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Course Syllabus _ Overview - Computer Science

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									 Parallel and Distributed
Computing Overview and
         Syllabus


   Professor Johnnie Baker
 Guest Lecturer: Robert Walker
               Instructors
• Professor Johnnie W. Baker
  – Primary Lecturer
• Professor Robert Walker
  – Guest lectures on specific architectures
  – Guest lecture on his groups VLSI work on
    parallel architectures
• Possible guest lecturers from parallel
  processing group
  – Lecture in areas of expertise
  – Occasionally cover classes when I am away
            Prerequisites
• Designed to be accessible to all graduate
  students in computer science
• Students who are not CS graduate
  students may also be qualified to take
  course
   Textbook and References
• Textbook
  – Parallel Programming in C with MPI and
    OpenMP
  – Michael Quinn, author
  – Published by McGraw Hill in 2004
• References for Supplementary Reading
  – Classroom Slides will also include additional
    information from a wide range of sources
  – Any additional needed reference material will
    be handed out or posted on course website
   Some Features of Course
• Includes coverage of fundamental
  concepts of parallel computation, rather
  than focusing only on latest trends.
  – Often quickly outdated due to rapid
   technological changes
• Also covers the currently popular cluster
  architectures, shared memory processors,
  and the MP language.
  – This is the focus of the Quinn Textbook
     Course Features (cont.)
• Covers the common techniques for
  parallel computation by looking at three
  key features for each technique:
  – Typical architectural features
  – Typical programming languages used
  – Typical algorithm design techniques used.
     Some Specific Topics
• Fundamental concepts applicable to all
  parallel computation.
• Asynchronous (MIMD) distributed memory
  computation
  – Message passing communications
  – Programming using the MPI Language
  – Architectural features
  – Examples of typical algorithms
     Specific Topics (cont.)
• Asynchronous (MIMD) shared memory
  computation
  – Symmetric Multiprocessors or SMPs
  – OpenMP language overview
• Synchronous Computation
  – SIMD, vector, pipeline computing
  – Associative and Multi-Associative Computing
  – Programming using the ASC language
  – Programming on WorldScape system with Cn
  – Fortran 90 and HPF Language overviews
  – Algorithm examples
      Specific Topics (cont.)
• Interconnection Networks
  – Specific Computer Examples including 2D
    mesh, hypercube, etc.
  – Synchronous and asynchronous
    considerations
• Comparing MIMD & SIMD Computation
  using a Real-Time Application
  – ATC (Air Traffic Control)
    Some Benefits of Course
• While principal focus is on parallel computation,
  most information is applicable to distributed
  computing.
• There is a wide choice of thesis and dissertation
  topics in this area
• Several professors in department work in this
  area or make major use of parallel computation
  in their research
• Students working on a thesis or dissertation in
  another area may benefit from being able to use
  parallel computation in their work.
             Benefits (cont.)
• Most large computational problems require
  a parallel or distributed system to satisfy
  the speed and memory requirements
• Parallel computation currently has major
  advantages over both distributed
  computation and grid computation for
  computational intensive problems.
  – Programs are normally much simpler
  – Architectures are much cheaper
  – Grid computing is currently fairly futuristic
      Two Complementary Courses
• Parallel & Distributed Computing (Fall)
  –   Architectures
  –   Languages
  –   Parallel Programming
  –   Algorithm Examples for some architectures
• Parallel & Distributed Algorithms (Alternate
  Springs)
  – Important Parallel Models
  – Designing Efficient Algorithms for Various Models
  – Expect to be next offered in Spring 2009
• PDC and PDA can be taken in either order
  – Preference is for PDC to be taken first
   Real-Time Systems Course
• Will be offered this Spring as an online
  course
• Co-taught with Professor Drew at Ohio
  University
• Plan to have a project on implementing a
  basic ATC system on a WorldScape-
  ClearSpeed parallel computer.
• The PDC class should provide useful
  background information for this course.
      Assignments and Grading
• Homework assignments
  – Problems assigned for most chapters
  – Probably 5-7 different assignments
  – Some assignments will involve programming
• Course Grade
  – Based on homework, midterm, and final
  – Approximate weights
     • Homework        40%
     • Midterm Exam 30%
     • Final Exam       30%
     Documented Disabilities
• If you have documented disabilities,
  please contact me and make me aware of
  your needs.
• For information on disability
  accommodations, support, and verification
  procedure, please see www.kent.edu/sds
           Course Website
• Will be established quickly
• Class slides, assignments, and some
  references will be posted on this website.
• Also, an online reference textbook and a
  pointer to a second online textbook will be
  available at this site.
• First Assignment – Read Chapter 1 in
  textbook.

								
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