Nsf tcpp curriculum planning workshop
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NSF/TCPP Curriculum Planning workshop. Behrooz Shirazi Washington State University February 2010. Introductory Course on Parallel Computation (version 1). Senior/first year grad level course Course is taught in Spring 2010

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NSF/TCPP Curriculum Planning workshop

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Nsf tcpp curriculum planning workshop

NSF/TCPP Curriculum Planning workshop

Behrooz Shirazi

Washington State University

February 2010


Introductory course on parallel computation version 1

Introductory Course on Parallel Computation (version 1)

  • Senior/first year grad level course

  • Course is taught in Spring 2010

  • Course taught by adjunct prof. (John Feo) – senior technical staff at Pacific Northwest National Lab (PNNL)

  • PNNL is heavily involved in both compute-intensive and data-intensive HPC

  • Very practical and application oriented


Introductory course on parallel computation version 11

Introductory Course on Parallel Computation (version 1)

  • Programming model using task parallelism with message passing.

  • Move from focus on data distribution to parallelism.

  • Think parallel, and optimize for performance and scalability.

  • Course based on Cray XMT, a shared-memory, multithreaded computer system.

  • On the Cray XMT, performance is only a function of parallelism (supporting all parallel models including data, task, recursion, and dataflow).

  • Course require team work to prepare 3 papers that include algorithm development and implementation.


Introductory course on parallel computation version 12

Introductory Course on Parallel Computation (version 1)

  • Topics:

    • General concepts

    • Cray XMT architecture

    • Cray XMT programming model

    • Cray XMT programming tools

    • Reasoning about performance on the Cray XMT

    • Data parallelism

    • Task parallelism

    • Using and optimizing recursive algorithms

    • Dataflow

    • Graph algorithms

    • Other cool algorithms


Introductory course on parallel computation version 2

Introductory Course on Parallel Computation (version 2)

  • Course Taught: Spring, 2009 by a CS faculty (KC Wang)

  • Based on class notes

  • Recommended reading:

    • Highly Parallel Computing, G.S. Almasi & A. Gottlieb, Benjamin/Cummings, 1989/1994

    • Introduction to Parallel Computing, 2nd Edition, Grama/Gupta/Karypis/Kumar, Addison Wesley,2003

    • Computer Architecture and Parallel Processing, K. Hwang & F.A. Briggs, McGraw-Hill, 1990

    • The Art of Parallel Programming, B. Lester, 1stWorld Publishing, 2006

    • Journal Articles


Introductory course on parallel computation version 21

Introductory Course on Parallel Computation (version 2)

  • Class Notes/Topics:

    • Introduction to Parallel Computing

    • Multicore Processors

    • POSIX pthreads Programming

    • Pthreads

    • Cache memory and Cache Coherence in MP

    • Finite field GF(2) and Applications

    • Interconnect Networks for MP

    • Multicomputers

    • How to get MPI

    • MPI Programming

    • Parallel Pi using MPI

    • Parallel Pi using Monte-Carlo Method

    • Diffusion, MPI code, etc

    • Shortest Path Algorithm

    • Fast Fourier Transform (FFT)

    • Current Supercomputers


Introductory course on parallel computation version 22

Introductory Course on Parallel Computation (version 2)

  • Assignments:

    • Multi-threading

    • Mutex-semaphore-thread_join for MTX

    • Pthreads Programming

    • HELP : Gaussian Elimination by Threads

    • Parallel Quicksort


Introductory course on parallel computation version 3

Introductory Course on Parallel Computation (version 3)

  • Semester Taught: Spring, 2007 by CS faculty Murali Medidi

  • Books used:

    • An introduction to Parallel Algorithms (Joseph Jaja)

    • Parallel Computation Models and Methods (Selim G. Akl)

  • Topics

    • MPI tutorial

    • Parallel Algorithms

      • sorting algorithm

      • Minimum spanning tree

      • shortest path

      • matrix manipulation

      • sorting networks

    • Super computer architecture.

      • Mesh

      • Cube

      • PRAM model CRCW, CREW, ERCW, etc.

  • Projects/1 term paper/5 homeworks/ 2 closed-book exams


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