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Charisma: orchestrating migratable parallel objects
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Source
High Performance Distributed Computing archive
Proceedings of the 16th international symposium on High performance distributed computing table of contents
Monterey, California, USA
SESSION: Load balancing table of contents
Pages: 75 - 84  
Year of Publication: 2007
ISBN:978-1-59593-673-8
Authors
Chao Huang  University of Illinois at Urbana-Champaign
Laxmikant Kale  University of Illinois at Urbana-Champaign
Sponsors
ACM: Association for Computing Machinery
SIGARCH: ACM Special Interest Group on Computer Architecture
Publisher
ACM  New York, NY, USA
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ABSTRACT

The parallel programming paradigm based on migratable objects, as embodied in Charm++, improves programmer productivity by automating resource management. The programmer decomposes an application into a large number of parallel objects, while an intelligent run-time system assigns those objects to processors. It migrates objects among processors to effect dynamic load balance and communication optimizations. In addition, having multiple sets of objects representing distinct computations leads to improved modularity and performance. However, for complex applications involving many sets of objects, Charm++'s programming model tends to obscure the global flow of control in a parallel program: One must look at the code of multiple objects to discern how the multiple sets of objects are orchestrated in a given application. In this paper, we present Charisma, an orchestration notation that allows expression of Charm++ functionality without fragmenting the expression of control flow. Charisma separates expression of parallelism, including control flow and macro data-flow, from sequential components of the program. The sequential components only consume and publish data. Charisma expression of multiple patterns of communication among message-driven objects. A compiler generates Charm++ communication and synchronization code via static dependence analysis. As Charisma out puts standard Charm++ code, the functionality and performance benefits of the adaptive run-time system, such as automatic load balancing, are retained. In the paper, we show that Charisma programs scale up to 1024 processors without introducing undue overhead.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Laxmikant V. Kalé, Sameer Kumar, Gengbin Zheng, and Chee Wai Lee. Scaling molecular dynamics to 3000 processors with projections: A performance analysis case study. In Terascale Performance Analysis Workshop, International Conference on Computational Science(ICCS) Melbourne, Australia, June 2003.
 
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Ramkumar V. Vadali, Yan Shi, Sameer Kumar, L.V. Kale, Mark E. Tuckerman, and Glenn J. Martyna. Scalable ?ne-grained parallelization of plane-wave-based ab initio molecular dynamics for large supercomputers. Journal of Comptational Chemistry 25(16):2006--2022, Oct.2004.
 
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L. V. Kale and Attila Gursoy. Modularity,reuse and efficiency with message-driven libraries.In Proc. 27th Conference on Parallel Processing for Scientific Computing pages 738--743,February 1995.
 
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T. A. Darden, D. M. York, and L. G. Pedersen. Particle mesh Ewald. An N¿log(N)method for Ewald sums in large systems. JCP 98: 10089--10092, 1993.
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Jayant DeSouza and Laxmikant V.Kalé. MSA: Multiphase specifically shared arrays. In Proceedings of the 17th International Workshop on Languages and Compilers for Parallel Computing West Lafayette, Indiana,USA,September 2004.

Collaborative Colleagues:
Chao Huang: colleagues
Laxmikant Kale: colleagues