Generosity and gluttony in GEMS: grid enabled molecular simulations

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.

[1]  Matei Ripeanu,et al.  Peer-to-peer architecture case study: Gnutella network , 2001, Proceedings First International Conference on Peer-to-Peer Computing.

[2]  David R. Karger,et al.  Chord: a scalable peer-to-peer lookup protocol for internet applications , 2003, TNET.

[3]  Stuart Murdock,et al.  BioSimGrid: towards a worldwide repository for biomolecular simulations. , 2004, Organic & biomolecular chemistry.

[4]  Andrea C. Arpaci-Dusseau,et al.  Flexibility, manageability, and performance in a Grid storage appliance , 2002, Proceedings 11th IEEE International Symposium on High Performance Distributed Computing.

[5]  Miron Livny,et al.  A worldwide flock of Condors: Load sharing among workstation clusters , 1996, Future Gener. Comput. Syst..

[6]  Micah Beck,et al.  The Internet Backplane Protocol: Storage in the Network , 1999 .

[7]  Steven Tuecke,et al.  Protocols and services for distributed data-intensive science , 2002 .

[8]  Dan Walsh,et al.  Design and implementation of the Sun network filesystem , 1985, USENIX Conference Proceedings.

[9]  Ben Y. Zhao,et al.  OceanStore: an architecture for global-scale persistent storage , 2000, SIGP.

[10]  Miguel Castro,et al.  Farsite: federated, available, and reliable storage for an incompletely trusted environment , 2002, OPSR.

[11]  Peter Z. Kunszt,et al.  Giggle: A Framework for Constructing Scalable Replica Location Services , 2002, ACM/IEEE SC 2002 Conference (SC'02).

[12]  Lustre : A Scalable , High-Performance File System Cluster , 2003 .

[13]  Rajesh Raman,et al.  Matchmaking: distributed resource management for high throughput computing , 1998, Proceedings. The Seventh International Symposium on High Performance Distributed Computing (Cat. No.98TB100244).

[14]  Robert Morris,et al.  Chord: A scalable peer-to-peer lookup service for internet applications , 2001, SIGCOMM 2001.

[15]  Sergey Brin,et al.  The Anatomy of a Large-Scale Hypertextual Web Search Engine , 1998, Comput. Networks.

[16]  Mahadev Satyanarayanan,et al.  Scale and performance in a distributed file system , 1987, SOSP '87.

[17]  Thierry Matthey,et al.  ProtoMol, an object-oriented framework for prototyping novel algorithms for molecular dynamics , 2004, TOMS.

[18]  Aaron Striegel,et al.  GIPSE: streamlining the management of simulation on the grid , 2005, 38th Annual Simulation Symposium.

[19]  Robert B. Ross,et al.  PVFS: A Parallel File System for Linux Clusters , 2000, Annual Linux Showcase & Conference.

[20]  Antony I. T. Rowstron,et al.  Storage management and caching in PAST, a large-scale, persistent peer-to-peer storage utility , 2001, SOSP.

[21]  Yong Zhao,et al.  Chimera: a virtual data system for representing, querying, and automating data derivation , 2002, Proceedings 14th International Conference on Scientific and Statistical Database Management.

[22]  Douglas Thain Chirp: An Architecture for Cooperative Storage , 2005 .

[23]  David J. DeWitt,et al.  Shoring up persistent applications , 1994, SIGMOD '94.