Parallel Programming (CS 4230)

Fall 2012

Schedule: Tues./Thur., 9:10-10:30 AM
Location: WEB L112
Instructor: Mary Hall
Office Hours: MEB 3466; Mondays, 11:00-11:30 AM; Thursdays, 10:45-11:15 AM or by appointment
Mailing list: cs4230@list.eng.utah.edu
TA: Axel Rivera

Jump to: [Background] [Grading] [Textbook] [Schedule] [Assignments] [Policies]

 Background and Description

This course is a comprehensive exploration of parallel programming paradigms, examining core concepts, focusing on a subset of widely used contemporary parallel programmingmodels, and providing context with a small set of parallel algorithms. In the last few years, this area has been the subject of significant interest due to a number of factors. Most significantly, the advent of multi-core microprocessors has made parallel computing available to the masses. At the high end, major vendors of large-scale parallel systems, including IBM, and Cray, have recently introduced new parallel programming languages designed for applications that exploit tens of thousands of processors. Embedded devices can also be thought of as small multiprocessors. The convergence of these distinct markets offers an opportunity to finally provide application programmers with a productive way to express parallel computation.

The course will be structured as lectures, homeworks, programming assignments and a final project. Students will perform four programming projects to express algorithms using selected parallel programming models and measure their performance. The final project will consist of teams of 2-3 students who will implement codes by combining multiple programming models.

Prerequisites: CS 4400, or concurrent

 Grading

35%Programming projects(P1, P2, P3, P4)
20%Written homeworks
5%Participation
25%Quiz and Final
15%Final project

Note:Late homeworks are not allowed. Late projects will incur a 20% penalty per day.

 Textbook

An Introduction to Parallel Programming by Peter Pacheco (ISBN: 978-0-12-374260-5).

 Schedule (tentative)

The following schedule is subject to change with a week's notice, particularly as opportunities for guest lectures and conflicts arise. The readings listed should be completed ahead of class so that you can follow the lecture and respond to questions. Homeworks and programming assignments are due before class so that we can discuss them.

