PARALLEL COMPUTING

BİS512

Course Code: BİS512
Semester: -
Theory+Practice: 2 + 2
ECTS: 10

Course Type

Elective Course

Course Level

Master's Degree Without Thesis

Year of Study

Semester

ECTS

Name of Lecturer(s)

Learning Outcomes

At the end of this course, the students;

Learn fundamental concepts of parallel programming.
Learn parallelism, their principles and structures.
Understand the basics of parallel machine structure.
Learn parallel algorithm design, analyze and implementation.
Understand the possible limitations of parallel processing.

Mode of Delivery

E-Learning

Prerequisites

Recommended Optional Programme Components

None

Course Description

Parallel 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

WEEK	TOPICS
1^st Week	Parallel programming techniques.
2^nd Week	Parallel programming techniques.
3^rd Week	Parallel programming techniques.
4^th Week	Parallel programming techniques.
5^th Week	Classification of parallel processing systems.
6^th Week	Classification of parallel processing systems.
7^th Week	Classification of parallel processing systems.
8^th Week	Parallel computer architectures.
9^th Week	Parallel computer architectures.
10^th Week	Parallel computer architectures.
11^th Week	Parallel computer architectures.
12^th Week	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.
13^th Week	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.
14^th Week	Final Exam

Recommended or Required Reading

1. 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 Methods

Lecture

Assessment Methods and Criteria

	Quantity	Percentage (%)
Assignment	1	20
Total(%)		20
Contribution of In-term Studies to Overall Grade(%)		20
Contribution of Final Examination to Overall Grade(%)		80
Total(%)		100

ECTS Allocated Based on Student Workload

Activities	Quantity	Duration (Hour)	Total Workload (Hour)
Midterm exam
Preparation for Quiz
Individual or group work	14	3	42
Preparation for Final exam	1	40	40
Course hours	14	3	42
Preparation for Midterm exam
Laboratory (including preparation)
Final exam	1	2	2
Homework
Presentation (including preperation)	1	80	80
Project	1	80	80
Total Work Load			286
Total Work Load / 30 (h)			9.53
ECTS Credit of the Course			10

Language of Instruction

Turkish

Work Placement(s)

Programme Qualifications / Learning Outcomes

	LO1	LO2	LO3	LO4	LO5
K1				X
K2		X	X
K3				X
K4				X
K5			X	X
K6		X
K7	X		X
K8		X
K9		X
K10				X
K11				X
K12				X