Transparent Grid Enablement of Weather Research and Forecasting S. Masoud Sadjadi1, Liana Fong6, Rosa M. Badia2, Javier Figueroa1,9, Javier Delgado1, Xabriel J. Collazo-Mojica8, Khalid Saleem1, Raju Rangaswami1, Shu Shimizu4, Hector A. Duran Limon5, Pat

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Transparent Grid Enablement ofWeather Research
and ForecastingS. Masoud Sadjadi1, Liana Fong6,
Rosa M. Badia2, Javier Figueroa1,9, Javier
Delgado1, Xabriel J. Collazo-Mojica8, Khalid
Saleem1, Raju Rangaswami1, Shu Shimizu4, Hector
A. Duran Limon5, Pat Welsh3, Sandeep Pattnaik10,
Anthony Praino6, David Villegas1, Selim Kalayci1,
Gargi Dasgupta7, Onyeka Ezenwoye1, Juan Carlos
Martinez1, Ivan Rodero2, Shuyi Chen9, Javier
Muñoz1, Diego Lopez1, Julita Corbalan2, Hugh
Willoughby1, Michael McFail1, Christine Lisetti1,
and Malek Adjouadi11 Florida International
University (FIU), Miami, Florida, USA 2
Barcelona Supercomputing Center, Barcelona,
Spain 3 University of North Florida,
Jacksonville, Florida, USA 4 IBM Tokyo Research
Laboratory, Tokyo, Japan 5 University of
Guadalajara, CUCEA, Mexico 6 IBM T. J. Watson,
NY, USA 7 IBM IRL, India 8 University of
Puerto Rico, Mayaguez Campus, Puerto Rico 9
University of Miami, Coral Gables, Florida, USA
10 Florida State University, Tallahassee,
Florida, USAContact sadjadi_at_cs.fiu.edu
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Outline

• Motivation
• Grid Enablement
• Application and Scenario
• System Overview
• Remaining Challenges Lessons Learned

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Motivation

• Weather Prediction can
• Save Lives
• Help Business Owners
• How?
• Accurate Results
• Precise Location Information
• What do we have?
• WRF Weather Research Forecast
• The Weather Research and Forecasting (WRF) Model
  is a next-generation mesocale numerical weather
  prediction system designed to serve both
  operational forecasting and atmospheric research
  needs.

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Motivation (Cont.)

• WRF Status
• Single Machine/Cluster
• Single Domain
• Fine Resolution -gt Resource Requirements
• How to Overcome this?
• Through Grid Enablement
• Expected Benefits to WRF
• More available resources Different Domains
• Faster results
• Improved Accuracy

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Grid Enablement

• Grid-enabling is the practice of taking existing
  applications, which currently run on a single
  node or on a cluster of homogeneous nodes, and
  adapt them (either automatically or manually) so
  that they can be deployed over non-homogeneous
  computing resources connected through the
  Internet across multiple organizational
  boundaries (e.g., multiple clusters from
  different organizations) without major
  modifications to the underlying source code.
• Grid-enablement process successful if the
  resulting Grid-enabled application performs
  better than the original application.
• Performs better can be interpreted differently
• Improved execution time, better resource
  utilization, enabling collaboration,

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Application and ScenarioThree-Layer Nested Domain
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Application and ScenarioThree-Layer Nested Domain
15 km
5 km
1 km
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Application and ScenarioThree-Layer Nested Domain
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System Overview

• Web-Based Portal
• Grid Middleware (Plumbing)
• Job-Flow Management
• Meta-Scheduling
• Profiling and Benchmarking
• Development Tools and Environments
• Transparent Grid Enablement (TGE)
• TRAP Static and Dynamic adaptation of programs
• TRAP/BPEL, TRAP/J, TRAP.NET, etc.
• GRID superscalar Programming Paradigm for
  parallelizing a sequential application
  dynamically in a Computational Grid

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System Architecture
Grid Middleware
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Web-Based Portal Screenshot
Meteorologist Login Interface
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Web-Based Portal Screenshot
Business Owners/Emergency Officials Login
Interface
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Grid Middleware

• Middleware
• A layer between network operating systems and
  applications that aims to resolve heterogeneity
  and distribution
• Examples CORBA, Javas RMI and .NET.
• Grid Middleware
• Middleware for Grid Enablement
• Examples Globus, Legion, Condor-G, etc.

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Peer-to-Peer Inter-Domain Interactions
Meteorologist
Meteorologist
BSC
FIU
Web-Base Portal
Web-Base Portal
Job-Flow Manager
Job-Flow Manager
Peer-to-peer Protocols
Meta-Scheduler
Meta-Scheduler
Resource Policies
Resource Policies
Loca scheduler
Loca scheduler
Loca scheduler
Loca scheduler
Local Resources
Local Resources
Local Resources
Local Resources
C
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Peer-to-Peer Inter-Domain Interactions
Meteorologist
Meteorologist
BSC
FIU
Web-Base Portal
Web-Base Portal
Job-Flow Manager
Job-Flow Manager
Peer-to-peer Protocols
Meta-Scheduler
Meta-Scheduler
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Resource Policies
Resource Policies
Loca scheduler
Loca scheduler
Loca scheduler
Loca scheduler
Local Resources
Local Resources
Local Resources
Local Resources
C
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Peer-to-Peer Inter-Domain Interactions
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Fault-Tolerant Job-Flow Management
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Job Flow Management Architecture
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The Meta-Scheduling Protocol
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FIU Meta-Scheduler Internal Architecture
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Better Scheduling by Modeling WRF Behavior
Mathematical Modeling
An Iterative Process
An Incremental Process
Profiling
Code Inspection Modeling
Modeling WRF Behavior
Start
Parameter Estimation
Texe ( ?0 ?1 / nodes ) ( ?0 ?1 / clock )
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ResultsExecution Time Vs Allocated CPU
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ResultsModel Validation A Linear Model!
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Challenges remain to be addressed

• High latency of Internet compared to high-speed
  LANs
• High overhead of the Grid middleware software
• Risking compatibility with future WRF versions
• High volume of the WRF sources code
• Compiling WRF on unsupported platforms

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Lessons Learned

• No current and complete methodology for Grid
  Enablement
• Grid enabling cluster applications Issues LAN vs
  WAN
• WRF lack of enough documentation, old
  programming techniques
• Mathematical Model May Optimize Speedup but
  also Error Margin More Clusters Needed
• Still on early stage of Concrete Scenario for
  Forecast Ensemble

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Acknowledgements

• We are thankful to the following individuals for
  their
• contributions to some of the ideas presented in
  this paper Yanbin Liu, Norman Bobroff, Balaji
  Viswanathan, Steve Luis, Shu-Ching Chen, Lloyd
  Trinish, Jason Liu, Alex Orta, T. N.
  Krishnamurti, Eric Johnson, and Donald Llopis.
• This work was supported in part by IBM (SUR and
  Student Support awards), the National Science
  Foundation (grants OISE-0730065, OCI-0636031,
  REU-0552555, and HRD-0317692). This work is part
  of the Latin American Grid (LA Grid) project

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• Contact Information
• S. Masoud Sadjadi
• http//www.cs.fiu.edu/sadjadi/
• sadjadi_at_cs.fiu.edu
• Thank you!
• and
• Questions?