Innovative Approaches In Computer Architectures
Information Systems Engineering
Institute of Natural and Applied Sciences
Second Cycle (Master's Degree)
| Course Unit Title | Course Unit Code | Type of Course Unit | Level of Course Unit | Year of Study | Semester | ECTS Credits |
|---|---|---|---|---|---|---|
| Innovative Approaches In Computer Architectures | BTM555 | Elective | Master's degree | 1 | Fall | 10 |
Name of Lecturer(s)
Associate Prof. Dr. Süleyman EKEN
Research Assistant Seda BALTA
Learning Outcomes of the Course Unit
1) Understands computer architecture components.
2) Distinguish the architectures in Flynn taxonomy.
3) Learns graphics processors and accelerator structures.
4) High performance computing facts.
5) Learns supercomputer and quantum computing structures.
Program Competencies-Learning Outcomes Relation
| Program Competencies | ||||||||
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | ||
| Learning Outcomes | ||||||||
| 1 | Middle | Middle | Middle | High | Middle | High | Low | |
| 2 | Middle | Middle | Middle | High | Low | High | Middle | |
| 3 | Middle | High | Low | High | Middle | Low | Low | |
| 4 | Middle | High | Middle | Low | Middle | High | Middle | |
| 5 | Middle | High | Low | Middle | Low | High | Middle | |
Mode of Delivery
Face to Face
Prerequisites and Co-Requisites
None
Recommended Optional Programme Components
Not Required
Course Contents
This course includes learning the fundamental components of computer architecture, innovative work for computer architectures, groundbreaking developments, understanding the differences and interoperability in computer architectures for edge-to-cloud computing, examining high-performance computing components, understanding computing concepts for heterogeneous computing and artificial intelligence, and supercomputers. It contains basic information about
Weekly Schedule
1) Dersin tanıtımı, genel kavramlar, bilgisayar mimarisinin temeli.2) Bilgisayar mimari bileşenleri (işlemci, önbellek, yazmaç)
3) Bilgisayar mimari bileşenleri (bellek, disk, çevresel birimler)
4) Çok-çekirdekli işlemciler ve işlemci optimizasyonları
5) Bellek optimizasyonları ve vektör işleme mimarileri
6) Grafik işlemciler ve GPU hesaplama optimizasyonları
7) Grafik işlemciler ve GPU hesaplama optimizasyonları
8) Hızlandırıcı Mimarileri
9) Uç-Bulut Hesaplama
10) Heterojen ve Dağıtık Hesaplama Yaklaşımları
11) Yüksek Başarımlı Hesaplama ve Yapay Zekâ Uygulamaları
12) Süper-bilgisayarlar
13) Kuantum Hesaplamanın Temelleri
14) Nöromorfik Hesaplamanın Temelleri
15) Proje sunumları
16) Final sınavı
Recommended or Required Reading
1- John L. Hennessy, David A. Patterson, Computer Architecture: A Quantitative Approach 5th Edition
2- Onur Mutlu, Computer Architecture Lecture Notes, Fall 2022, ETH Zurich, https://safari.ethz.ch/architecture/fall2022/doku.php?id=start.
Planned Learning Activities and Teaching Methods
1) Lecture
2) Question-Answer
3) Discussion
4) Drill and Practice
5) Group Study
6) Lab / Workshop
7) Self Study
8) Problem Solving
9) Project Based Learning
Assessment Methods and Criteria
Contribution of Semester Studies to Course Grade |
60% |
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Contribution of Final Examination to Course Grade |
40% |
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Total | 100% | |||||||||||
Language of Instruction
Turkish
Work Placement(s)
Not Required