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COURSE UNIT TITLECOURSE UNIT CODESEMESTERTHEORY + PRACTICE (Hour)ECTS
PARALLEL PROCESSING BİL478 - 3 + 0 5

TYPE OF COURSE UNITElective Course
LEVEL OF COURSE UNITBachelor's Degree
YEAR OF STUDY-
SEMESTER-
NUMBER OF ECTS CREDITS ALLOCATED5
NAME OF LECTURER(S)-
LEARNING OUTCOMES OF THE COURSE UNIT At the end of this course, the students;
1) Learn fundamental concepts of parallel programming.
2) Learn parallelism, their principles and structures.
3) Understand the basics of parallel machine structure.
4) Learn parallel algorithm design, analyze and implementation.
5) Understand the possible limitations of parallel processing.
MODE OF DELIVERYFace to face
PRE-REQUISITES OF THE COURSENo
RECOMMENDED OPTIONAL PROGRAMME COMPONENTNone
COURSE DEFINITIONParallel programming techniques. Classification of parallel processing systems. Parallel computer architectures. A comprehensive study of basic techniques: Parallel Computer Models; Message-Passing Computing; Pipelined Computations; Programming with Shared Memory; Algorithms and Applications connected with Parallel Processing.
COURSE CONTENTS
WEEKTOPICS
1st Week Parallel programming techniques.
2nd Week Classification of parallel processing systems.
3rd Week Parallel computer architectures.
4th Week A comprehensive study of basic techniques:
5th Week Parallel Computer Models;
6th Week Message-Passing Computing;
7th Week Pipelined Computations;
8th Week Mid-term
9th Week Programming with Shared Memory;
10th Week Algorithms and Applications connected with Parallel Processing.
11th Week Algorithms and Applications connected with Parallel Processing.
12th Week Algorithms and Applications connected with Parallel Processing.
13th Week Algorithms and Applications connected with Parallel Processing.
14th Week Algorithms and Applications connected with Parallel Processing.
RECOMENDED OR REQUIRED READING1. Introduction to Parallel Computing, V. Kumar, A. Grama, A. Gupta and G. Karypis, V. Kumar (second edition), 2003
2. Addison Wesley Parallel Programming with MPI, P. Pacheco, Morgan Kaufmann Publishers, Inc., 1997.
3. MPI Related Materials Scalable Parallel Computing, Kai Hwang and Zhiwei Xu, 2000
PLANNED LEARNING ACTIVITIES AND TEACHING METHODSLecture,Questions/Answers,Problem Solving,Practice,Project,Report Preparation,Experiment,Presentation,Other
ASSESSMENT METHODS AND CRITERIA
 QuantityPercentage(%)
Mid-term130
Quiz315
Project115
Total(%)60
Contribution of In-term Studies to Overall Grade(%)60
Contribution of Final Examination to Overall Grade(%)40
Total(%)100
ECTS WORKLOAD
Activities Number Hours Workload
Midterm exam11,51,5
Preparation for Quiz
Individual or group work
Preparation for Final exam12020
Course hours14342
Preparation for Midterm exam11515
Laboratory (including preparation)
Final exam11,51,5
Homework
Project17070
Quiz4,52
Total Workload152
Total Workload / 305,06
ECTS Credits of the Course5
LANGUAGE OF INSTRUCTIONTurkish
WORK PLACEMENT(S)No
  

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