• Class Number 4194
  • Term Code 3430
  • Class Info
  • Unit Value 6 units
  • Mode of Delivery In Person
    • Prof Dirk Pattinson
    • Dr John Taylor
  • Class Dates
  • Class Start Date 19/02/2024
  • Class End Date 24/05/2024
  • Census Date 05/04/2024
  • Last Date to Enrol 26/02/2024
SELT Survey Results

A practically oriented introduction to programming paradigms for parallel computers. Considers definitions of program efficiency on parallel computers, addresses the modelling, analysis and measurement of program performance. Description, implementation and use of parallel programming languages, parallel features of operating systems, library routines and applications.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

  1. Be proficient at programming multiple parallel machines in more than one special programming language or programming system
  2. Be able to descriptively compare the performance of different programs and methods on one machine
  3. Demonstrate advanced knowledge of the elements of parallel programming language and system implementation
  4. Recall the history of parallel systems and describe the developments in the field

Introduction to Parallel Computing, 2nd Ed., A. Grama, A. Gupta, G. Karypis, V. Kumar, Addison-Wesley 2003, ISBN 0201648652. This book is available in electronic form from O'Reilly. You will need to enter your ANU email address at this site to get access (possibly you will need to access from within an ANU network as well).

Principles of Parallel Programming, Calvin Lin and Lawrence Snyder. Pearson, International Edition - ISBN 978-0-321-54942-6 or US Edition - ISBN 978-0-321-48790-2 (Amazon linkPearson link)

Introduction to High Performance Computing for Scientists and Engineers (Chapman & Hall/CRC Computational Science) Georg Hager and Gerhard Wellein. This text book provides a useful application programmer perspective.

Staff Feedback

Students will be given feedback in the following forms in this course:
  • Written comments
  • Verbal comments
  • Feedback to the whole class, to groups, to individuals, focus groups

Student Feedback

ANU is committed to the demonstration of educational excellence and regularly seeks feedback from students. Students are encouraged to offer feedback directly to their Course Convener or through their College and Course representatives (if applicable). The feedback given in these surveys is anonymous and provides the Colleges, University Education Committee and Academic Board with opportunities to recognise excellent teaching, and opportunities for improvement. The Surveys and Evaluation website provides more information on student surveys at ANU and reports on the feedback provided on ANU courses.

Other Information

The use of Generative AI Tools (e.g., ChatGPT) is permitted in this course, given that proper citation and prompts are provided, along with a description of how the tool contributed to the assignment. Guidelines regarding appropriate citation and use can be found on the ANU library website (https://libguides.anu.edu.au/generative-ai ). Marks will reflect the contribution of the student rather than the contribution of the tools. Further guidance on appropriate use should be directed to the convener for this course.

Class Schedule

Week/Session Summary of Activities Assessment
1 Introduction; Classical Parallel Hardware
2 Message Passing with MPI; Performance Measures and Models Lab 1
3 Embarrassingly Parallel Problems; Routing and Communication Lab 2
4 Synchronous Computations; Parallelization by Pipelining Lab 3
5 Parallelization by Data Partitioning and Divide-And-Conquer Assignment 1 Lab
6 Mid-semester Outlook and Review Mid-Semester Test
7 Shared Memory Programming; Pthreads Assignment 1 deadline
8 Thread Synchronization; OpenMP Lab 4
9 Simultaneous Multi-Threading; Single Instruction Multiple Data Lab 5
10 Intro to GPUs; GPU SM Architecture & Execution Model; Intro to GPU Memory Management Lab 6
11 GPU Memory Management: Global and Shared Memory; CPU Cache Coherence Assignment 2 Lab
12 Performance Analysis with the Roofline Model (CPU & GPU); Outlook and Review Assignment 2 deadline

Assessment Summary

Assessment task Value Due Date Learning Outcomes
Assignment 1 25 % 15/04/2024 1,2,3
Assignment 2 25 % 26/05/2024 1,2,3,4
Mid-Semester Test 10 % 26/05/2024 1,2,3
Final exam 40 % * 1,2,3,4

* If the Due Date and Return of Assessment date are blank, see the Assessment Tab for specific Assessment Task details


ANU has educational policies, procedures and guidelines, which are designed to ensure that staff and students are aware of the University’s academic standards, and implement them. Students are expected to have read the Academic Misconduct Rule before the commencement of their course. Other key policies and guidelines include:

Assessment Requirements

The ANU is using Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. For additional information regarding Turnitin please visit the ANU Online website Students may choose not to submit assessment items through Turnitin. In this instance you will be required to submit, alongside the assessment item itself, hard copies of all references included in the assessment item.

