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Despite the ample number of articles on parallel-vector computational algorithms published over the last 20 years, there is a lack of texts in the field customized for senior undergraduate and graduate engineering research. Parallel-Vector Equation Solvers for Finite Element Engineering Applications aims to fill this gap, detailing both the theoretical development and important implementations of equation-solution algorithms. The mathematical background necessary to understand their inception balances well with descriptions of their practical uses. Illustrated with a number of state-of-the-art FORTRAN codes developed as examples for the book, Dr. Nguyen's text is a perfect choice for instructors and researchers alike.
High-performance multiprocessor computers provide new and interesting opportunities to solve large-scale structural engineering problems. However, the development of new computational models and algorithms that exploit the unique architecture of these machines remains a challenge. High Performance Computing in Structural Engineering explores the use of supercomputers with vectorization and parallel processing capabilities in structural engineering applications. The book focuses on the optimization of large structures subjected to the complicated, implicit, and discontinuous constraints of commonly used design codes and presents robust parallel-algorithms for analysis of these structures. The authors apply the algorithms to and analyze the performance of minimum weight designs of large, steel space trusses and moment-resisting frames, with or without bracings, consisting of discrete standard shapes. They clearly show that adroit and judicious use of vectorization techniques can improved the speedup of an optimization algorithm, and that parallel processing can lead to even further speedup. With its review of the necessary background material, generous illustrations, and unique content, this is the definitive resource for the analysis and optimization of structure on shared-memory multiprocessor computers. By extension, High Performance Computing in Structural Engineering will prove equally valuable in distributed computing on a cluster of workstations
Subspace and Lanczos iterations have been developed, well documented, and widely accepted as efficient methods for obtaining p-lowest eigen-pair solutions of large-scale, practical engineering problems. The focus of this paper is to incorporate recent developments in vectorized sparse technologies in conjunction with Subspace and Lanczos iterative algorithms for computational enhancements. Numerical performance, in terms of accuracy and efficiency of the proposed sparse strategies for Subspace and Lanczos algorithm, is demonstrated by solving for the lowest frequencies and mode shapes of structural problems on the IBM-R6000/590 and SunSparc 20 workstations. Nguyen, Duc T. Langley Research Center...