Distributed Computing. Mark Govett Global Systems Division



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Transcription:

Distributed Computing Mark Govett Global Systems Division

Modeling Activities Prediction & Research Weather forecasts, climate prediction, earth system science Observing Systems Denial experiments Observing System Simulation Experiments (OSSEs) UAVs, GOES Sounder

Modeling Development Increasingly complex, higher resolution Local, Regional, Global, Climate FIM Model being developed at ESRL 15KM global 7 day forecast / run every day 1000 PEs on wjet, 6-8 hours per run Produces 1.3 TB total output per run Ensemble Modeling Systems Probabilistic forecasts Data Assimilation Higher spatial and temporal scales Systematic Model Testing & Verification WRF NMM & ARW require hundreds of runs per experiment

NOAA s High Performance Computing (HPC) Facilities West Virginia Princeton Boulder Silver Springs Internet

NOAA s Primary Responsibility: to manage and provide data or information Model Data - Local, Regional, Global - Ocean, Atmospheric, etc Archive Data - Model Development - Model Verification - Observing System Experiments - Model Comparisons Observations - Expect a 100 fold increase in 7 years - GSD will manage more global data than ever

Data Access & Discovery Data Management Stovepipes Difficult to locate and obtain data Manually pull files from NCEP (eg. FTP) Difficulty in running long simulations Locate, store and stage data We cannot continue to store all the data Requires data integration solutions Standard solutions for defining, locating and accessing the data we need.

Future Data Growth Global Earth Observation System of Systems Needs technical solutions for system integration New observing systems GOES-R, NPOESS, National Composite Radar High resolution models, ensembles How can NOAA handle and effectively utilize these data? Support operational requirements Enable model research and development

End goal - A fully wired, networked and integrated system that provides for data processing, distribution, & archiving - C. Lautenbacher, NOAA Administrator

The Grid: An IT Infrastructure for NOAA in the 21 st Century Mark Govett, Mike Doney, Paul Hyder May 2004 To meet challenges facing NOAA in the next decade and beyond 100 Fold Increase in Data Volume in 10 years GOES-R, NPOESS, IEOS, Radar, GPS More Complex Modeling Systems higher resolutions, ensembles, data assimilation, more data Proposed an Integrated IT Infrastructure based on Grids Build Compute Grids to link HPC resources Build on existing data systems (e.g. CLASS, NOMADS) Develop Dynamic Data Discovery, Access, Integration Utilize & Develop Web Services, Grid Portals

Grid Computing Infrastructure Links compute, data, network resources Compute Grids HPC resources (eg. TeraGrid) dedicated computers within an organization desktop systems together (cycle harvester) Vendor supported grid computing Data Grids Link only data resources together Easier to implement due to security issues

Compute Grid Challenges Software was not sufficiently mature Limitations Security trust relationships ESRL 3 1 NCEP Grid Authority 2

Computing Distributed Computing Push for single authentication mechanism at NOAA Cross NOAA HPC job scheduling Data Access, Discovery & Integration Web Services Integration via Standards

NOAA s High Performance Computing (HPC) Facilities West Virginia Princeton Boulder Silver Springs Job Scheduler Internet

Web Services A unit of work done by a provider to achieve desired end results for a consumer. Platform Independent Standard way to communicate between services, client applications Access data, produce a forecast Link web services via a Service Oriented Architecture (SOA)

Open Geospatial Consortium (OGC) Web Services Standards for data access Web Mapping Service (WMS) To access maps, images Web Feature Service (WFS) To access point or feature data Web Coverage Service (WCS) To access gridded data Widely adopted but deficient for Earth Science Community

Web Coverage Service composite radar data national coverage every 5 minutes retrieve some portion of the data efficiently integrate with other data for verification, forecasting, etc

Questions?