In this special session, we will compare and contrast several game engines that have been used in game development courses, and describe our experiences teaching such courses.

This 90-minute panel session will discuss recent and future developments in incorporating Computational Science and Engineering into the undergraduate curriculum. There is a companion session devoted to tools and techniques and so the focus here is on programs and courses.The panelists will demonstrate a clear uniformity of purpose but a wide variety of approaches to increasing the CSE experience of undergraduates in different types of schools.The schools represented vary from large state universities to small private liberal arts colleges and a medium-sized school with a strong engineering bias.The approaches adopted also differ. There are complete programs built largely from existing courses, specific courses that are added to established programs to allow a student to follow an emphasis in CSE. The introduction of CSE into existing programs through faculty advice and education has also been successful.Yet other approaches represented among the panelists are the introduction of multi-disciplinary team-taught project-based courses as a springboard for growing an undergraduate CSE program including undergraduate research projects. The incremental use of small add-on courses to supplement conventional mathematics offerings with some CSE content has also been used successfully.Another approach represented on the panel is the use of a particular vehicle --- in this case graphics and visualization --- to introduce key ideas of CSE into regular parts of the curriculum.The unifying theme of the panel --- the desire to improve undergraduate CSE education will be evident throughout. By presenting a wide variety of approaches to achieve this end, it is hoped that any audience participants who wish to create a CSE thread in their own programs will find some ideas to help them. Some of the practical and political issues will also be discussed in the various contexts.The program for the panel would allow each panelist a maximum of 10 minutes to outline their programs and approaches. The remaining 30 (or more) minutes would then be reserved for general discussion and questions and contributions from the audience.

No abstract available.

Results from the development and teaching of a senior-level undergraduate multidisciplinary course in high performance computing are presented. Having been taught four times, there are several "Lesson Learned" presented in this paper. Help from the technical staff at the San Diego Supercomputer Center and support from the National Science Foundation has been instrumental in the evolution of this course. The work of faculty at other universities has influenced the author's courses and is gratefully acknowledged. A subsequent sophomore level course was developed at SDSU and has become part of a voluntary, cooperative program, Undergraduate Computational Science and Engineering.

Several strategies for replica maintenance are considered, and the benefits of each are analyzed. Formulas describing the reliability of the replicated data object are presented, and closed-form solutions are given for the tractable cases. Numerical solutions, validated by simulation results, are used to analyze the tradeoffs between reliability and storage cost. With estimates of the mean times to site failure and repair in a given system, the numerical techniques presented can be applied to predict the fewest number of replicas required to provide the desired level of reliability.>

The accessibility of vital information can be enhanced by replicating the data on several sites and employing a consistency control protocol to manage the replicas. The reliability of a replicated data object depends on maintaining a viable set of current replicas. When storage is limited, it may not be feasible to simply replicate a data object at enough sites to achieve the desired level of reliability. Regeneration approximates the reliability provided by additional replicas for a modest increase in storage costs, and is applicable whenever a new replica of a data object can be created faster than a system failure can be repaired. Regeneration enhances reliability by creating new replicas on other sites in response to site failures. Several strategies for replica maintenance are considered, and the benefits of each are analyzed using simulation and both algebraic and numeric solutions to systems of differential equations.>

Methods based on backward differentiation formulas (BDFs) for solving stiff differential equations require iterating to approximate the solution of the corrector equation on each step.One hope for reducing the cost of this is to make do w~th iteration matrices that are known to have errors and to do no more iterations than are necessary to maintain the stability of the method.This paper, following work by Klopfenstem, examines the effect of errors m the iteration matrix on the stability of the method.Apphcation of the results to an algorithm is discussed briefly.