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263-2800-00L 9 Credits BSC , DZ , SHE , MSC , WBZ D-INFK , D-MATH , D-ITET

Design of Parallel and High-Performance Computing

Lecturers & Examiners: Dr. Alexandru Calotoiu

Only one of the two courses can be counted for credits: 263-2800-00L Design of Parallel and High-Performance Computing 263-2800-10L Design of Parallel and High Performance Computing - Theory

VVZ CR 2.83

Last Updated: 2026-06-03 00:07:33

Abstract

Advanced topics in parallel and high-performance computing.

Objective

Understand concurrency paradigms and models from a higher perspective and acquire skills for designing, structuring and developing possibly large parallel high-performance software systems. Become able to distinguish parallelism in problem space and in machine space. Become familiar with important technical concepts and with concurrency folklore.

Content

We will cover all aspects of high-performance computing ranging from architecture through programming up to algorithms. We will start with a discussion of caches and cache coherence in practical computer systems. We will dive into parallel programming concepts such as memory models, locks, and lock-free. We will cover performance modeling and parallel design principles as well as basic parallel algorithms.

General Information

Language: English
Levels: BSC , DZ , SHE , MSC , WBZ
Frequency: Yearly recurring

Examination

Type: session examination
Mode: written 120 minutes
Aids: Keine

50% of your grade is determined by mandatory project work and 50% is determined by a written exam; the exam is given during the official examination period.

Registration & Places

Max Places: 125

Course Components

Type	Title	Time & Place	Hours
lecture	Design of Parallel and High-Performance Computing	No time listed	2 h weekly
exercise	Design of Parallel and High-Performance Computing	No time listed	2 h weekly
independent project	Design of Parallel and High-Performance Computing Project Work, no fixed presence required.	No time listed	4 h weekly

Offered In

Computational Science and Engineering Bachelor
- Electives (In the ‘electives’ subcategory, at least two course units must be successfully completed.)
- Core Courses
Computational Science and Engineering Master
- Electives (In the ‘electives’ subcategory, at least two course units must be successfully completed. All courses listed as core courses (not electives) for one of the following ETH MSc programmes, MSc Statistics, MSc Physics, MSc Computer Science, MSc (Applied) Mathematics, MSc Neural Systems and Computation, MSc Robotics, Systems, and Control, MSc Data Science, MSc Electrical Engineering and Information Technology, can be taken as an elective course in the MSc CSE without prior permission.)
Computer Science Master
- Majors
  - Major in Secure and Reliable Systems
    - Core Courses
  - Major in Data Management Systems
    - Elective Courses
- Minors
Computer Science Teaching Diploma (More informations at : )
- Spec. Courses in Resp. Subj. w/ Educ. Focus & Further Subj. Didactics
Computer Science TC (Detailed information on the programme at: )
- Specialized Courses in Respective Subject with Educational Focus
CAS in Computer Science
- Focus Courses and Electives
Data Science Master
- Master Studies (Programme Regulations 2017)
  - Core Courses
    - Core Electives
DAS in Data Science
- Specialisation Track
  - Big Data Systems
Cyber Security Master
- Minor
  - Data Management Systems
    - Elective Courses