Instructor:
Andrew Rau-Chaplin (arc@cs.dal.ca)
Hours:
Class: Fri. 9:00am -12:00pm, rm 2107 Mona Campbell
Office: Weds 12:00pm or by appt. rm 4242 Mona Campbell.
Course
Materials:
Lectures:
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News
- Oct 30: To compile OpenMP code using the gcc compiler on CGM6 or CGM7 use the -fopenmp switch.
Example: gcc -fopenmp omp_hello.c
- Oct 26:Assignment 2 has been extended and is now due Friday November 7th before class!
- Oct 16:For the multicore version of partition problem in Assignment 2 you might want to read this slide deck that outlines possible algorithms.
- Sep 26: Assignment 2 is now available. Due: Friday October 31st before class!
- Sep 4: Assignment 1 Questions and Readings are available. Assignment 1: Readings R1, R2, R3. Extened Due date: October 3rd before 3pm handed in to front desk in the Goldberg CS building!
- 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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