Date Available


Year of Publication


Degree Name

Doctor of Philosophy (PhD)

Document Type

Doctoral Dissertation




Electrical and Computer Engineering

First Advisor

Dr. Robert J. Adams


This dissertation presents and analyzes two new algorithms for sparse direct solution methods based on the use of local-global solution (LOGOS) modes. One of the new algorithms is a rigorous error control strategy for LOGOS-based matrix factorizations that utilize overlapped, localizing modes (OL-LOGOS) on a shifted grid. The use of OL-LOGOS modes is critical to obtaining asymptotically efficient factorizations from LOGOS-based methods. Unfortunately, the approach also introduces a non-orthogonal basis function structure. This can cause errors to accumulate across levels of a multilevel implementation, which has previously posed a barrier to rigorous error control for the OL-LOGOS factorization method. This limitation is overcome, and it is shown that it is possible to efficiently decouple the fundamentally non-orthogonal factorization subspaces in a manner that prevents multilevel error propagation. This renders the OL-LOGOS factorization error controllable in a relative RMS sense. The impact of the new, error-controlled OL-LOGOS factorization algorithm on computational resource utilization is discussed and several numerical examples are presented to illustrate the performance of the improved algorithm relative to previously reported results.

The second algorithmic development considered is the development of efficient out-of-core (OOC) versions of the OL-LOGOS factorization algorithm that allow associated software tools to take advantage of additional resources for memory management. The proposed OOC algorithm incorporates a memory page definition that is tailored to match the flow of the OL-LOGOS factorization procedure. Efficiency of the function of the part is evaluated using a quantitative approach, because the tested massive storage device performances do not follow analytical results. The performance latency and the memory usage of the resulting OOC tools are compared with in-core performance results.

Both the new error control algorithm and the OOC method have been incorporated into previously existing software tools, and the dissertation presents results for real-world simulation problems.