COURSE UNIT TITLE

: HIGH PERFORMANCE COMPUTING

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
CSE 5070 HIGH PERFORMANCE COMPUTING 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

This course provides students with an in-depth analysis of these current issues in HPC systems including: (1) Parallel Computing (2) New Processor Architectures, (3) Power-Aware Computing and Communication, (4) Advanced Topics on Petascale Computing and Optical Systems. In addition, course also covers parallel models of computation such as dataflow, and demand-driven computation.

Learning Outcomes of the Course Unit

1   Fundamentals of Parallel computing
2   To undestand new processor architecture
3   to be able to know and use power-aware computing and communication
4   To familiarize with advaced topics on petascale computing and optical systems

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to High Performance Computing
2 Review of Parallel Processing Concepts
3 Parallel Programming with CUDA
4 Parallel Programming with CUDA
5 Fundamental Design Issues in Parallel Computing
6 Fundamental Design Issues in Parallel Computing
7 Fundamental Design Issues in Parallel Computing
8 Fundamental Limitations Facing Parallel Computing
9 Fundamental Limitations Facing Parallel Computing
10 Power-Aware Computing and Communication
11 Power-Aware Computing and Communication
12 Advanced topics: Petascale Computing, Optics in Parallel Computing, Quantum Computers, Recent developments in nanotechnology and its impact on HPC
13 Advanced topics: Petascale Computing, Optics in Parallel Computing, Quantum Computers, Recent developments in nanotechnology and its impact on HPC
14 Advanced topics: Petascale Computing, Optics in Parallel Computing, Quantum Computers, Recent developments in nanotechnology and its impact on HPC

Recomended or Required Reading

Recommended textbooks
[1] "Highly Parallel Computing", by George S. Almasi and Alan Gottlieb
[2] "Parallel Computer Architecture: A hardware/Software Approach", by David Culler Jaswinder Pal Singh, Morgan Kaufmann, 1999.
[3] "Scalable Parallel Computing", by Kai Hwang, McGraw Hill 1998.
[4] "Principles and Practices on Interconnection Networks", by William James Dally and Brian Towles, Morgan Kauffman 2004.
[5] GPU Gems 3 --- by Hubert Nguyen (Chapter 29 to Chapter 41)
[6] Introduction to Parallel Computing, Ananth Grama, Anshul Gupta, George Karypis, and Vipin Kumar, 2nd edition, Addison-Welsey, © 2003.
[7] Petascale Computing: Algorithms and Applications, David A. Bader (Ed.), Chapman & Hall/CRC Computational Science Series, © 2007.

Planned Learning Activities and Teaching Methods

class preseantations, discussion, programming and reading assignment, project

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, 9:00-12:00

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 12 3 36
Tutorials 4 3 12
Preparations before/after weekly lectures 12 4 48
Preparing assignments 4 10 40
Design Project 1 40 40
Preparation for midterm exam 1 20 20
Midterm 1 3 3
TOTAL WORKLOAD (hours) 199

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

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

Copyright 2015 DEÜ. BİD

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