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Research Plan Presentation

Cornelius Toole, Jr. Louis Stokes Mississippi Alliance for Minority Participation Bridge to the Doctoral Program Department of Computer Science Jackson State University September 16, 2004 Program Director: Dr. James Perkins Research Advisor: Dr. Loretta A. Moore .

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Research Plan Presentation

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  1. Cornelius Toole, Jr. Louis Stokes Mississippi Alliance for Minority Participation Bridge to the Doctoral Program Department of Computer Science Jackson State University September 16, 2004 Program Director: Dr. James Perkins Research Advisor: Dr. Loretta A. Moore Research Plan Presentation

  2. Outline Advisor Areas of Interest Career Objectives Academic Preparation Research Experience Topic Areas Overview Research Plan Methodology Activities / Coursework Needed Preparation Prospective Doctoral Programs

  3. Advisor - Dr. Loretta Moore Educational Background PhD., Computer Science, Illinois Institute of Technology, 1991 M.S., Computer Science, Illinois Institute of Technology, 1986 B.S., Computer Science, Jackson State University, 1985 Current Appointment Associate Professor and Chair of Computer Science Department ( 1998 – present )

  4. Academic Preparation Began Computer Science Program at JSU Fall 1999 Began Art Program at JSU mid-semester Fall 1999 Courses Overview: Java, C, C++ programming Data Structures, Discrete Structures, Programming Languages, Computer Architecture, Algorithms, Operating Systems, Data Mining, Computer Ethics, Senior Project Biology, Chemistry, Physics I & II Trigonometry, Calculus I II & III, Probability and Statistics I & II Graphic Design, Drawing, Computer Art BS Computer Science May 2003

  5. Areas of Interest Computer Graphics and Visualization Interface Design High Performance Computing

  6. Career Objectives Complete Master’s Degree in Computer Science at Jackson State University Enter & complete PhD program in Computer Science Attain academic/research appointment Conduct research and development in the areas of information/scientific visualization and new media tools Form R&D lab Creation of coalitions between academia and industry in visual computing

  7. Research Experience Student Research Assistant in JSU Computer Science Department, spring 2001 – fall 2002 Topic: Machine Vision, Image Processing, & Smart Camera Advisor Dr. Loretta Moore Student Research Intern at the Computations/Engineering Directorates at LLNL, summer 2001 Topic: Smart Camera Project Manager Doug Coffland Advisor Virgil Kohlhepp Student Research at the Engineering Directorate at LLNL, summer 2002 Topic: Smart Camera Project Manager: Doug Coffland Advisor: Virgil Kohlhepp

  8. Research Experience cont'd Student Research Intern at Geo-Structures Laboratory at the U.S. Army Corps of Engineers ERDC, summer 2003 Topic: Protective Structures Division Chief: Frank Dallriva Advisor: Matt Hosseley Student Research Guest at Center for Science and Engineering Education / Computing Sciences Division at LBNL in the Visualization Group, summer 2004 Topic: Visualization of Discrete Ordinates Method Radiation Transport Data Mentor: John Shalf

  9. Graduate Research Experience: Radiation Transport Part of a scientific team interested in discovering the cause of supernovae Radiation transport involved in key processes taking place in supernovae Radiation transport describes processes that occur when the properties of protons are altered by scattering, absorption, and reemission of the matter through which the protons are passing

  10. Graduate Research Experience cont’d Equation extremely difficult to solve because of the integration on an angle Scientist uses Discrete Ordinates Methods to circumvent this DOM divides the domain into regions called ordinates through discretization Integro-differential form of Boltzmann Radiative Transfer Equation Discretization of integration over an angle by quadrature sums times appropriate weights at finite points in interval

  11. Radiation Density Visualization

  12. Summer Research Summary Provide scientist with tools to explore radiation transport data Interest in remote distributed visualization Chose this work in order to gain experience in scientific visualization and to better understand needs and challenges of visualization first

