QuakeSim Evaluation of FutureGrid for Cloud Computing

Project Details

Project Lead
Andrea Donnellan 
Project Manager
Andrea Donnellan 
Project Members
Marlon Pierce, Jun Wang, Eric Heien  
Supporting Experts
Fugang Wang, Gregor von Laszewski  
Institution
Jet Propulsion Laboratory, California Institute of Technology, Science Division  
Discipline
Geosciences (302) 
Subdiscipline
40.06 Geological and Related Sciences 

Abstract

QuakeSim is a multi-source, synergistic, data-intensive computing system to support modeling earthquake faults individually and as complex interacting systems. The project involves information technology research and development for data management and data-centric cloud computing. Numerous and growing online data sources from NASA, USGS, NSF, and other resources provide researchers with an exceptional opportunity to integrate varied data sources to support comprehensive efforts in data mining, analysis, simulation, and forecasting. QuakeSim is currently extending its web services infrastructure to cloud infrastructure to support fault modeling with a focus toward earthquake forecasting and response. The developed technology can support a wide array of science and engineering applications. The current focus of QuakeSim is to: 1) Develop bridging services within the QuakeSim service-oriented architecture that will integrate data from multiple sources, including interferogram, GPS position and velocity measurements, and seismicity; 2) Develop a fundamental cloud computing framework to support fault model optimization through the integration of multiple data types; 3) Develop cyberinfrastructure within the QuakeSim science gateway to handle the computing requirements of the optimization framework; 4) Improve the QuakeTables fault database to handle issues of model contribution, provenance, version tracking, commenting, rating, etc of fault models produced by the optimization framework; and 5) Use the improved fault models in downstream earthquake hazard assessment and forecasts.

Intellectual Merit

Understanding crustal deformation and fault behavior leads to improved forecasting, emergency planning, and disaster response. Accurate fault models supported through complementary information such as geologic observations, crustal deformation from InSAR and GPS, and seismicity. Fault models are subject to both known and unknown uncertainties that propagate through any analysis and downstream applications. Providing better constraints on the models by integrating multiple data collections, delivering these models through flexible, Web-based catalog services, and validating these models with numerous downstream applications will improve our understanding of earthquake processes. Analysis of crustal deformation data often indicates the existence of otherwise unknown faults. This project provides the computing infrastructure to identify, characterize, model and consider the consequences of unknown faults.

Broader Impacts

Handling large volumes of InSAR data and integrating the data with model applications is necessary for optimizing the utility of future NASA L-band radar missions, which will produce tremendous volumes of InSAR data products. Cloud compute infrastructure and analysis tools will allow NASA to realize the investment in an InSAR mission by generating a large user base that extends well beyond the typical domain experts.

Scale of Use

Initially a few VMs for an experiment. Eventually we will want production analysis for multiple jobs.

Results

http://quakesim.org