ECTS - Parallel 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 Area Elective 3 0 0 3 5
Pre-requisite Course(s)
N/A
Course Language English
Course Type Computer Engineering Elective Courses
Course Level Ph.D.
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
Supportive Courses X
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 Comprehends the most advanced technology and literature in the field of software engineering research. X
2 Gains the ability to conduct world-class research in software engineering and publish scholarly articles in top conferences and journals in the area.
3 Conducts quantitative and qualitative studies in software engineering. X
4 Develops and applies software engineering approaches to acquire the necessary skills to bridge the gap between academia and industry in the field of software engineering and to solve real-world problems. X
5 Gains the ability to access the necessary information to follow current developments in science and technology, and to conduct scientific research or develop projects in the field of software engineering. X
6 Gains awareness and a sense of responsibility regarding professional, legal, ethical, and social issues in the field of software engineering.
7 Acquires project and risk management skills; gains awareness of the importance of entrepreneurship, innovation, and sustainable development; adapts international excellence standards for software engineering practices and methodologies.
8 Gains awareness of the universal, environmental, social, and legal consequences of software engineering practices when making decisions.
9 Develops, adopts, and supports the sustainable use of excellence standards for software engineering practices.

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