Massachusetts Institute of Technology (MIT)
The team at MIT is working in collaboration with Yale University and the University of Wisconsin at Madison on a comparative study, funded by a National Science Foundation (NSF) CLuE grant, of approaches to cluster-based, large-scale data analysis. In addition they are also independently studying Cloud Computing Infrastructure and Technology for Education.
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A Comparative Study of Approaches to Cluster-Based Large Scale Data Analysis |
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This is a collaborative study being conducted by MIT, University of Wisconsin, and Yale University. These three universities are using a National Science Foundation CLuE grants for a comparative study of approaches to cluster-based, large-scale data analysis. Both MapReduce and parallel database systems provide scalable data processing over hundreds to thousands of nodes, yet it's important for researchers to know the differences in performance and scalability of these two approaches to know which is more suitable when designing new data-intensive computing applications.
This project is engaged in systems research, much of which requires the ability to change the operating environment. Since this is not possible on the IBM/Google cluster, the project is also hosted on the Cloud Computi ....
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Cloud-Computing Infrastructure and Technology for Education (CITE) |
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This project will support the development of middleware that will enable numerical models to be run on commercial compute farms via cloud computing and exploited in ongoing and future classroom educational activities.
The intellectual merit of this work derives from two linked parts: (1) development of technology that would be suitable for many educational scenarios, including providing access to parallel computing resources in classrooms (K-12 on to university). Students and teachers would be able to run and interact with numerical models developed by leading researchers without the overhead of supporting software distributed to desktops in a school or the logistical headache of maintaining a cluster resource. Commercial compute farms would be exploited in which the technical `nitty-g ....
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