DocumentCode
2224107
Title
Generosity and gluttony in GEMS: grid enabled molecular simulations
Author
Wozniak, J.M. ; Brenner, P. ; Thain, D. ; Striegel, A. ; Izaguirre, J.A.
Author_Institution
Dept. of Comput. Sci. & Eng., Notre Dame Univ., IN, USA
fYear
2005
fDate
24-27 July 2005
Firstpage
191
Lastpage
200
Abstract
Biomolecular simulations produce more output data than can be managed effectively by traditional computing systems. Researchers need distributed systems that allow the pooling of resources, the sharing of simulation data, and the reliable publication of both tentative and final results. To address this need, we have designed GEMS, a system that enables biomolecular researchers to store, search, and share large scale simulation data. The primary design problem is striking a balance between generosity and gluttony. On one hand, storage providers wish to be generous and share resources with their collaborators. On the other hand, an unchecked data producer can be gluttonous and easily replicate data unnecessarily until it fills all available space. To balance generosity and gluttony, GEMS allows both storage providers and data producers to state and enforce policies on the consumption of storage and the replication of data. By taking advantage of known properties of simulation data, the system is able to distinguish between high value final results that must be preserved and low value intermediate results that can be deleted and regenerated if necessary. We have built a prototype of GEMS on a cluster of workstations and demonstrate its ability to store new data, to replicate within policy limits, and to recover from failures.
Keywords
biology computing; digital simulation; grid computing; molecular biophysics; replicated databases; system recovery; workstation clusters; GEMS; biomolecular research; biomolecular simulation; data replication; data search; data storage; distributed systems; failure recovery; generosity; gluttony; grid enabled molecular simulations; resource pooling; resource sharing; simulation data sharing; workstation cluster; Biological system modeling; Biology computing; Collaboration; Computational modeling; Data engineering; Engineering management; Grid computing; Large-scale systems; Prototypes; Workstations;
fLanguage
English
Publisher
ieee
Conference_Titel
High Performance Distributed Computing, 2005. HPDC-14. Proceedings. 14th IEEE International Symposium on
ISSN
1082-8907
Print_ISBN
0-7803-9037-7
Type
conf
DOI
10.1109/HPDC.2005.1520959
Filename
1520959
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