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Blue matter on blue gene/L: massively parallel computation for biomolecular simulation
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Source International Conference on Hardware Software Codesign archive
Proceedings of the 3rd IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis table of contents
Jersey City, NJ, USA
SESSION: "BioChips and BioInformatics" table of contents
Pages: 207 - 212  
Year of Publication: 2005
ISBN:1-59593-161-9
Authors
Robert S. Germain  IBM Thomas J. Watson Research Center, Yorktown Heights, NY
Blake Fitch  IBM Thomas J. Watson Research Center, Yorktown Heights, NY
Aleksandr Rayshubskiy  IBM Thomas J. Watson Research Center, Yorktown Heights, NY
Maria Eleftheriou  IBM Thomas J. Watson Research Center, Yorktown Heights, NY
Michael C. Pitman  IBM Thomas J. Watson Research Center, Yorktown Heights, NY
Frank Suits  IBM Thomas J. Watson Research Center, Yorktown Heights, NY
Mark Giampapa  IBM Thomas J. Watson Research Center, Yorktown Heights, NY
T.J. Christopher Ward  IBM Hursley Park, Hursley, UK
Sponsors
SIGDA: ACM Special Interest Group on Design Automation
SIGBED: ACM Special Interest Group on Embedded Systems
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 10,   Downloads (12 Months): 76,   Citation Count: 6
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ABSTRACT

This paper provides an overview of the Blue Matter application development effort within the Blue Gene project that supports our scientific simulation efforts in the areas of protein folding and membrane-protein systems. The design philosophy of the Blue Gene/L architecture relies on large numbers of power efficient nodes (whose technology is derived from the world of embedded microprocessors) to enable packing of many such nodes into a small volume to achieve high performance. In order for an application to exploit the potential of this architecture, the application must scale well to large node counts. Because the scientific goals of the project entail simulating very long time-scales, up to microseconds, strong scaling of a fixed size problem to these large node counts is a requirement. In pursuit of this objective we have considered a variety of parallel decompositions and explored ways to exploit and map algorithms onto the two primary high performance interconnects provided by the Blue Gene architecture, the 3D-torus network and the collective network. Our current version of the application continues to speed up through 4096 nodes and is being used for studies of a protein/lipid system (for which some results have already been published) and for protein folding/unfolding simulations.


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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G. Almasi et al. Design and implementation of message-passing services for the Blue Gene/L supercomputer. IBM Journal of Research and Development, 49(2/3):393--406, 2005. http://www.research.ibm.com/journal/rd/492/almasi.pdf.
 
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M. C. Pitman, A. Grossfield, F. Suits, and S. E. Feller. Role of cholesterol and polyunsaturated chains in lipid-protein interactions: Molecular dynamics simulation of rhodopsin in a realistic membrane environment. Journal of the American Chemical Society, 127(13):4576--4577, 2005. http://dx.doi.org/10.1021/ja042715y.
 
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CITED BY  6

Collaborative Colleagues:
Robert S. Germain: colleagues
Blake Fitch: colleagues
Aleksandr Rayshubskiy: colleagues
Maria Eleftheriou: colleagues
Michael C. Pitman: colleagues
Frank Suits: colleagues
Mark Giampapa: colleagues
T.J. Christopher Ward: colleagues