ECTSParallel and Cluster Computing

Parallel and Cluster Computing (CMPE575) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Parallel and Cluster Computing CMPE575 Elective Courses 3 0 0 3 5
Pre-requisite Course(s)
N/A
Course Language English
Course Type Elective Courses
Course Level Natural & Applied Sciences Master's Degree
Mode of Delivery Face To Face
Learning and Teaching Strategies Lecture.
Course Coordinator
Course Lecturer(s)
Course Assistants
Course Objectives TheThe objective of this course is to teach parallel/cluster computer architectures and their organization. This course also aims at teaching different programming paradigms for parallelizing engineering problems.
Course Learning Outcomes The students who succeeded in this course;
  • Recognize parallelism in computational problems
  • Explain different parallel systems and their classification
  • Design parallel algorithms for different applications
  • Implement parallel algorithms using different programming environments such as MPI and OpenMP.
Course Content Models of parallel computing ? dependence on architecture, trade-off between computation cost and communication cost, performance measures for parallel computation ? computational complexity, techniques for parallel computation ? divide and conquer, partitioning, and pipelining, parallel algorithms for sorting, searching and matrix computations, MP

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Introduction to parallel/cluster computing. Ch 1.1 of the main text
2 Parallel computing platforms 1 Ch 1.2
3 Parallel computing platforms 2 Ch 1.3-1.4-1.5
4 Parallel algorithm design principles 1 Ch 4, Ch 3 – other resources 1
5 Parallel algorithm design principles 2 Ch 4, Ch 3 – other resources 1
6 Parallel algorithm design principles 3 Ch 4, Ch 3 – other resources 1
7 Synchronous Computations Ch 6
8 Analytical models for parallel programming 1 Ch 5 – other resources 1
9 Analytical models for parallel programming 2 Ch 5 – other resources 1
10 Message Passing with MPI 1 Ch 2, Ch 6 – other resources 1
11 Message Passing with MPI 2 Ch 2, Ch 6 – other resources 1
12 Developing parallel programs with MPI Ch 10-11, Ch 2, Ch 8-9-10 – other resources 1
13 OpenMP programming 1 Ch 8 – other resources 5
14 OpenMP programming 2 Ch 8 – other resources 5
15 Review
16 Review

Sources

Course Book 1. “Parallel Programming: Techniques & Applications Using Networked Workstations & Parallel Computers”, 2nd. Edition, B. Wilkinson Michael Allen, Pearson, 2005
Other Sources 2. “Introduction to Parallel Computing”, 2nd Edition, A. Grama, A. Gupta and G. Karypis, V. Kumar Addison-Wesley 2003.
3. http://www.hku.hk/cc/sp2/ftp/mpi/MPI_ug_in_FORTRAN.doc
4. "Using MPI - 2nd Edition: Portable Parallel Programming with the Message Passing Interface (Scientific and Engineering Computation)", William Gropp, 1999
5. "Parallel Programming With MPI", Peter Pacheco, Morgan Kaufmann, 1997
6. “Using OpenMP: Portable Shared Memory Parallel Programming (Scientific and Engineering Computation)”, Barbara Chapman, Gabriele Jost, Ruud van der Pas, The MIT Press, 2007.

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics - -
Homework Assignments - -
Presentation - -
Project 1 30
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 30
Final Exam/Final Jury 1 40
Toplam 3 100
Percentage of Semester Work 60
Percentage of Final Work 40
Total 100

Course Category

Core Courses
Major Area Courses X
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 An ability to apply knowledge of mathematics, science, and engineering. X
2 An ability to design and conduct experiments, as well as to analyse and interpret data. X
3 An ability to design a system, component, or process to meet desired needs. X
4 An ability to function on multi-disciplinary domains.
5 An ability to identify, formulate, and solve engineering problems. X
6 An understanding of professional and ethical responsibility.
7 An ability to communicate effectively. X
8 Recognition of the need for, and an ability to engage in life-long learning.
9 A knowledge of contemporary issues. X
10 An ability to use the techniques, skills, and modern engineering tools necessary for engineering practice. X
11 Skills in project management and recognition of international standards and methodologies X
12 An ability to produce engineering products or prototypes that solve real-life problems.
13 Skills that contribute to professional knowledge. X
14 An ability to make methodological scientific research.
15 An ability to produce, report and present an original or known scientific body of knowledge. X
16 An ability to defend an originally produced idea.

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Laboratory
Application
Special Course Internship
Field Work
Study Hours Out of Class 16 2 32
Presentation/Seminar Prepration
Project 1 15 15
Report
Homework Assignments
Quizzes/Studio Critics
Prepration of Midterm Exams/Midterm Jury 1 15 15
Prepration of Final Exams/Final Jury 1 20 20
Total Workload 130