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DD2443 Parallel and Distributed Computing 7,5 hp

Course memo Autumn 2021-51281

Version 1 – 05/29/2022, 10:27:51 AM

Course offering

pardis21 (Start date 30/08/2021, English)

Language Of Instruction

English

Offered By

EECS/Computer Science

Course memo Autumn 2021

Course presentation

Advanced course in computer science on the theory, algorithms, and techniques of parallel and distributed computing systems.

Headings denoted with an asterisk ( * ) is retrieved from the course syllabus version Autumn 2020

Content and learning outcomes

Course contents

The course is an advanced course in parallel and distributed computations, dealing with the following subjects:

  • models, fundamental concepts and analytical methods for parallel and distributed systems, fundamental limitations and impossibility results,
  • algorithms and protocol for commonly occurring computational problems within communication, synchronisation, fault tolerance, coordination and consensus, replication and sharing, security, and peer-to-peer systems,
  • basic knowledge of synchronization mechanisms within operating systems and programming languages (semaphores, locks, monitors) and some interest for theoretical subjects are good starting points.

Intended learning outcomes

Having passed the course, the student should be able to:

  • account for models, limitations and fundamental concepts within parallel computations with communication based both on message passing and shared memory
  • analyse concrete systems and algorithms
  • adapt and develop algorithms for execution on parallel and distributed machines and analyse the algorithms with respect to correctness, reliability, safety and performance.

Learning activities

Course Format

Lectures: There are 14 2-hour lectures, two per week. Reading material, in textbook, web, or papers, is assigned for each lecture.

Exercises: Each lecture has assigned exercises, some for training only, most are for hand-in. Training exercises are voluntary. Deadline for each weeks hand-in exercises is Friday 10.00 (right before the respective exercise session). We apply peer review, with review deadline following Wednesday 18.00. The weeks exercises are discussed in the Friday exercise session.

Labs: Labs are done asynchronously. That is, no fixed time is allotted for the labs, it is up to yourself to plan your time and make sure the labs are handed in at the appropriate time. Labs are done pairwise. We are using PDC facilities in order to get access to machines with more interesting architecture and larger number of cores than what the regular laptops offer. An extra PDC intro lecture is scheduled during the first week of the course. Lab presentations will be scheduled separately, on Zoom for Covid-19 reasons.

Seminars: Each student is strongly encouraged to present a research paper of own choosing at one of the four scheduled seminar sessions. Check here for details.

Discussions: Use of the Canvas discussion feature is encouraged. Try to make it a habit to submit at least one reasonably well thought out comment per lecture. This can be either by initiating a new discussion thread or by commenting on an existing one.

Examination: Is oral, check here for details.

Attendance

Attendance at lectures and exercise sessions is strongly recommended, particularly in these Covid-19 times. The material is not easy and a good result in the course is strongly correlated with activity (like: asking questions in real time, browsing through slides the day before the scheduled lecture) and attendance at lectures and exercise sessions. 

Seminar attendance is obligatory.

Course Requirements

The course returns TEN2, 4.5 hp and UPP1, 3 hp. TEN2 grade scale is A, B, C, D, E, Fx, F and UPP1 is pass/fail. The TEN2 grade is determined by the oral exam, optionally "plus one" if a presentation was given and awarded VG. For UPP1 the requirements are the following:

  1. Presence at seminars.
  2. All exercises handed in and passed.
  3. All peer reviews handed in and passed.
  4. Labs handed in and passed.

The aggregate course grade is the exam grade, and the exam grade "plus one", if the presentation was awarded VG. Additional adjustments either direction may in exceptional situations be done based on exercise and peer review performance, and contributions to the discussions.

PhD Students

Postgraduate students (using course code FDD3008) must pass the course at minimum level B, and must receive a VG grade for the paper presentation.

Covid-19

For Covid-19 reasons lectures and seminars are this year (2021) given on zoom. Exercise sessions are given physically on Campus, with ample space and attention to physical distancing. Labs are presented on zoom. The final (oral) exam will likely be done physically, details to be announced. 

