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DD2358 Introduction to High Performance Computing 7.5 credits

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A second course covering algorithms and techniques for high performance computing.

Information per course offering

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Termin

Course syllabus as PDF

Please note: all information from the Course syllabus is available on this page in an accessible format.

Course syllabus DD2358 (Spring 2025–)
Headings with content from the Course syllabus DD2358 (Spring 2025–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

This course introduces methods and tools for developing and optimizing the execution of program code on high-performance computing systems. It focuses on computing system architectures for high computational performance, tools for performance monitoring and analysis, software engineering for scientific code development and parallel computing. The course contains four modules:

  • the fundamentals of computing systems for high-performance computing and measuring code performance
  • data structures and methods for high-performance computing
  • performance optimization
  • the basics of parallel computing.

Intended learning outcomes

After passing the course, the student shall be able to

  • list characteristics of high performance computer architectures
  • use software tools to measure and analyze the performance of given program code
  • identify performance bottlenecks and performance optimization of given program code
  • use tools for version control, testing and documentation for high-performance computer software
  • use parallel computing to optimize program code
  • develop and optimize a scientific application from scratch according to the best high-performance computing methods.

Literature and preparations

Specific prerequisites

Knowledge and skills in programming, 6 credits, equivalent to completed course DD1337/DD1310-DD1319/DD1321/DD1331/DD100N/ID1018.

Knowledge in algorithms and data structures, at least 6 higher education credits, equivalent to completed course DD1338/DD1320/DD1325/DD1328/DD1338/DD2325/ID1020/ID1021.

Knowledge in algebra and geometry, 7.5 higher education credits, equivalent to completed course SF1624.

Equipment

No information inserted

Literature

No information inserted

Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

A, B, C, D, E, FX, F

Examination

  • LAB1 - Laboratory Assignments, 3.0 credits, grading scale: P, F
  • LAB2 - Project, 4.5 credits, grading scale: A, B, C, D, E, FX, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

Opportunity to complete the requirements via supplementary examination

No information inserted

Opportunity to raise an approved grade via renewed examination

No information inserted

Examiner

Profile picture Stefano Markidis

Ethical approach

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

Course room in Canvas

Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.

Offered by

EECS/Computer Science

Main field of study

Computer Science and Engineering

Education cycle

Second cycle

Add-on studies

No information inserted

Contact

Stefano Markidis, markidis@kth.se

Supplementary information

In this course, the EECS code of honor applies, see:
http://www.kth.se/en/eecs/utbildning/hederskodex