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DAT280 / DIT261 Parallel functional programming lp4 vt22 (7.5 hp)

The course is offered by the department of Computer Science and Engineering

Contact details

examiner

teachers 

TAs

When using office hours, it is a good idea to send a mail, preferably the day before, with a good explanation of your problem and of what you have tried to do to solve it. It may turn out that an email discussion is sufficient to solve your problem. Please do not expect instant turnaround, however. Our TAs have a lot to do, and need to avoid fragmentation.

Student Representatives

Please volunteer to be a student representative! We will call for volunteers in the first two lectures. 

The following students have kindly agreed to be student representatives:

Erik von Bennekum                          bennekum at student.chalmers.se                   Computer Systems & Networks

Jacob Spilg                                        spilg at student.chalmers.se                              Software Engineering & Technology

Lawrence Chonavel                          chonavel at student.chalmers.se                     N2COS GU

Sebastian Helin                                 helinse at student.chalmers.se                        MPALG                    

Please feel free to mail Mary, the TAs, or one of the student representatives if you have questions or concerns about the course.

 

Guest Lecturers (to be confirmed)

  • Troels Henriksen, designer and implementor of Futhark, (Links to an external site.) DIKU Copenhagen
  • Gabriele Keller, expert on DSLs for parallel programming, Utrecht University
  • Peter Sestoft, Java expert, ITU Copenhagen
  • Umut Acar, parallel ML, CMU
  • Dimitrios Vytiniotis, DeepMind
  • Erik Stenman, Erlang expert and entrepreneur
  • Richard Carlsson, Erlang expert, Klarna

Course purpose

The aim of the course is to introduce the principles and practice of parallel programming in a functional programming language. By parallel programming, we mean programming using multiple hardware cores or processors in order to gain speed. The course covers approaches to parallel functional programming in both Haskell and Erlang. It covers current research on these topics, and also research on other approaches. The course relies heavily on scientific papers as its source materials and is intended also to give students some insights into research in computer science by considering the development of a sub-field over time. Guest lectures from both academia and industry help to place the presented research and programming methods in context.

 

Schedule

Our current plan is to hold lectures live on the Chalmers campus, and to stream them on zoom for those who cannot attend (for example because they have symptoms). We are still quite unkeen to get Covid, so we hope that we can all be quite careful.

Here is the schedule in  TimeEdit.

(There will be no teaching on holiday or self-study days, and the schedule will be adjusted accordingly.)

Course literature

This course does not have a set book. Instead, you will be expected to read a number of research papers. Links to those papers will be made available through the lectures page. However, note that Simon Marlow’s book on Parallel and Concurrent Programming in Haskell (Links to an external site.) covers a good chunk of the course (and lots of other interesting stuff). The book is currently free to read online at the O'Reilly site.

The lectures appear under Modules and we will also add them to the calendar.  Click on a lecture and you will get a description of what the lecture is about, related reading material and the slides. 

 

Course design

The course has four compulsory lab exercises, which should be done in pairs. Only in special circumstances will we permit students to work alone, as we must conserve scarce TA resources. We suggest using the Discussions area of the course Canvas to help in the search for a lab partner.

We will use fire for submission and grading of labs. The submission link will be pfp-lp4-22.fire.cse.chalmers.se. The lab exercises are central to your learning on this course. Those who take them seriously typically also pass the written exam easily. That is our intention.

You must pass all four lab exercises (as well as the final written exam) to complete the course.

The course has two main parts, each of which in turn has two parts, and hence the four lab exercises. 

  1. Parallel Programming in Haskell
  2. Robust Parallel Erlang Programming
  3. Data Parallel Programming
  4. Map Reduce and noSQL databases

The guest lectures on the course are not just entertaining additions but contain examinable material. For example, there is a lab exercise related to the lecture on Futhark. So come to the guest lectures! They also broaden the view of parallel functional programming presented by the course.

Changes made since the last occasion

The course will be very similar to last year's instance, but note that this year's exam will be a normal, written exam taken in an exam hall, without a computer.

Learning objectives and syllabus

Learning objectives:

Knowledge and understanding

1. Distinguish between concurrency and parallelism.

2. Give an overview of approaches to parallelism in functional programming languages in the scientific literature.

Skills and abilities

1. Write, modify and test parallel functional programs, to run on a variety of architectures such as shared memory multiprocessors, networks of commodity servers, and GPUs.

2. Interpret parallelism profiles and address bottlenecks.

 

Judgement and approach

1. Identify when using a functional language may be appropriate for solving a parallel programming problem.

2. Select an appropriate form of parallel functional programming for a given problem, and explain the choice.

Link to the syllabus on Studieportalen.

Study plan (Chalmers)

TODO The study plan at GU should be linked here.

Examination form

You must complete all four lab exercises to complete the course. Labs are done in pairs.

You must also pass the written exam at the end of the course. Your grade on the course is determined entirely by your result on the written exam. 

Schedule

TimeEdit

Course summary:

Date Details Due