Projects

NEESgrid is a national collaboratory for earthquake engineering, created as part of the NSF-funded Network for Earthquake Engineering Simulation (NEES) project. NEESgrid allows earthquake engineers to share data and, using a grid-based telecontrol service developed for this project, perform distributed experiments that combine computational simulations with large-scale physical experiments running at geographically (and organizationally) distant sites.

Related Documents:

• Distributed Hybrid Earthquake Engineering Experiments: Experiences with a Ground-Shaking Grid Application :: L. Pearlman, C. Kesselman, S. Gullapalli, B.F. Spencer, Jr., J. Futrelle, K. Ricker, I. Foster, P. Hubbard, C. Severance. To appear in Proc. 13th IEEE Symp. on High Performance Distributed Computing, June 2004.
  

The Globus Project is run by the Globus Alliance, which conducts research and development to create fundamental technologies behind the "Grid," allowing people to share computing power, databases, and other on-line tools securely across corporate, institutional, and geographic boundaries without sacrificing local autonomy.

The Alliance produces open-source software (including the Globus Toolkit) that is central to science and engineering activities totalling nearly a half-billion dollars internationally and is the substrate for significant Grid products offered by leading IT companies.

The Alliance is based at the following institutes:

• University of Southern California's Information Sciences Institute
• Argonne National Laboratory
• University of Chicago
• University of Edinburgh
• Sweden's Center for Parallel Computers

Pegasus , which stands for Planning for Execution in Grids, was developed at ISI as part of the GriPhyN project.  Pegasus is a configurable system that can map and execute complex workflows on the Grid. Pegasus has been integrated with the GriPhyN Chimera system. In that configuration, Pegasus receives an abstract workflow (AW) description from Chimera, produces a concrete workflow (CW), and submits it to Condor's DAGMan for execution. The abstract workflow describes the transformations and data in terms of their logical names. The concrete workflow, which specifies the location of the data and the execution platforms, is optimized by Pegasus from the point of view of Virtual Data. If data products described within AW are found to be already materialized (via queries to the Globus Replica Location Service (RLS)), Pegasus reuses them and thus reduces the complexity of CW.

Pegasus can also be configured to perform the generation of the abstract workflow based on application-level metadata attributes. Given attributes such as time interval, frequency of interest, location in the sky, etc., Pegasus is currently able to produce any virtual data products present in the LIGO pulsar search.  The figure below shows the visualization of the search shown at SC 2002. This configuration of Pegasus is based on AI-planning technologies. To find out more about planning process, click here.