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Parallel and Distributed Computing Overview and Syllabus PowerPoint Presentation
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Parallel and Distributed Computing Overview and Syllabus

Parallel and Distributed Computing Overview and Syllabus

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Parallel and Distributed Computing Overview and Syllabus

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  1. Parallel and Distributed Computing Overview and Syllabus Professor Johnnie Baker Guest Lecturer: Robert Walker

  2. 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

  3. 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

  4. 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

  5. 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 • Often quickly outdated due to rapid technological changes • Also covers the currently popular cluster architectures, shared memory processors, and the MP language.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

  6. Course Features (cont.) • Covers major types of parallel computation by looking at three key features of each: • Typical architectural features • Typical programming languages used • Typical algorithm design techniques used.

  7. 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

  8. 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 • MultiC language overview • Fortran 90 and HPF Language overviews • Algorithm examples

  9. Specific Topics (cont.) • Interconnection Networks • Specific Computer Examples including 2D mesh, hypercube, etc. • Synchronous and asynchronous considerations • MIMD-SIMD Comparisons in Real-Time Applications

  10. 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 this work.

  11. 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

  12. Two Complementary Courses • Parallel & Distributed Computing (Fall) • Architectures • Languages • Parallel Programming • Algorithm Examples for some architectures • Parallel & Distributed Algorithms (Spring) • Important Parallel Models • Designing Efficient Algorithms for Various Models • Will be offered in Spring 2007 • PDC and PDA can be taken in either order • Preference is for PDC to be taken first

  13. 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%

  14. 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

  15. 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.