  13. Visualization is a method of computing. It transforms the symbolic into the geometric, enabling researchers to (more effectively) observe their simulations and computations. Visualization offers a method for seeing the unseen. It enriches the process of scientific discovery and fosters profound and unexpected insights... -B. McCormick, T. DeFanti, and M. Brown Several Representations of DNA strand Scientific Visualization: Definition

  14. Principles of Scientific Visualization The scientific investigation model as it relates to scientific visualization

  15. Distributed Systems: Computational Grids • Can support the execution of large-scale, resource-intensive, & distributed applications • Distributed systems • Linking resources in a geographically remote manner

  16. Distributed Systems: Computational Grids • Example of an e-ChemLab enabled by grid technology • Spring 2004 special topics course on grid technology • Instructed by Drs. Geoffrey Fox, Bryan Carpenter, and Marlon Pierce from Indiana University

  17. Distributed Visualization Architecture: DiVA

  18. Distributed Visualization: Motivation Resources and capabilities for visualization are dispersed. Large data store may be at one site Special display system at another High graphics performance processing capabilities may exist at a rendering farm in another site What if we could create a system to take advantage of all these capabilities in an application that works seamlessly as a single machine? Remote distributed visualization (RDV) can enable this

  19. Distributed Visualization Applications Particle Physics Astronomy Genomics Bioinformatics Computation Biology Any scientific domain that generates huge amounts of data and can take advantage of high performance computing

  20. Distributed Visualization Architecture: Remote Distributed Visualization Key Problem Areas in Remote Distributed Visualization New Network Transport and Communications Protocols Job Control Brokering of Grid Services for Visualization Common / Unified Data Formats New Visualization Algorithms

  21. RDV: Need for a Broker Possible to manually configure a RDV application on limited number of machines in a distributed environment Infeasible with many ( hundreds ) of machines and components not to mention that one would have to know all the info about each component This needs to be automated – could be done by an agent called a broker

  22. Visualization Services Broker • A Broker provides services for: • Service/Component Discovery & Location • Performance Prediction / Modelling • Optimal Configuration • Application Invocation • Permissions Granting / Acquisition • Recording Performance History / Configuration Refinements

  23. Research Plan Tentative Thesis Topic Area DiVA – Distributed Visualization Architecture Brokering for Visualization Grid Services Research Goal To develop and implement components that provide brokering services for distributed visualization applications This work's main focuses are studies in visualization, and distributed computing.

  24. Research Plan cont'd Currently in literature review DiVA research is being conducted at: Lawrence Berkeley National Laboratory Carnegie Mellon University Louisiana State University Becoming familiar with grid computing frameworks Studies of various visualization techniques

  25. Research Plan: Methodology Implement visualization components as grid services Implement performance models and profiles for each component Implement components for service location Implement components for optimal configuration selection Implement agent to invoke visualization pipeline application Implement methods to monitor and refine application performance

  26. Activities / Coursework

  27. Publication Plans / Professional Development ACM Mid Southeast Region Conference in Gatlinburg, TN, Nov 2004 – present paper on work at LBNL Overset Symposium in Huntington Beach, CA, Oct 5 -7, 2004 Winter 2004 Publications on visualization brokering grid services

  28. Preparation Needed Mathematics Reinforcement of calculus, linear algebra, differential equations, set theory and logic, and probability & statistics Numerical analysis Computer Graphics Computer Animation

  29. Preparation Needed Neural Networks Algorithm Design and Analysis( reinforcement ) Parallel Programming Distributed Computing Web\Grid Services

  30. Proposed Doctoral Programs University of California Davis Computer Science Program Kwa Liu Ma, PhD Scientific Visualization / Information Visualization University of Illinois Chicago Computer Program The Electronic Visualization Laboratory University of Florida Computer Science Program Paul Fishwick Aesthetic Computing

  31. Acknowledgements My parents My wife Jackson State University Computer Science Department Faculty and Staff Dr. Loretta Moore Dr. James Perkins The National Science Foundation and the Louis Stokes Alliance for Minority Participation The Office of Science of the Department of Energy and Lawrence Berkeley National Laboratory

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