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High Performance Multi-Paradigm Messaging Runtime Integrating Grids and Multicore Systems
Xiaohong Qiu¹
xqiu@indiana.edu
¹Research Computing UITS
Indiana University Bloomington
Geoffrey C. Fox², Huapeng Yuan², Seung-Hee Bae²
gcf@indiana.edu yuanh@indiana.edu sebae@indiana.edu
²Community Grids Laboratory
Indiana University Bloomington
George Chrysanthakopoulos³, Henrik Frystyk Nielsen³
georgioc@microsoft.com henrikn@microsoft.com
³Microsoft Research
Redmond WA

eScience applications need to use distributed Grid environments where each component is an individual or cluster of multicore machines. These are expected to have 64-128 cores 5 years from now and need to support scalable parallelism. Users will want to compose heterogeneous components into single jobs and run seamlessly in both distributed fashion and on a future “Grid on a chip” with different subsets of cores supporting individual components. We support this with a simple programming model made up of two layers supporting traditional parallel and Grid programming paradigms (workflow) respectively. We examine for a parallel clustering application, the Concurrency and Coordination Runtime CCR from Microsoft as a multi-paradigm runtime that integrates the two layers. Our work uses managed code (C#) and for AMD and Intel processors shows around a factor of 5 better performance than Java. CCR has MPI pattern and dynamic threading latencies of a few microseconds that are competitive with the performance of standard MPI for C.

 

  • Supporting materials

Figure/Table # File name Worksheet #
Table1
Testing_environment
AMD4core_2.19Ghz_64bitXPPro_basic_computation.xls
Intel4core_2.80Ghz_64bitXPPro_basic_computation.xls
Intel8core_2.66Ghz_64BitVista_basic_computation.xls
N/A
1
1
1
1 clustering results 1
5(a) AMD4core_2.19Ghz_64bitXPPro_all.xls 7
5(b) intel8core2.66Ghz_64bitVista_all.xls 7
Table2 Intel8core_2.66Ghz_64BitVista_Table1_all.xls 4
Others MPJE_tests_on_DOUBLEAMD  


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