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Title:  Accelerating induction machine finiteelement simulation with parallel processing 
Author(s):  Ross, Christine Anne Haines 
Advisor(s):  Krein, Philip T. 
Department / Program:  Electrical & Computer Engineering 
Discipline:  Electrical & Computer Engineering 
Degree Granting Institution:  University of Illinois at UrbanaChampaign 
Degree:  M.S. 
Genre:  Thesis 
Subject(s):  finite element
simulation finite element MATLAB Graphics Processing Unit (GPU) parallel parallel processing linear nonlinear transient eddy current eddy induction Machine induction machine electrical machine speedup electromagnetic Compute Unified Device Architecture (CUDA) sparse matrixvector multiplication Sparse Matrixvector Multiply (SpMV) Krylov iterative solver Finite Element Method (FEM) Finite Element Analysis (FEA) Galerkin 
Abstract:  Finite element analysis used for detailed electromagnetic analysis and design of electric machines is computationally intensive. A means of accelerating twodimensional transient finite element analysis, required for induction machine modeling, is explored using graphical processing units (GPUs) for parallel processing. The graphical processing units, widely used for image processing, can provide faster computation times than CPUs alone due to the thousands of small processors that comprise the GPUs. Computations that are suitable for parallel processing using GPUs are calculations that can be decomposed into subsections that are independent and can be computed in parallel and reassembled. The steps and components of the transient finite element simulation are analyzed to determine if using GPUs for calculations can speed up the simulation. The dominant steps of the finite element simulation are preconditioner formation, computation of the sparse iterative solution, and matrixvector multiplication for magnetic flux density calculation. Due to the sparsity of the finite element problem, GPUimplementation of the sparse iterative solution did not result in faster computation times. The dominant speedup achieved using the GPUs resulted from matrixvector multiplication. Simulation results for a benchmark nonlinear magnetic material transient eddy current problem and linear magnetic material transient linear induction machine problem are presented. The finite element analysis program is implemented with MATLAB R2014a to compare sparse matrix format computations to readily available GPU matrix and vector formats and Compute Unified Device Architecture (CUDA) functions linked to MATLAB. Overall speedup achieved for the simulations resulted in 1.23.5 times faster computation of the finite element solution using a hybrid CPU/GPU implementation over the CPUonly implementation. The variation in speedup is dependent on the sparsity and number of unknowns of the problem. 
Issue Date:  20150717 
Type:  Thesis 
URI:  http://hdl.handle.net/2142/88070 
Rights Information:  Copyright 2015 Christine Ross 
Date Available in IDEALS:  20150929 
Date Deposited:  August 201 
This item appears in the following Collection(s)

Dissertations and Theses  Electrical and Computer Engineering
Dissertations and Theses in Electrical and Computer Engineering 
Graduate Dissertations and Theses at Illinois
Graduate Theses and Dissertations at Illinois