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Parallel Computer Architecture

Master's level | 7.5 credits | Course code: DIT361

The course is not given as a stand-alone course this academic year, but can be included in the program/course package. For information contact the department.

About the Course

From 1975 to 2005, the computer industry accomplished a phenomenal mission: in 30 years, we put a personal computer on every desk and in every pocket. In 2005, however, mainstream computing hit a wall, and the industry undertook a new mission: to put a personal parallel supercomputer on every desk, in every home, and in every pocket. In 2011, we completed the transition to parallel computing in all mainstream form factors, with the arrival of multicore tablets and smartphones.

Power and temperature have joined performance as first-class design goals. High-performance computing platforms now strive for the highest performance/watt. This course looks at the design of current multicore systems with an eye towards how those designs are likely to evolve over the next decade. The content is divided into several parts: 

  • a review of fundamental concepts in computer architecture 
  • basic multiprocessor designs for the message passing and shared memory programming models 
  • interconnection networks, an essential component in chip multiprocessors and scalable parallel computer systems 
  • how to correctly support parallel algorithms in shared memory hardware 
  • last years' recent transition towards chip multiprocessors (also known as "multicores")

A common thread running through all content parts is a discussion of cost tradeoffs with respect to performance, power, energy, verifiability, programmability, and maintainability. A second unifying theme is the memory bottleneck, and the importance of efficient resource management.

The lectures are complemented with several exercise sessions. Via three lab assignments, participants learn how to develop software using models such as C++ threads and OpenMP, they develop and analyze synchronization algorithms, and they learn how to use performance analysis tools. The course also contains a written assignment in which the participants take the role of the computer architect who will survey and discuss solutions to a particular problem in the field of parallel computing.

More Information

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Course Syllabus


Tuition Fee

Please contact the department.
EU/EEA citizens, Swedish residence permit holders and exchange students do not pay fees. More information on:

Study Guidance



Department of Computer Science and Engineering
41296 Göteborg

Visiting address: Rännvägen 6 B

Page Manager: Pontus Sundén
Last update: 2/18/2020 2:41 PM

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Page Manager: Pontus Sundén|Last update: 10/16/2018

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Utskriftsdatum: 2020-07-07