Parallel Sessions - Approaches to Modeling 4
           
Event Type Start Time End Time Rm # Chair  

 

Education 3:30PM 5:00PM 21, 22, 23, 24, 25, 28
 
Title:

Approaches to Modeling
  Speakers/Presenter:

 

Education 3:30PM 5:00PM 21, 22, 23, 24, 25, 28
 
Title:

Cluster Computing: Intermediate Message Passing Interface
  Speakers/Presenter:
Paul Gray, David Joiner

 

Education 3:30PM 5:00PM 21, 22, 23, 24, 25, 28
 
Title:

GIS2K (GIS to Knowledge)
  Speakers/Presenter:
Michael Welge, Loretta Auvil, Peter Bajscy

 

Education 3:30PM 5:00PM 21, 22, 23, 24, 25, 28
 
Title:

Introduction to Parallel and Distributed Computing
  Speakers/Presenter:
Alf Wachsmann
             

 

     
  Session: Parallel Sessions - Approaches to Modeling 4
  Title: Approaches to Modeling
  Chair:
  Time: Sunday, November 16, 3:30PM - 5:00PM
  Rm #: 21, 22, 23, 24, 25, 28
  Speaker(s)/Author(s):  
 
   
  Description:
  Civic Center Rooms [to be assigned]

* Agent Modeling – Michael Novak, Lisa Bievenue, Edna Gentry (repeat of 8:30 AM session)
* Systems Dynamics Modeling – Shawn Sendlinger, Susan Ragan (repeat of 8:30 AM session)
* Algebraic Modeling – Garrett Love, Dan Warner (repeat of 8:30 AM session)
* Geowall Demonstration
* GIS2K (GIS to Knowledge) – Michael Welge, Loretta Auvil, Peter Bajscy
* Cluster Computing: Intermediate Message Passing Interface – Paul Gray, David Joiner
* Introduction to Parallel and Distributed Computing - Alf Wachsmann
  Link: --
   

 

     
  Session: Parallel Sessions - Approaches to Modeling 4
  Title: Cluster Computing: Intermediate Message Passing Interface
  Chair:
  Time: Sunday, November 16, 3:30PM - 5:00PM
  Rm #: 21, 22, 23, 24, 25, 28
  Speaker(s)/Author(s):  
  Paul Gray, David Joiner
   
  Description:
  This session will apply basic MPI skills to the parallelization of a numerical model. Participants will be introduced to MPI features for collective communication and reduction, as well as debugging tools available for the most common MPI implementations.
  Link: --
   

 

     
  Session: Parallel Sessions - Approaches to Modeling 4
  Title: GIS2K (GIS to Knowledge)
  Chair:
  Time: Sunday, November 16, 3:30PM - 5:00PM
  Rm #: 21, 22, 23, 24, 25, 28
  Speaker(s)/Author(s):  
  Michael Welge, Loretta Auvil, Peter Bajscy
   
  Description:
  Geographic Information System (GIS) is a composite of hardware and software used for storage, retrieval, mapping, and analysis of geographic data. Spatial features are stored in a coordinate system (latitude/longitude, UTM, etc.), which references a particular place on the earth. Spatial features and their associated descriptive attributes are combined in the same coordinate system and layered together for mapping and analysis. Applications of GIS come from many scientific domains including land use studies, hydrology, geology, soil management, environmental or development planning.

This session will describe analyses of GIS data for territorial partitioning. We will present a suite of tools that use modules in D2K for processing raster and vector data, georeferencing heterogeneous data, extracting statistical features per boundary, aggregating boundaries based on selected features and performing geographical error analysis of territorial aggregations. We will demonstrate our analyses with the vector data defined by the U.S. Census Bureau, USGS terrain elevation maps, forest data, and crime data. This session will overview some of the GIS challenges and illustrate how GIS analysis can be accomplished for territorial partitioning purposes.
  Link: --
   

 

     
  Session: Parallel Sessions - Approaches to Modeling 4
  Title: Introduction to Parallel and Distributed Computing
  Chair:
  Time: Sunday, November 16, 3:30PM - 5:00PM
  Rm #: 21, 22, 23, 24, 25, 28
  Speaker(s)/Author(s):  
  Alf Wachsmann
   
  Description:
  “Introduction to Parallel and Distributed Computing" tries to connect general computing with the SuperComputing conference by explaining why parallel computing is a good idea.

We will explain how parallel computing can speed up computations. We will show how to parallelize the addition of numbers. After introducing the concept of computation and communication costs and explaining the
Big-O notation we will talk about "latency" and "bandwidth." These concepts are then used to explain why writing efficient parallel programs is so hard.

We will explain the difference between parallel and distributed computing by introducing the notion of tightly vs. loosely coupled systems, fine vs. coarse grain parallel programs, and synchronous vs. asynchronous computation.

We will explain which classes of algorithms (matrix and the like) are well suited for parallel and distributed computing.
  Link: --