ALGORITHM: Collaborative Research: SEIDD--Scalable Domain Decomposition Algorithms for Solving Parabolic Problems

Texas Tech University, Lubbock TX

Investigators

Abstract

The Stabilized Explicit-Implicit Domain Decomposition (SEIDD) is a class of globally non-iterative and non-overlapping Domain Decomposition (DD) algorithms for solving parabolic equations on parallel computers. These algorithms do not use large amounts of memory and are inherently parallel, which makes them useful for large scale parallel processing. The SEIDD approach aims to provide algorithmic solutions that can better utilize parallel/distributed computing resources, thereby improving the accessibility of high performance computing power for researchers and educators from a broad range of science and engineering disciplines. Through integration with education and curriculum development, this research project promises to provide better education opportunities in high performance computing for a wide range of students while offering immediate training for computer science students in parallel algorithm design and programming.