XSEDE12

EOT: FutureGrid Education: Using Case Studies to Develop Curriculum for Communicating Parallel and Distributed Computing Concepts

Abstract: The shift to parallel computing---including multi-core computer architectures, cloud distributed computing, and general-purpose GPU programming---leads to fundamental changes in the design of software and systems. As a result, learning parallel computing techniques in order to allow software to take advantage of the shift toward parallelism is of important significance. To this end, FutureGrid, an experimental testbed for cloud, grids, and high performance computing, provides a resource for anyone to find, share, and discuss modular teaching materials and computational platform supports. 

FutureGrid advances the education and training in distributed computing for organizations with less diverse computational resources; it accomplishes this through the development of instructional resources to include preconfigured environments for providing students with sandboxed virtual clusters. These can be used for either self-learning or teaching courses in parallel, cloud, and grid computing. FutureGrid’s education and outreach initiatives allow computational frameworks, such as, Google’s proprietary, MapReduce and the open-source Apache Hadoop to be applied to datasets of web scale. The availability of cloud computing platforms offer a variety of programming models, such as Hadoop and Twister, an iterative MapReduce framework, to make it feasible for anyone who wants to explore the data deluge without extensive local or personal investment in cluster computing. 

FutureGrid provides users with community-driven teaching modules, which provide conceptual principles of parallelism and hands-on practice with parallel computing, in self-contained units, which can be inserted in various environments in multiple curricular contexts. These modules offer an incremental approach to getting interested individuals the exposure to parallelism they will need to become participants in the concurrency evolution. 

This paper would present a series of case studies for experiences in parallel and distributed education using the FutureGrid testbed. Building on previous experiences from courses, workshops, and summer schools associated with FutureGrid, we present a viable solution to developing a curriculum by leveraging collaboration with organizations. Our approach to developing a successful guide stems from the idea of anyone interested in learning parallel and distributing computing can do so with minimum assistance from a domain expert, and it addresses the educational goals and objectives to help meet many challenges, which lie ahead in the discipline. We validate our approach to developing a community driven curriculum by providing use cases and their experiences with the teaching modules. Examples of some use cases include the following: a NCSA summer school for big data science, hosting a workshop for faculty members of historically black colleges and universities, courses in distributed and cloud computing at universities, such as Indiana University, University of Florida, Louisiana State University, and the University of Piemonte Orientale - A. Avogadro.