COMPX553-19A (HAM)

Extremely Parallel Programming

15 Points

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Division of Health Engineering Computing & Science
School of Computing and Mathematical Sciences
Department of Computer Science

Staff

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Convenor(s)

Shaoqun Wu

Shaoqun Wu
4782
G.2.21
To be advised
shaoqun.wu@waikato.ac.nz

Lecturer(s)

Administrator(s)

Placement Coordinator(s)

Tutor(s)

Student Representative(s)

Lab Technician(s)

Librarian(s)

: debby.dada@waikato.ac.nz

You can contact staff by:

  • Calling +64 7 838 4466 select option 1, then enter the extension.
  • Extensions starting with 4, 5, 9 or 3 can also be direct dialled:
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Paper Description

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This paper covers advanced parallel programming for large-scale parallelism. A variety of programming techniques will be covered, with application to cluster computers, GPU computing and many-core computing.
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Paper Structure

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There are one two-hour lecture and a weekly two hours lab in Lab1 or Lab 6 (R-Block). All online resources, support and discussion forums are available via Moodle.
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Learning Outcomes

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Students who successfully complete the course should be able to:

  • explain the basic concepts, benefits, and challenges of parallel programming.
    Linked to the following assessments:
  • develop simple parallel programs using a variety of techniques, such as Hadoop MapReduce, Apache Spark, the OpenCL language for GPU programming, and Java thread pools and streams.
    Linked to the following assessments:
  • understand key Java performance issues and be able to suggest ways of measuring and improving performance.
    Linked to the following assessments:
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Assessment

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Assessment Components

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The internal assessment/exam ratio (as stated in the University Calendar) is 100:0. There is no final exam. The final exam makes up 0% of the overall mark.

The internal assessment/exam ratio (as stated in the University Calendar) is 100:0 or 0:0, whichever is more favourable for the student. The final exam makes up either 0% or 0% of the overall mark.

Component DescriptionDue Date TimePercentage of overall markSubmission MethodCompulsory
1. Photo-Editor Assignment
8 Mar 2019
11:30 PM
10
  • Online: Submit through Moodle
2. GPGPU Programming Lab Exercise
15 Mar 2019
11:30 PM
5
  • Online: Submit through Moodle
3. GPGPU Programming Quiz
22 Mar 2019
11:30 PM
5
  • Online: Submit through Moodle
4. GPGPU Programming Assignment
29 Mar 2019
11:30 PM
20
  • Online: Submit through Moodle
5. Java Streams Assignment
5 Apr 2019
11:30 PM
5
  • Online: Submit through Moodle
6. Java Executors Quiz
12 Apr 2019
11:30 PM
3
  • Online: Submit through Moodle
7. Java CompletableFuture Assignment
12 Apr 2019
11:30 PM
7
  • Online: Submit through Moodle
8. Hadoop MapReduce Assignment
10 May 2019
11:30 PM
15
  • Online: Submit through Moodle
9. Apache Spark Assignment 1
17 May 2019
11:30 PM
10
  • Online: Submit through Moodle
10. Apache Spark Assignment 2
24 May 2019
11:30 PM
10
  • Online: Submit through Moodle
11. Apache Spark Project
7 Jun 2019
11:30 PM
10
  • Online: Submit through Moodle
Assessment Total:     100    
Failing to complete a compulsory assessment component of a paper will result in an IC grade
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Required and Recommended Readings

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Required Readings

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The required and recommended reading for the paper will be specified on the Moodle website.There is no required textbook for this paper.

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Online Support

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All online resources, support and discussion forums are available via Moodle.
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Workload

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The expected workload is twelve hours per week, for 12.5 weeks = 150 hours.

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Linkages to Other Papers

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Prerequisite(s)

Prerequisite papers: COMPX202 or COMPX242 or COMP204 or COMP242, or equivalent Java and jUnit experience.

Corequisite(s)

Equivalent(s)

Restriction(s)

Restricted papers: COMP453, COMP553

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