COURSE UNIT TITLE

: PARALLEL INFORMATION PROCESSING

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
CSE 5022 PARALLEL INFORMATION PROCESSING ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

Offered to

Computer Engineering Non-Thesis
COMPUTER ENGINEERING
Computer Engineering
Computer Engineering
Computer Engineering (Non-Thesis-Evening)

Course Objective

The goal of this course is to introduce students to the foundations of parallel Information Processing, including the principles of parallel computer architectures. Students will learn thinking in parallel to write their own simple parallel codes for both shared- and distributed-memory systems.

Learning Outcomes of the Course Unit

1   To understand Parallel Computer Architectures
2   To learn to think in parallel when designing algorithm for parallel architecture
3   To be able to develop code for shared-memory architectures using OpenMP
4   To be able to develop code for distributed-memory architectures using MPI

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to Parallel Information Processing
2 Parallel Architectures
3 Parallel Architectures
4 Distributed-memory programming with MPI
5 Distributed-memory programming with MPI
6 Distributed-memory programming with MPI
7 Distributed-memory programming with MPI
8 Shared-memory programming with p-threads
9 Shared-memory programming with p-threads
10 Shared-memory programming with p-threads
11 Shared-Memory Programming with OpenMP
12 Shared-Memory Programming with OpenMP
13 Parallel Program development
14 Parallel Program development

Recomended or Required Reading

1) Ananth Grama, Anshul Gupta, George Karypis, Vipin Kumar, Introduction to Parallel Computing, Second Edition, Addison Wesley, 2003, ISBN: 0-201-64865-2
2) Pacheco, Peter S., An introduction to parallel programming, Morgan Kaufmann Publisher, 2011, ISBN 978-0-12-374260-5

Planned Learning Activities and Teaching Methods

Class lectures, tutorial, programming exercises, projects

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 ASG ASSIGNMENT
2 MTE MIDTERM EXAM
3 PRJ PROJECT
4 FCG FINAL COURSE GRADE ASG * 0.30 + MTE * 0.40 + PRJ * 0.30


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Dokuz Eylül University, Department of Computer Engineering
Tınaztepe Campus 35160 Buca, Izmir
Tel:+90-(232) 301 74 01

Office Hours

Monday 9:30 - 12:00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 13 3 39
Preparation for midterm exam 1 20 20
Design Project 1 40 40
Preparing assignments 4 15 60
Reading 10 3 30
Midterm 1 3 3
TOTAL WORKLOAD (hours) 192

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11
LO.15555555
LO.25555555
LO.35555555
LO.45555555