SOFTWARE: Adaptive-XML: Tools for Collaborative Network Computing

Georgia Tech Research Corporation, Atlanta GA

Investigators

Abstract

Modern science is an increasingly distributed enterprise, particularly when addressing challenging scientific problems with multidisciplinary researchteams, where team members are routinely assembled from multiple universities,the national labs, and industry participants. A problem pervasive to suchdistributed endeavors is the need to efficiently share scientific data across multiple teams, sites, applications, and machines. This project's focus is on the ability to represent such data so that it is easily shared across research teams that each use their own, well-defined and domain-specific data representations. S(cientific)-XML is a suite of tools that translate user-friendly XML-based meta-information about shared data to/from the application-specific, efficient, binary-based data structure descriptions used by high performance scientific codes. With S-XML, end users can conveniently express and view their structured data, but all data manipulation and exchanges are performed using efficient binary data representations. Complementing these tools is the XML-ECho adaptive XML-conscious peer-to-peer communication infrastructure, which implements the wide-area exchange of the large-scale binary data used in scientific collaborations. This middleware uses runtime adaptation to dynamically adjust its data transport and manipulation actions to meet application-level quality of service needs. Specifically, via XML-based descriptions of data structure, end users can dynamically express and alter interest expression that state what data is most important to them and should therefore, be transported preferentially. The resulting Adaptive-XML tools and data exchange middleware will enable effective collaboration in scientific endeavors that remain infeasible with today's technologies, a concrete example being the Terascale Supernova Initiative now being undertaken by a large research team distributed across U.S. universities and national labs. Project outcomes will also benefit U.S. corporations, as evident from our discussions with companies like Schlumberger and also from the deployment of some of our technologies in industry testbed (e.g., at Delta Air Lines).