MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Microwulf: a beowulf cluster for every desk
Proceedings of the 39th SIGCSE technical symposium on Computer science education
Hadoop at home: large-scale computing at a small college
Proceedings of the 40th ACM technical symposium on Computer science education
A view of the parallel computing landscape
Communications of the ACM - A View of Parallel Computing
A cluster for CS education in the manycore era
Proceedings of the 42nd ACM technical symposium on Computer science education
WebMapReduce: an accessible and adaptable tool for teaching map-reduce computing
Proceedings of the 42nd ACM technical symposium on Computer science education
Modules in community: injecting more parallelism into computer science curricula
Proceedings of the 42nd ACM technical symposium on Computer science education
Strategies for preparing computer science students for the multicore world
Proceedings of the 2010 ITiCSE working group reports
Teaching parallelism with GPUS and a Game of life assignment
Journal of Computing Sciences in Colleges
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It is no longer news that undergraduates in computer science need to learn more about parallelism. The range of options for parallel programming is truly staggering, involving hundreds of languages. How can a CS instructor make informed choices among all the options? This panel provides a guided introduction to parallelism in programming languages and their potential for undergraduate CS education, organized into four progressive categories: low-level libraries and; higher-level libraries and features; programming languages that incorporate parallelism; and frameworks for productive parallel programming. The four panelists will present representative examples in their categories, then present viewpoints on how those categories relate to coursework, curriculum, and trends in parallelism.