This collection provides an overview of the 2008-'09 Open Education Cup competition. Contest rules, author resources, and example content are provided. This competition is intended to encourage development of original educational content in the field of parallel computing, with cash prizes awarded to contest winners. Selected modules will be included as part of a new collection available through Connexions.
Methodologies have been developed to allow parallel programming in a higher level. These include the Chemical Reaction Models, Linda, and Unity. We present the Chemical Reaction Models and its applications. An example in modeling a course maintenance system is given.
"This course introduces fundamentals of shared and distributed memory programming, teaches you how to code using openMP and MPI respectively, and provides hands-on experience of parallel computing geared towards numerical applications."
Modern computing platforms provide unprecedented amounts of raw computational power. But significant complexity comes along with this power, to the point that making useful computations exploit even a fraction of the potential of the computing platform is a substantial challenge. Indeed, obtaining good performance requires a comprehensive understanding of all layers of the underlying platform, deep insight into the computation at hand, and the ingenuity and creativity required to obtain an effective mapping of the computation onto the machine. The reward for mastering these sophisticated and challenging topics is the ability to make computations that can process large amount of data orders of magnitude more quickly and efficiently and to obtain results that are unavailable with standard practice. This class is a hands-on, project-based introduction to building scalable and high-performance software systems. Topics include performance analysis, algorithmic techniques for high performance, instruction-level optimizations, cache and memory hierarchy optimization, parallel programming, and building scalable distributed systems. The course also includes design reviews with industry mentors, as described in this MIT News article.
Subject:
Mathematics and Statistics, Science and Technology
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