Course syllabus
Course-PM
DAT400 / DIT431 DAT400 / DIT431 High-performance parallel programming lp1 HT26 (7.5 hp)
This course is offered by the department of Computer Science And Engineering
Course meetings
All lectures, problem sessions, workshops and labs will be held on campus. Check timeedit for the rooms.
Contact details
- Miquel Pericàs <miquelp@chalmers.se> (Examiner + Lecturer)
- Hari Abram <hariv@chalmers.se> (Teaching Assistant)
- Sonia Rani Gupta <soniar@chalmers.se> (Teaching Assistant)
- Hongguang Chen (Teaching Assistant)
- Joel Andersson (Teaching Assistant)
- Jing Chen (Teaching Assistant)
Course purpose
This course looks at parallel programming models, efficient programming methodologies and performance tools with the objective of developing highly efficient parallel programs.
Short description of the course purpose and content: can be copied from syllabus in Studieportalen. Additional information can be added.
Labs
The link to the signup spreadsheet can be found here.
Instructions for connecting remotely to lab machines:
Workshops
Workshops contain hands-on coding exercises during each session. The recommended methods to participate are as follows.
- Via the remote lab machines (see: https://chalmers.topdesk.net/tas/public/ssp/content/detail/knowledgeitem?unid=304967f9ad004d3293b986a976e39833 )
- Via your own Windows laptop and using WSL (Windows Subsystem for Linux). Installation instructions: https://learn.microsoft.com/en-us/windows/wsl/install
- Via your own Linux laptop.
- Macbook laptops should also work
Schedule
Check TimeEdit for room reservations. The schedule is shown below.
Note: This schedule is subject to change. Check periodically. The first lecture will be on Tuesday, Sep 1st, at 13:15h in room HC3
| Sep 1st, 13:15-16:00 | Miquel | |||
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| Sep 3rd, 13:15-16:00 | Miquel | |||
| Sep 4th & Sep 8th, 8:00-11:45 | Hari, Sonia, Hongguang, Joel | |||
| Sep 8th, 13:15-16:00 | Miquel | |||
| Sep 10th, 13:15-16:00 | Miquel | |||
| Sep 11th & Sep 15th, 8:00-11:45 | Hari, Sonia, Hongguang, Joel | |||
| Sep 15th, 13:15-15:00 | Parallel Programming Models | Hari | ||
| Sep 17th, 13:15-15:00 | Performance Analysis and Roofline Model | Sonia | ||
| Sep 18th & Sep 22nd, 8:00-11:45 | Hari, Sonia, Hongguang, Joel | |||
| Sep 22nd, 13:15-16:00 | Miquel | |||
| Sep 24th, 13:15-16:00 | Miquel | |||
| Sep 25th & Sep 29th, 8:00-11:45 | Hari, Sonia, Hongguang, Joel | |||
| Sep 29th, 13:15-16:00 | Miquel | |||
| Oct 1st, 13:15-16:00 | Miquel | |||
| Oct 2nd & Oct 6th, 8:00-11:45 | Hari, Sonia, Hongguang, Joel | |||
| Oct 6th, 13:15-16:00 | Miquel | |||
| Oct 8th, 13:15-16:00 | Miquel | |||
| Oct 13th & Oct 16th, 8:00-11:45 | Hari, Sonia, Hongguang, Joel | |||
| 20 | Oct 13th, 13:15-15:00 | Workshop #3 | CUDA (session 3) | Miquel |
| 21 | Oct 15th | No lecture | ||
| Oct 20th & Oct 23rd, 8:00-11:45 | Hari, Sonia, Hongguang, Joel | |||
| Oct 20th, 13:15-15:00 | Description of examination + Solutions to 2025 Exam | Hari + Miquel | ||
| Oct 22rd, 13:15-15:00 | Solutions to 2024 exam + Q&A session | Sonia + Miquel | ||
| Oct 29th, 8:30-12:30 | DAT400 team |
Course literature
The theory part (part #1) of the course loosely follows the following book: "Parallel Programming for Multicore and Cluster Systems", Thomas Rauber and Gudula Rünger (3rd edition, 2023). This book can be accessed through the Chalmers Library: link to the coursebook (accessible via Chalmers library).
The practical part (part #2) which covers various programming models and libraries is based on several online resources that will be published at a later point
Course literature
List all mandatory literature, including descriptions of how to access the texts (e.g. Cremona, Chalmers Library, links).
Also list reference literature, further reading, and other non-mandatory texts.
Course design
The course consists of a set of lectures and laboratory sessions. The lectures start with an overview of parallel computer architectures and parallel programming models and paradigms. An important part of the discussion is mechanisms for synchronization and data exchange. Next, code transformations and performance analysis of parallel programs is covered. The course proceeds with a discussion of tools and techniques for developing parallel programs in shared address spaces. This section is based on two workshops that cover the OpenMP programming model. Next, the course discusses the development of parallel programs for distributed address space. Here, two workshops cover the Message Passing Interface (MPI). Finally, we discuss how to program GPU accelerators. This part consists of two workshops that describe the CUDA (Compute Unified Device Architecture) programming environment.
The lectures are complemented with a set of laboratory sessions in which participants explore the topics introduced in the lectures. During the lab sessions, participants parallelize sample programs over a variety of parallel architectures and use performance analysis tools to detect and remove bottlenecks in the parallel implementations of these programs. The lab sessions are done in teams of two. At the end of each session a joint report has to be submitted. There is no strict deadline for the report, but we strongly recommend to submit it before the beginning of the next lab session.
Throughout the course, several assignments are proposed that provide bonus points. These assignments consist in reading papers and submitting solutions for proposed exercises. They are not mandatory, but they provide bonus points that are added to the score of the written exam given that the exam has reached a minimum score (this will be discussed in the first lecture).
Changes made since the last occasion
No major changes are planned for this edition of the course.
Learning objectives and syllabus
Learning objectives:
Knowledge and Understanding
- List the different types of parallel computer architectures, programming models and paradigms, as well as different schemes for synchronization and communication.
- List the typical steps to parallelize a sequential algorithm
- List different methods for analysis methodologies of parallel program systems
- Apply performance analysis methodologies to determine the bottlenecks in the execution of a parallel program
- Predict the upper limit to the performance of a parallel program
- ability to cooperate in diverse group compositions with team members with different skills, cultural and educational backgrounds, gender and nationality
- the student should be able to make and defend ethical judgement in general, and in particular within the area of High-Performance Computing systems
- Given a particular software, specify what performance bottlenecks are limiting the efficiency of parallel code and select appropriate strategies to overcome these bottlenecks
- Design energy-aware parallelization strategies based on a specific algorithms structure and computing system organization
- Argue which performance analysis methods are important given a specific context
Link to the syllabus on Studieportalen.
https://www.gu.se/en/study-gothenburg/high-performance-parallel-programming-dit431
Examination form
The exam (4.5c)
The final exam is in written form and accounts for 4.5 credits. Bonus points collected via course assignments can contribute to increase the score of the final exam. Bonus points will only added if your exam score reaches 18pts (out of 60)! The pass score in the final exam is 24/60 pt.
The labs (3.0c)
Successful completion of all the labs accounts for 3.0 credits.
The final grade is the same grade as the exam. To be given a pass grade on the whole course, both components need to have a pass.
Course summary:
| Date | Details | Due |
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