Parallel scripting using cloud resources

Project Details

Project Lead
Michael Wilde 
Project Manager
Michael Wilde 
Project Members
David Kelly, Justin Wozniak, Ketan Maheshwari, Eugene Yan, Yonas Demissie, Thomas Uram  
Supporting Experts
, Zhenhua Guo  
Argonne National Laboratory, Computation Institute  
Computer Science (401) 


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.

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.