Date Topics Read Assign Notes
21 Aug Introduction (ppt) (pdf)
Importance of parallel programming
Chapter 1 - -
23 Aug Introduction to parallel algorithms and correctness (ppt) (pdf)
Concerns for parallelism correctness and performance
Chapter 1 HW01 Pthread sum code versions
28 Aug Parallel Computing Platforms, Memory Systems and Models of Execution (ppt) (pdf)
A diversity of parallel architectures, taxonomy, and examples
Chapter 2, 2.1-2.3, pgs. 15-46 - -
Parallel Programming Model Concepts
30 Aug Memory Systems and Introduction to Shared Memory Programming (ppt) (pdf)
Deeper understanding of memory systems and getting ready for programming
Ch. 2.4-2.4.3 (pgs. 47-52), 4.1-4.2 (pgs. 151-159), 5.1 (pgs. 209-215) HW02 -
04 Sep Data Parallelism in OpenMP(ppt) (pdf)
Introduction to OpenMP and Parallel Loops
Chapter 5.2-5.7, 5.10 (pgs. 216-241, 256-258) - Sun Ultrasparc T2 http://www.youtube.com/watch?v=2pFOivcJ74g&feature=relmfu
06 Sep Data Dependences(ppt) (pdf)
Code restructuring techniques: permutation and tiling
- - Dep Notes OpenMP distributions
11 Sep Data parallel algorithms - - Watch videos: Implementing Domain Decompositions in OpenMP Dense Linear Algebra I
13 Sep Data Locality (ppt) (pdf)
Code restructuring techniques: tiling, unroll-and-jam and scalar replacement
- - Locality Notes
18 Sep Singular Value Decomposition (ppt)
(pdf)
Algorithm Description for SVD
- - -
20 Sep More Locality and Data Parallelism (ppt) (pdf)
Tiling example and Red-Blue example
- P02 Locality versions
25 Sep Data Parallelism (ppt) (pdf)
Finish Red-Blue example, Stencils
- - Stencil notes
27 Sep Lab Day
Go over programming assignment
- - -
02 Oct Breaking Dependences, and Introduction to Task Parallelism (ppt) (pdf)
Parallel sections, Producer-consumer parallelism
- - -
04 Oct (pdf)
OpenMP sections and tasks
Chapter 5.8 (pgs. 241-450) - More Task Parallelism (ppt)
16 Oct Midterm Review
-
- - Task-parallel versions
18 Oct -
Midterm
- - -
Message Passing
23 Oct Introduction to Message Passing (ppt)
(pdf)
What is MPI? Complexities of a distributed address space
Chapter 3.1-3.2, 3.4, pgs. 83-96, 101-106 - -
25 Oct MPI Communication (ppt) (pdf)
Non-blocking communication, One-sided communication
- P03 -
30 Oct Putting it Together: N-Body (ppt) (pdf)
N-body
Chapter 6.1 - -
Parallel Programming for GPUs
01 Nov Introduction to GPUs and CUDA (ppt)
(pdf)
Architecture and programming constructs
(Optional) CUDA Programming Guide - DDJ article
06 Nov CUDA, cont. (ppt) (pdf)
SIMT execution model, divergent branches, memory hierarchy
- P04 -
08 Nov CUDA, cont. (ppt) (pdf)
More memory hierarchy and examples
- - -
13 Nov SIMD multimedia extensions (ppt) (pdf) (video)
Multimedia extension architectures, performance issues
- - -
Parallel Algorithms
15 Nov Sparse Algorithms (ppt) (pdf)
Sparse Graphs and Matrices
Chapter 3.3,3.5-3.7 (pgs. 106-136) - -
20 Nov Parallel Graph Algorithms (ppt) (pdf)
Tree Search, Traveling Salesperson Problem
Chapter 6.2 - -
27 Nov SSE SIMD review
-
- - Examples, compile with "icc -O3 -msse3 -vec-report=3 " t1.c t2.c t3.c t4.c t5.c
29 Nov Course Retrospective and Future Directions for Parallel Computing (ppt)
(pdf)
Where the field is going
Chapter 7 - -
Project Presentations
04 Dec Project Presentations, Dry Run
-
- - -
06 Dec Project Presentations Poster Session
-
- - -
11 Dec -
-
- - -
13 Dec Final exam
-
- - -

 Assignments

All written homeworks are due one week from when they are assigned. See the schedule above for due dates. Use handin , and submit PDF files. Programming assignments will sometimes be given more time if they require more depth. The final programming assignment will be a group project for teams of 1 to 3 students.

Written Homework

Programming Assignments Final Project The final project will be a group project with teams of 2 to 3 students (single-student projects may be approved by the instructor in some cases). You will combine two of the parallel programming models we learned in class and develop a non-trivial application.
  • Project description
  • Poster presentation example poster
  • Poster dry run in class, Tues., Dec. 4
  • Presentation in class, Thurs., Dec. 6
  • 2-4 page report summarizing poster and project completion and software, due 11:59PM, Thurs., Dec. 13

    Final Exam Take-home exam final , due 11:59PM, Thurs., Dec. 13

     Policies

    Laptops in class: Laptops should not be used in class, unless you have an ADA exemption. (see ADA policy below)

    Cheating: Any assignment or exam that is handed in must be your own work. It must be in your own words, and based on your own understanding of the solution. However, talking with one another to understand the material better is strongly encouraged. When taking an exam, you must work independently. Any collaboration during an exam will be considered cheating. Any student who is caught cheating will be given an E in the course and referred to the University Student Behavior Committee.

    ADA: The University of Utah conforms to all standards of the Americans with Disabilities Act (ADA). If you wish to qualify for exemptions under this act, notify the Center for Disabled Students Services, 160 Union.

    College guidelines: Document concerning adding, dropping, etc. here.