Workshop Descriptions

The Parallel Programming & Cluster Computing workshop focuses on techniques and tools for parallel computing. Much of this workshop concentrates on distributed parallelism (MPI); in addition, shared memory parallelism (OpenMP), instruction level parallelism, Graphics Processing Unit parallelism and hybrid shared/distributed parallelism are also explored. Participants will learn about developing, debugging, profiling and tuning of parallel applications across a variety of architectures, using tools from a variety of sources, including GNU, Intel, TotalView, and the Bootable Cluster CD. The material is designed for undergraduate faculty from a variety of disciplines who would like to add parallel computing to their undergraduate teaching and research. In addition, undergraduate and graduate students are encouraged to attend alongside a sponsoring faculty member. The workshop is hands-on, with exercises in both programming and curriculum development.

This workshop will cover various ways that computers can be used to enhance and expand the educational experience of students enrolled in the undergraduate chemistry curriculum. Discussions and hands-on laboratory exercises on visualization, simulation, molecular modeling, and mathematical software will be presented.

The purpose of this workshop is to expose participants to and inspire them with new techniques, teaching materials, and applications to use computational models in the undergraduate curriculum. By bringing faculty from different disciplines together so that they can learn how to incorporate computational models into their classrooms and research projects, it will advance the use of computing in undergraduate science education. We desire to have participants from a broad range of disciplines, including computer science, mathematics, and the natural sciences.

This workshop will introduce college faculty to various resources that can be used to prepare students to acquire computational thinking, modeling and quantitative analysis skills that have become essential to the practice of modern biology. Hands-on sessions with software for building and running dynamic models, finding sequence motifs, inferring phylogeny and predicting structure will be coupled with pedagogy and examples of integration into the biology classroom. Hands-on tutorials on first two days will focus on: NetLogo for agent-based and system dynamics modeling; MATLAB/Scilab for flexible graphing, analysis and numerical computing; Biology Workbench for bioinformatics; and Gromacs for molecular dynamics. The focus will then shift to group work to develop materials for the classroom, with additional sessions based on participant interest.

This workshop focuses on Physics education augmented with the resources of high performance computing (HPC). Primary workshop content draws from the traditional parallel computing curriculum, but additional focus is placed on the use of creating curricular content that demonstrates the use of high performance computing hardware to solve modern-day HPC problems.

This workshop focuses on applications of computational science in engineering and bioengineering education. The workshop will build upon earlier workshops held at SC08 Education Program in Austin, Texas and provide more in-depth work with undergraduate and graduate engineering faculty as well as interested professionals from industry. The workshop will introduce the basic competencies for modeling and simulation for undergraduate engineers and provide hands-on examples using MATLAB, Vensim, and other modeling tools. This will allow for more advanced sessions in using parallel MATLAB for signal image processing and several other possible applications, computational fluid dynamics using the Open Foam, open source package, and one or two other subareas depending upon demand.

The purpose of this workshop is to expose participants to and inspire them with new techniques, teaching materials, and applications to use computational models in the grades 6-12 classroom. By bringing teachers from different disciplines together so that they can learn how to incorporate computational models into their classrooms, it will advance the use of computing in science education.