenging task of driver size optimization with a goal of skew minimization. The expensive objective function evaluations and difficulty in getting explicit sensitivity information make this problem intractable to standard optimization methods. We propose to explore the recently developed asynchronous parallel pattern search (APPS) method for efficient driver size tuning. While being a search-based method, APPS not only provides the desirable derivative-free optimization capability, but is also amenable to parallelization and possesses appealing theoretically rigorous convergence properties. We show how such a method can lead to powerful parallel sizing optimization of large clock meshes with significant runtime and quality advantages over the traditional sequential quadratic programming (SQP) method. We also show how design-specific properties and speeding-up techniques can be exploited to make the optimization even more efficient while maintaining the convergence of APPS in a practical sense.