Parallel pivoting combined with parallel reduction

Parallel algorithms for triangularization of large, sparse, and unsymmetric matrices are presented. The method combines the parallel reduction with a new parallel pivoting technique, control over generations of fill-ins and a check for numerical stability, all done in parallel with the work being distributed over the active processes. The parallel technique uses the compatibility relation between pivots to identify parallel pivot candidates and uses the Markowitz number of pivots to minimize fill-in. This technique is not a preordering of the sparse matrix and is applied dynamically as the decomposition proceeds

Assessment Strategies for Student Recruitment and Retention in Engineering

A recruitment and retention program is developed and assessed for undergraduate engineering students. The goal is to recruit students with academic talent and to provide the financial, academic and social network supports that prepare these students to graduate in the field of engineering. The program has three main components: (1) A pre-collegiate summer workshop designed to introduce engineering concepts to high school students through a new multidisciplinary precollegiate summer course; (2) Scholarships for full-time students enrolled in the program who demonstrate financial need and academic achievement; (3) A network of academic and social support that will help students persist in their studies at a high level of achievement, complete their baccalaureate in a timely manner, and pursue careers and educational opportunities in the field. By focusing the program within the college of engineering we are able to facilitate the institution of a program-centered community of learners whose members share common goals, interests, and identity that are associated with achievement and persistence toward graduation. During a four year period we were able to recruit and retain 25 students in four engineering majors

The FORCE: A highly portable parallel programming language

Here, it is explained why the FORCE parallel programming language is easily portable among six different shared-memory microprocessors, and how a two-level macro preprocessor makes it possible to hide low level machine dependencies and to build machine-independent high level constructs on top of them. These FORCE constructs make it possible to write portable parallel programs largely independent of the number of processes and the specific shared memory multiprocessor executing them

Tiled Algorithms for Matrix Computations on Multicore Architectures

The current computer architecture has moved towards the multi/many-core structure. However, the algorithms in the current sequential dense numerical linear algebra libraries (e.g. LAPACK) do not parallelize well on multi/many-core architectures. A new family of algorithms, the tile algorithms, has recently been introduced to circumvent this problem. Previous research has shown that it is possible to write efficient and scalable tile algorithms for performing a Cholesky factorization, a (pseudo) LU factorization, and a QR factorization. The goal of this thesis is to study tiled algorithms in a multi/many-core setting and to provide new algorithms which exploit the current architecture to improve performance relative to current state-of-the-art libraries while maintaining the stability and robustness of these libraries.Comment: PhD Thesis, 2012 http://math.ucdenver.ed