CSci6702 Parallel Computing

Fall 2013

Instructor:
Andrew Rau-Chaplin (arc@cs.dal.ca)

Hours:
Class: Wed/Fri. 10:30am -12:00pm, rm 2107 Mona Campbell  
Tutoral: Wed/Fri. 12:05pm -1:30pm, rm LSC-COMMON AREA C212. Note the tutorial sessions will only be used on an infrequent basis! 
Office: Weds 12:00pm or by appt. rm 4242 Mona Campbell.

Course Materials:

Lectures:

News
  • Oct 25: Upcomming student seminars (Topics)
    • Wed Nov 6 - Owen Davison
    • Fri Nov 8 - Hassan Nikoo
    • Wed Nov 13 - Nathan Lapierre
    • Fri Nov 15 - Leah Brown Fri
    • TBD - Mugundhan Balaji Pattabi
  • Oct 17: Please see updated Seminar and Project Topic page
  • Oct 4: Owen and Daniel have been very kind and got the code for Question 2 of Assignment 2 running sequentially. It is available to on Git hub here: https://github.com/OwenDavison/6702a2q2
  • Oct 4: Time to start thinging about seminars! You are to 1) teach yourself a new area of parallel computing, 2) teach the class what you have learnt, 3) provide materials so someone else could teach themselves based on your notes. In class deliver 1.5 hour hands-on tutorial on your topic in groups of 1.
    Possible topics:
    1. GPU programming in CUDA,
    2. Web-scale applications on AWS,
    3. Vectorization using Vtune,
    4. Parallel programming in Java,
    5. Multicore programming in CILK,
    6. MapReduce and Hadoop.

    Deliverables: Tutorial materials organized on a web page, plus in class seminar. Each of you should meet with me twice before delivering your topic.
  • Sep 30: Assignment 2 is now available.
  • Sep 12: Assignment 1 Questions and Readings are available. Assignment 1: Readings R1, R2, R3.
  • Aug 28: I have posted a list of Journals and Conferences in Parallel Computing.
  • Aug 28: If you need to brush up your background in analysis of algorithms please see the first 25 slides here. If you like video introductions you might like to watch Lecture 1 and 2 from the Intro Analysis of Algorithms course at MIT.  Erik Demaine the guy teaching lecture 2 did his undergraduate degree at Dalhousie.
  • Aug 28: Sign up for a ACEnet account here. You will need my Project Account Number which I will give you during the first class.
  • Aug 28: To learn MPI I suggest that you complete the first six sections of the Online Introduction to MPI Course at NCSA. You will need to create a new Account to get started. In order to experiment with MPI while you are learning you will need to setup an MPI environment here at Dalhousie. Our MPI Tutorial will help to get you started.
  • Official Outline: This course explores various aspects of parallel computing including parallel architectures, algorithms, systems, programming languages and implementation issues. The focus is on solving real problems on existing parallel machines. Student will be expected to read recent research publications, and participate in significant parallel implementation projects.

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