Document Type



Doctor of Philosophy (PhD)


Computer Science

First Advisor's Name

David Barton

First Advisor's Committee Title

Committee Chair

Second Advisor's Name

Gustavo Roig

Third Advisor's Name

Osama Mohammed

Fourth Advisor's Name

Nand Tripathi

Fifth Advisor's Name

John Comfort


Differential equations, Nonlinear, Numerical solutions, Data processing, Parallel processing (Electronic computers), Computer architecture

Date of Defense



Solving nonlinear systems of equations is a central problem in numerical analysis, with enormous significance for science and engineering. A special case, sparse systems of equations, occurs frequently in various applications. Sparsity occurs in the analysis of many types of complex systems because of the local nature of the dependence or connectivity among system components.

One such system which may be modeled by a nonlinear sparse set of equations is the power system load flow analysis. This is a mathematical study performed by electrical utilities to monitor the electrical power system. The data from system components are used to create a set of nonlinear equations. These equations are then solved to find the voltage profile of the power network. With these data, control and security of the power system are achieved.

Solving problems of this type is very time consuming when the system is large. This dissertation proposes a highly parallel computer architecture for solving large sets of nonlinear sparse equations. The goal of this architecture is to reduce the processing time required to solve this type of problem. In particular, the load flow problem is analyzed and implemented on this architecture. For the FPL network, the speed is increased by a factor of about 2000.





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