Floyd B. Hanson

Laboratory for Advanced Computing

Annotated Publications in
Education and Training:
Supecomputing and Control

34[SC88]. F. Hanson, T. Moher, N. Sabelli and A. Solem, A training program for scientific supercomputing users, in Proc. Supercomputing '88, pp. 342-349, November 1988.

This paper, presented by Sabelli at the Supercomputing '88 conference, Reno, NV, November 1989, describes the UIC Workshop Program on Scientific Supercomputing. In this program students brings a large scale research problem with code that has potential for optimization and testing on various supercomputers, such as the Cray X-MP48, IBM 3090 600E/VF and Alliant FX/8. The workshop uses intense instruction, clinics, and invited as well as local instructors for selected participants, who participate full time. The topics include vectorization, parallelization, numerical method, operating systems, graphical visualization, software engineering and vendor presentations. The workshop was also presented as a full-day tutorial at Supercomputing '88 and '90 by Sabelli, Solem and others.

41[SC90]. F. B. Hanson, A Real Introduction to Supercomputing: A User Training Course , in Proc. Supercomputing '90, pp. 376-385, November 1990.

(Click to FTP Postscript Copy?)
In this paper, the principal investigator's supercomputing course is discussed. Knowledge and techniques gained in supercomputing research have been transferred to this graduate computer science course. The paper was presented at the Supercomputing '90 conference, New York, NY, November 1990. The course uses NSF supported National Center for Supercomputing Applications Cray X-MP/48 and Cray 2S/128, as well as the Argonne National Laboratory Alliant FX/8. This course helps our graduate students maintain leading edge capabilities in computing.

84[FGCS03]. F. B. Hanson, Local Supercomputing Training in the Computational Sciences Using Remote National Centers, Future Generation Computer Systems: Special Issue on Education in the Computational Sciences, vol. 19, pp. 1335-1347, November 2003.

Local training for high performance computing using remote national supercomputing centers is quite different from training at the centers themselves or using local machines. The local site computing and communication resources are a fraction of those available at the national centers. However, training at the local site has the potential of training more computational science and engineering students in high performance computing by including those who are unable to travel to the national center for training. The experience gained from supercomputing courses and workshops in the last seventeen years at the University of Illinois at Chicago is described. These courses serve as the kernel in the program for training computational science and engineering students. Many training techniques, such as the key local user's guides and starter problems, that would be portable to other local sites are illustrated. Training techniques are continually evolving to keep up with rapid changes in supercomputing. An essential feature of this program is the use of real supercomputer time on several supercomputer platforms at national centers with emphasis in solving large scale problems.

88[CDC03]. Floyd B. Hanson, Computational Stochastic Control: Basic Foundations, Complexity and Techniques, Proceedings of 2003 Conference on Decision and Control, Invited Poster/Interactive Paper in a Control Education Session, pp. 3024-3029, December 2003.

Longer 9 page Submitted Version.

Abstract: Much research in control systems is purely mathematical, but advances in stochastic control problem solving can be used beyond the limits of where theoretical mathematics can help. Theoretical and computational mathematics are complementary. Computation is important where the problem is mathematically intractable, of high dimension as in stochastic dynamic programming or solving the problem is urgent as in competitive financial engineering predictions. Many advances in solving large scale control problems have been gained through technical improvements in computing hardware, but as many advances have been made in the development of new and better algorithms, the theoretical side of computation. Both analysis and computation are important in solving problems. Both rely on mathematics, but rely on them in different ways. An important part of educational training is general preparation for problem solving since the postgraduate job is uncertain in the current world.

In this expository paper, a selection of basic computational considerations, high performance computers and some useful algorithms are surveyed. Some of the computational methodology in both algorithms and advanced computers arose from the author's own research. Much of the knowledge has been transferred to classes in computation and control, so that student instruction is at the leading edge, a buffer against obsolescence. An important general lesson in computational education is that the computation, if done properly, forms the other half of mathematics, beyond the topics of regular or traditional mathematics courses. Computation has its own algebra, oriented to finite precision arithmetic, and its own analysis that is numerically oriented. The view is that of an applied analyst and computational control scientist explaining the field to those with a regular mathematics background.

90[CSM04]. Molly H. Shor and Floyd B. Hanson, " Bringing Control to Students and Teachers,," Control Systems Magazine, vol. 24, no. 3, pp. 20-30, June 2004.

Abstract: CDC03 Conference Report on ``Ideas and Technology of Control Systems: NSF Workshop for Middle School and High School Students and Teachers'' in Maui, Hawaii in December 2003. See CSM issue for figures and sidebars.