Moderation of Assessment

Marks that are allocated during Semester are to be considered provisional until formalised by the College examiners meeting at the end of each Semester. If appropriate, some moderation of marks might be applied prior to final results being released.

Assessment Task 1

Value: 25 %
Due Date: 15/04/2024
Learning Outcomes: 1,2,3

Assignment 1

Assignment 1 involves designing and coding a scientific computing algorithm using distributed memory programming. The assignment is worth 25% of the final mark.

Assessment Task 2

Value: 25 %
Due Date: 26/05/2024
Learning Outcomes: 1,2,3,4

Assignment 2

Assignment 2 involves designing and coding a scientific computing algorithm using CPU shared memory programming and GPU programming. The assignment is worth 25% of the final mark.

Assessment Task 3

Value: 10 %
Due Date: 26/05/2024
Learning Outcomes: 1,2,3

Mid-Semester Test

The mid-term test will run in Week 6 covering the material up to the end of Week 5. The test is worth 10% of the final mark and is redeemable.

Assessment Task 4

Value: 40 %
Learning Outcomes: 1,2,3,4

Final exam

The final exam will be given at the end of semester and will cover all the course material. The final exam is worth 40% of the final mark.

It will be held during the official exam period.

Academic Integrity

Academic integrity is a core part of our culture as a community of scholars. At its heart, academic integrity is about behaving ethically. This means that all members of the community commit to honest and responsible scholarly practice and to upholding these values with respect and fairness. The Australian National University commits to embedding the values of academic integrity in our teaching and learning. We ensure that all members of our community understand how to engage in academic work in ways that are consistent with, and actively support academic integrity. The ANU expects staff and students to uphold high standards of academic integrity and act ethically and honestly, to ensure the quality and value of the qualification that you will graduate with. The University has policies and procedures in place to promote academic integrity and manage academic misconduct. Visit the following Academic honesty & plagiarism website for more information about academic integrity and what the ANU considers academic misconduct. The ANU offers a number of services to assist students with their assignments, examinations, and other learning activities. The Academic Skills and Learning Centre offers a number of workshops and seminars that you may find useful for your studies.

Online Submission

The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.

Hardcopy Submission

For some forms of assessment (hand written assignments, art works, laboratory notes, etc.) hard copy submission is appropriate when approved by the Associate Dean (Education). Hard copy submissions must utilise the Assignment Cover Sheet. Please keep a copy of tasks completed for your records.

Late Submission

Late submission of assessment tasks without an extension are not accepted.

Referencing Requirements

Accepted academic practice for referencing sources that you use in presentations can be found via the links on the Wattle site, under the file named “ANU and College Policies, Program Information, Student Support Services and Assessment”. Alternatively, you can seek help through the Students Learning Development website.

Extensions and Penalties

Extensions and late submission of assessment pieces are covered by the Student Assessment (Coursework) Policy and Procedure The Course Convener may grant extensions for assessment pieces that are not examinations or take-home examinations. If you need an extension, you must request an extension in writing on or before the due date. If you have documented and appropriate medical evidence that demonstrates you were not able to request an extension on or before the due date, you may be able to request it after the due date.

Privacy Notice

The ANU has made a number of third party, online, databases available for students to use. Use of each online database is conditional on student end users first agreeing to the database licensor’s terms of service and/or privacy policy. Students should read these carefully. In some cases student end users will be required to register an account with the database licensor and submit personal information, including their: first name; last name; ANU email address; and other information. In cases where student end users are asked to submit ‘content’ to a database, such as an assignment or short answers, the database licensor may only use the student’s ‘content’ in accordance with the terms of service — including any (copyright) licence the student grants to the database licensor. Any personal information or content a student submits may be stored by the licensor, potentially offshore, and will be used to process the database service in accordance with the licensors terms of service and/or privacy policy. If any student chooses not to agree to the database licensor’s terms of service or privacy policy, the student will not be able to access and use the database. In these circumstances students should contact their lecturer to enquire about alternative arrangements that are available.

Distribution of grades policy

Academic Quality Assurance Committee monitors the performance of students, including attrition, further study and employment rates and grade distribution, and College reports on quality assurance processes for assessment activities, including alignment with national and international disciplinary and interdisciplinary standards, as well as qualification type learning outcomes. Since first semester 1994, ANU uses a grading scale for all courses. This grading scale is used by all academic areas of the University.

Support for students

The University offers students support through several different services. You may contact the services listed below directly or seek advice from your Course Convener, Student Administrators, or your College and Course representatives (if applicable).

Prof Dirk Pattinson

Research Interests

Prof Dirk Pattinson


Research Interests


Dr John Taylor

Research Interests

Dr John Taylor


Responsible Officer: Registrar, Student Administration / Page Contact: Website Administrator / Frequently Asked Questions