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Programming with cluster openMP

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Jay P. HoeflingerAuthors Info & Claims

PPoPP '07: Proceedings of the 12th ACM SIGPLAN symposium on Principles and practice of parallel programming

Page 270

https://doi.org/10.1145/1229428.1229482

Published: 14 March 2007 Publication History

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Abstract

This full-day tutorial will teach the attendees about Cluster OpenMP and the tools that are available to assist the programmer in debugging and tuning. Cluster OpenMP is an Intel® programming system that allows the user to run an OpenMP program on a cluster of computers without a common hardware shared memory. The tutorial will consist of a short tutorial on OpenMP, a longer description of Cluster OpenMP, its concepts, mechanisms and tools, a set of short hands-on porting exercises for the participants, and a set of exercises with the Cluster OpenMP debugging and tuning tools.

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Burger JChapman RVillanustre F(2011)Parallel Processing, Multiprocessors and Virtualization in Data-Intensive ComputingHandbook of Data Intensive Computing10.1007/978-1-4614-1415-5_9(235-248)Online publication date: 11-Nov-2011
https://doi.org/10.1007/978-1-4614-1415-5_9
Karantasis KPolychronopoulos EEkaterinaris J(2010)Acceleration of a High Order Accurate Method for Compressible Flows on SDSM Based GPU ClustersProceedings of the 2010 IEEE 16th International Conference on Parallel and Distributed Systems10.1109/ICPADS.2010.107(460-467)Online publication date: 8-Dec-2010
https://dl.acm.org/doi/10.1109/ICPADS.2010.107
Karantasis KPolychronopoulos EDimitrakopoulos G(2010)Accelerating data clustering on GPU-based clusters under shared memory abstraction2010 IEEE International Conference On Cluster Computing Workshops and Posters (CLUSTER WORKSHOPS)10.1109/CLUSTERWKSP.2010.5613079(1-5)Online publication date: Sep-2010
https://doi.org/10.1109/CLUSTERWKSP.2010.5613079
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Index Terms

Programming with cluster openMP
1. Computing methodologies
  1. Parallel computing methodologies
    1. Parallel programming languages
2. Software and its engineering
  1. Software notations and tools
    1. General programming languages
      1. Language types
        Parallel programming languages
  2. Software organization and properties
    1. Software system structures
      1. Distributed systems organizing principles
        Organizing principles for web applications

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PPoPP '07: Proceedings of the 12th ACM SIGPLAN symposium on Principles and practice of parallel programming

March 2007

284 pages

ISBN:9781595936028

DOI:10.1145/1229428

General Chair:
Katherine Yelick
UC Berkeley and Lawrence Berkeley National Lab., USA
,
Program Chair:
John Mellor-Crummey
Rice University, USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 14 March 2007

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PPoPP07

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PPoPP07: ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming

March 14 - 17, 2007

California, San Jose, USA

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PPoPP '07 Paper Acceptance Rate 22 of 65 submissions, 34%;

Overall Acceptance Rate 230 of 1,014 submissions, 23%

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Burger JChapman RVillanustre F(2011)Parallel Processing, Multiprocessors and Virtualization in Data-Intensive ComputingHandbook of Data Intensive Computing10.1007/978-1-4614-1415-5_9(235-248)Online publication date: 11-Nov-2011
https://doi.org/10.1007/978-1-4614-1415-5_9
Karantasis KPolychronopoulos EEkaterinaris J(2010)Acceleration of a High Order Accurate Method for Compressible Flows on SDSM Based GPU ClustersProceedings of the 2010 IEEE 16th International Conference on Parallel and Distributed Systems10.1109/ICPADS.2010.107(460-467)Online publication date: 8-Dec-2010
https://dl.acm.org/doi/10.1109/ICPADS.2010.107
Karantasis KPolychronopoulos EDimitrakopoulos G(2010)Accelerating data clustering on GPU-based clusters under shared memory abstraction2010 IEEE International Conference On Cluster Computing Workshops and Posters (CLUSTER WORKSHOPS)10.1109/CLUSTERWKSP.2010.5613079(1-5)Online publication date: Sep-2010
https://doi.org/10.1109/CLUSTERWKSP.2010.5613079
Li JHei DYan L(2009)Correctness Analysis Based on Testing and Checking for OpenMP ProgramsProceedings of the 2009 Fourth ChinaGrid Annual Conference10.1109/ChinaGrid.2009.12(210-215)Online publication date: 21-Aug-2009
https://dl.acm.org/doi/10.1109/ChinaGrid.2009.12

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Performance comparison of MPI and three openMP programming styles on shared memory multiprocessors

MPI and OpenMP paradigms on cluster of SMP architectures: the vacancy tracking algorithm for multi-dimensional array transposition

Implementation of OpenMP Data-Sharing on CAPE

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