Parallel semiconductor device simulation: from power to 'atomistic' devices

This paper discusses various aspects of the parallel simulation of semiconductor devices on mesh connected MIMD platforms with distributed memory and a message passing programming paradigm. We describe the spatial domain decomposition approach adopted in the simulation of various devices, the generation of structured topologically rectangular 2D and 3D finite element grids and the optimisation of their partitioning using simulated annealing techniques. The development of efficient and scalable parallel solvers is a central issue of parallel simulations and the design of parallel SOR, conjugate gradient and multigrid solvers is discussed. The domain decomposition approach is illustrated in examples ranging from `atomistic' simulation of decanano MOSFETs to simulation of power IGBTs rated for 1000 V

Relaxing Synchronization in Distributed Simulated Annealing

Simulated annealing is an attractive, but expensive, heuristic for approximating the solution to combinatorial optimization problems. Since simulated annealing is a general purpose method, it can be applied to the broad range of NP-complete problems such as the traveling salesman problem, graph theory, and cell placement with a careful control of the cooling schedule. Attempts to parallelize simulated annealing, particularly on distributed memory multicomputers, are hampered by the algorithm’s requirement of a globally consistent system state. In a multicomputer, maintaining the global state S involves explicit message traffic and is a critical performance bottleneck. One way to mitigate this bottleneck is to amortize the overhead of these state updates over as many parallel state changes as possible. By using this technique, errors in the actual cost C(S) of a particular state S will be introduced into the annealing process. This dissertation places analytically derived bounds on the cost error in order to assure convergence to the correct result. The resulting parallel Simulated Annealing algorithm dynamically changes the frequency of global updates as a function of the annealing control parameter, i.e. temperature. Implementation results on an Intel iPSC/2 are reported

Dual Superconductor Scenario of Confinement: A Systematic Study of Gribov Copy Effects

We perform a study of the effects from maximal abelian gauge Gribov copies in the context of the dual superconductor scenario of confinement, on the basis of a novel approach for estimation of systematic uncertainties from incomplete gauge fixing. We present numerical results, in SU(2) lattice gauge theory, using the overrelaxed simulated annealing gauge fixing algorithm. We find abelian and non-abelian string tensions to differ significantly, their ratio being 0.92(4) at BETA = 2.5115. An approximate factorization of the abelian potential into monopole and photon contributions has been confirmed, the former giving rise to the abelian string tension.Comment: 35 pages uucompressed LaTeX with 10 encapsuled postscript figure

Efficient Wave-based Sound Propagation and Optimization for Computer-Aided Design

Acoustic phenomena have a large impact on our everyday lives, from influencing our enjoyment of music in a concert hall, to affecting our concentration at school or work, to potentially negatively impacting our health through deafening noises. The sound that reaches our ears is absorbed, reflected, and filtered by the shape, topology, and materials present in the environment. However, many computer simulation techniques for solving these sound propagation problems are either computationally expensive or inaccurate. Additionally, the costs of some methods are dramatically increased in design optimization processes in which several iterations of sound propagation evaluation are necessary. The primary goal of this dissertation is to present techniques for efficiently solving the sound propagation problem and related optimization problems for computer-aided design. First, we propose a parallel method for solving large acoustic propagation problems, scalable to tens of thousands of cores. Second, we present two novel techniques for optimizing certain acoustic characteristics such as reverberation time or sound clarity using wave-based sound propagation. Finally, we show how hybrid sound propagation algorithms can be used to improve the performance of acoustic optimization problems and present two algorithms for noise minimization and speech intelligibility improvement that use this hybrid approach. All the algorithms we present are evaluated on various benchmarks that are computer models of architectural scenes. These benchmarks include challenging environments for existing sound propagation algorithms, such as large indoor or outdoor scenes, structural complex scenes, or the prevalence of difficult-to-model sound propagation phenomena. Using the techniques put forth in this dissertation, we can solve many challenging sound propagation and optimization problems on the scenes in an efficient manner. We are able to accurately model sound propagation using wave-based approaches up to \SI{10}{\kilo\hertz} (the full range of human speech) and for the full range of human hearing (22kHz) using our hybrid approach. Our noise minimization methods show improvements of up to 13dB in noise reduction on some scenes, and we show a 71\% improvement in speech intelligibility using our algorithm.Doctor of Philosoph

Moldable Items Packing Optimization

This research has led to the development of two mathematical models to optimize the problem of packing a hybrid mix of rigid and moldable items within a three-dimensional volume. These two developed packing models characterize moldable items from two perspectives: (1) when limited discrete configurations represent the moldable items and (2) when all continuous configurations are available to the model. This optimization scheme is a component of a lean effort that attempts to reduce the lead-time associated with the implementation of dynamic product modifications that imply packing changes. To test the developed models, they are applied to the dynamic packing changes of Meals, Ready-to-Eat (MREs) at two different levels: packing MRE food items in the menu bags and packing menu bags in the boxes. These models optimize the packing volume utilization and provide information for MRE assemblers, enabling them to preplan for packing changes in a short lead-time. The optimization results are validated by running the solutions multiple times to access the consistency of solutions. Autodesk Inventor helps visualize the solutions to communicate the optimized packing solutions with the MRE assemblers for training purposes