COMP SCI 3305 - Parallel and Distributed Computing

North Terrace Campus - Semester 1 - 2017

A selection of topics from the following: the challenges faced in constructing parallel and distributed applications, including testing, debugging and performance evaluation. Various implementation techniques, paradigms, architectures and programming languages including: Flynn's taxonomy, MPI, MapReduce, OpenMP, GPGPU, concurrency and multi-threading.

  • General Course Information
    Course Details
    Course Code COMP SCI 3305
    Course Parallel and Distributed Computing
    Coordinating Unit School of Computer Science
    Term Semester 1
    Level Undergraduate
    Location/s North Terrace Campus
    Units 3
    Contact up to 2.5 hours per week
    Available for Study Abroad and Exchange
    Prerequisites One of COMP SCI 1007, COMP SCI 1009, COMP SCI 1103, COMP SCI 1203, COMP SCI 2103, or COMP SCI 2202
    Assumed Knowledge COMP SCI 2000
    Course Description A selection of topics from the following: the challenges faced in constructing parallel and distributed applications, including testing, debugging and performance evaluation. Various implementation techniques, paradigms, architectures and programming languages including: Flynn's taxonomy, MPI, MapReduce, OpenMP, GPGPU, concurrency and multi-threading.
    Course Staff

    Course Coordinator: Dr Claudia Szabo

    Course Timetable

    The full timetable of all activities for this course can be accessed from Course Planner.

  • Learning Outcomes
    Course Learning Outcomes
    On successful completion of this course students will be able to:

     
    1 To develop and apply knowledge of parallel and distributed computing techniques and methodologies.
    2 To gain experience in the design, development, and performance analysis of parallel and distributed applications.
    3 To gain experience in the application of fundamental Computer Science methods and algorithms in the development of parallel applications.
    4 To gain experience in the design, testing, and performance analysis of a software system, and to be able to communicate that design to others.

     
    University Graduate Attributes

    This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

    University Graduate Attribute Course Learning Outcome(s)
    Deep discipline knowledge
    • informed and infused by cutting edge research, scaffolded throughout their program of studies
    • acquired from personal interaction with research active educators, from year 1
    • accredited or validated against national or international standards (for relevant programs)
    1-4
    Critical thinking and problem solving
    • steeped in research methods and rigor
    • based on empirical evidence and the scientific approach to knowledge development
    • demonstrated through appropriate and relevant assessment
    2-4
    Teamwork and communication skills
    • developed from, with, and via the SGDE
    • honed through assessment and practice throughout the program of studies
    • encouraged and valued in all aspects of learning
    1,4
    Career and leadership readiness
    • technology savvy
    • professional and, where relevant, fully accredited
    • forward thinking and well informed
    • tested and validated by work based experiences
    1-4
    Intercultural and ethical competency
    • adept at operating in other cultures
    • comfortable with different nationalities and social contexts
    • Able to determine and contribute to desirable social outcomes
    • demonstrated by study abroad or with an understanding of indigenous knowledges
    1-4
    Self-awareness and emotional intelligence
    • a capacity for self-reflection and a willingness to engage in self-appraisal
    • open to objective and constructive feedback from supervisors and peers
    • able to negotiate difficult social situations, diffuse conflict and engage positively in purposeful debate
    2,4
  • Learning Resources
    Required Resources
    You should be able to perform all the exercise work required for the course in the University computer Labs. The programming language used are Java, C with MPI and OpenMP, and OpenCL.

    However, if you want to be able to work at home, you must install these on your system.
    Recommended Resources
    There are no textbooks for this course. However, there are a number of reference books for this course:
    • Parallel Programming for Multicore and Cluster Systems - T. Rauber, G. Runger, Springer 2009 - avalable online through the University library
    • Principles of Parallel Programming - C. Lin, L. Snyder, Addison-Wesley, 2009 - available in the University library
    • The Art of Computer Systems Performance Analysis - R. Jain, 1997
    Online Learning
    More information about the course can be found online on the Moodle forum of the school.
  • Learning & Teaching Activities
    Learning & Teaching Modes
    The course will be taught with lecture and tutorials. You are expected to attend the lectures and take part in the activities, and attempt tutorial questions before the scheduled tutorial session.  All lectures will be attempted to be recorded, however attendance at the lectures is recommended, due to the large number of activities present in the lectures. These activities will be critical for your learning, so attendance is a must!
    Workload

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    You are expected to attend all scheduled lecture classes (2hrs per week), and, if scheduled, the tutorial sessions. In addition to the schedule contact hours, you are expected to spend an additional 2-4 hours per week after each lecture to consolidate your understanding of it. You will need to allocate up to 7 hours per week on average to work on the assignments and tutorials.
    Learning Activities Summary
    The topics taught in this course can be broadly classified as shown below. The list of topics and their schedule is available on the course forum.

    Parallel and distributed systems - Overview and challenges
    Multi-threading synchronization issues and solutions 
    Parallel systems - Flynn. Introduction to parallel programming models.
    Parallel algorithm design
    Shared memory and Message Passing 
    GPU Architecture and CUDA Programming 
    Performance Analysis 
    Program Optimisation
  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    The assessment will comprise of two parts: practical programming assignments worth 70% and a final exam worth 30%.

    Component Weighting CBOK Areas
    Assignments 70% 1,2,4,7,8,9,11
    Final Written Exam 30% 1,2,8


    CBOK Legend
    1. Abstraction
    2. Design
    3. Ethics
    4. Interpersonal Communication
    5. Societal Issues
    6. History & Status of the Discipline
    7. Hardware & Software
    8. Data & Information
    9. Programming
    10. Human Computer Interfaces
    11. Systems Development

    Details of the Australian Computer Society's Core Bode of Knowledge (CBOK) can be found in this document.
    Assessment Detail
    More information on the assessment is provided online on the course forum. The course has two forms of assessment: summative assessment, provided by the tutorial sessions and intermediate assignment submissions, and formative assessment provided by the assignments.
    Submission
    All practical assignments must be submitted using the School of Computer Science online Submission System.
    Details are included in each assignment description on the course forum.  The University policy on plagiarism applies on all submissions.
    Course Grading

    Grades for your performance in this course will be awarded in accordance with the following scheme:

    M10 (Coursework Mark Scheme)
    Grade Mark Description
    FNS   Fail No Submission
    F 1-49 Fail
    P 50-64 Pass
    C 65-74 Credit
    D 75-84 Distinction
    HD 85-100 High Distinction
    CN   Continuing
    NFE   No Formal Examination
    RP   Result Pending

    Further details of the grades/results can be obtained from Examinations.

    Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

    Final results for this course will be made available through Access Adelaide.

  • Student Feedback

    The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.

    SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.

  • Student Support
  • Policies & Guidelines
  • Fraud Awareness

    Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student’s disciplinary procedures.

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