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
Floyd B. Hanson,
Computational Stochastic Control: Basic Foundations, Complexity and
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.
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.
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
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.
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.