Parallel scripting using cloud resources

Project Information

Discipline
Computer Science (401) 
Orientation
Research 
Abstract

We will develop and improve techniques for using the Swift parallel scripting language to leverage distributed cloud resources to execute scientific applications at a high degree of parallelism. We will test this on 4 applications: 1) protein structure prediction; 2) protein-RNA docking; 3) quantum-level simulation of glassy materials; 4) analysis of fMRI data

Intellectual Merit

This project will address the systems issues of dynamic resource aggregation, efficient data management without shared cluster filesystems, and scheduling across fluctuating application demand levels and resource availability levels.

Broader Impacts

The project will advance the ease-of-use of distributed cloud resources and make them more available to more scientists with less programming effort.

Project Contact

Project Lead
Michael Wilde (wilde) 
Project Manager
Michael Wilde (wilde) 
Project Members
David Kelly, Justin Wozniak, Ketan Maheshwari, Eugene Yan, Yonas Demissie, Thomas Uram  

Resource Requirements

Hardware Systems
  • hotel (IBM iDataPlex at U Chicago)
  • india (IBM iDataPlex at IU)
  • sierra (IBM iDataPlex at SDSC)
  • xray (Cray XM5 at IU)
 
Use of FutureGrid

To test applications in biochemistry and neuroscience using parallel scripting techniques to leverage and federate cloud resources.

Scale of Use

We would like to test on 4+ locations aggregating about 1000-2000 compute cores.We would run tests sporadically over several months, phasing in about 4 applications as they become ready.

Project Timeline

Submitted
12/01/2010 - 11:08 
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