 

Preparations before course start

Literature

Main textbook is

  • Maurice Herlihy, Nir Shavit, Victor Luchangco, Michael Spear: The art of multiprocessor programming, 2nd Edition, Morgan Kaufmann 2020.

The textbook is available online from the KTH library here.

We also use online course material from Roger Wattenhofer, ETHZ, see the reading lists for the relevant lectures.

Other material (papers, lecture notes) will be made available as the course pushes on.

Examination and completion

Grading scale

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

Examination

  • TEN2 - Oral exam, 4.5 credits, Grading scale: A, B, C, D, E, FX, F
  • UPP1 - Seminars, assignments and labs, 3.0 credits, Grading scale: P, 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.

The section below is not retrieved from the course syllabus:

Examination

Besides a number of obligatory elements detailed below, the main course evaluation is through an oral examination during the exam week following the course. The exam covers the entire body of course material presented in class, in slides or handouts, in exercises, and in the required reading material. Mads will explain the format of the exam in more detail in class. The exam grading scale is A-F.

Exercises and Exercise Peer Review

Exercise and exercise peer review hand-in by the assigned deadline is obligatory. The exercises to be handed in are marked clearly in the exercise sheets. Mostly these have the form "Answer 3 (alt. 4) of the following 4 (alt. 5 alt. 6) questions". This applies if you hand in your exercises in time. For late returns, all exercises must be completed. Exceptions are given only in special and well-documented circumstances. All assigned questions must be attempted and reviewed. There are no requirements on correctness, but a serious effort must be made. This applies to both the exercises and the peer reviews. Exercises and peer reviews are not graded but consistent outliers in either direction may be reflected in the final grade. 

You are allowed to discuss the exercises with your peers but you must produce the actual answer by yourself. No plagiarism.

Labs

Labs are done in pairs. Labs are graded pass/fail.

Seminars

Research paper presentations at one of the seminars are voluntary and graded on the scale [VG,G]. See About the Presentations for more detail. A VG presentation grade will cause a passing final grade to be raised one notch. For seminars the following grading criteria apply:

  • For G the presentation must bring out the basic contributions and motivational context of the paper in a manner that is comprehensible to the majority of students.
  • For VG the presentation must bring out the contributions and motivational context of the paper at a technically more advanced level, and communicate the insight in a manner that is well adapted to the audience.

Seminar attendance is obligatory. 

Late Assignments

  • What happens if you hand in your exercises late?
    • See above: You will need to hand in all exercises in the hand-in section of the exercise sheet.
  • What happens if you hand in your peer review late?
    • Write a short essay, pdf, 3-400 words, pdf, 12pt, single line, reflecting on the lectures covered by the exercises: Good, bad, relevance, learning objectives, what should be changed, what was hard, what was easy, what was important, what was less important. Submit together with the peer review.
  • What happens if you submit a lab late?
    • Write a short essay, 3-400 words, pdf, 11 pt, single line, summarising your reflections on the lab: What were the learning objectives in your opinion, how well did the lab succeed, what worked well and what did not, did you get appropriate information to do the lab, did the software you used to do the lab work well, do you have suggestions for improvements (other languages, other tools, other tasks), did you use any external resources? Submit together with the lab.
  • What happens if you're unable to attend a seminar?
    • Write a short essay, 3-400 words, pd, 11 pt, single line, summarizing one of the papers, or bodies of work, presented at the seminar: What problem is addressed? Why is it important (or not)? How is the problem approached? What are the key results?

Grading criteria/assessment criteria

Grading Criteria

For each of the grades listed below the following criteria apply:

For E: Ability to formulate basic concepts, definitions, and results in the area of parallel and distributed computation, and apply these concepts, definitions, and results to simple problems.

For D: In addition to apply the concepts, definitions, and results to a more advanced problem within some aspect of the course.

For C: In addition to apply the concepts, definitions, and results to advanced problems within both the parallel and distributed computation subareas.

For B: In addition to apply the concepts, definitions, and results to advanced problems within all areas of the course, and to formulate some basic ideas of some key proof construction presented in the course.

For A: In addition to correctly formulate key ideas of several proof constructions.

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

No information inserted

Round Facts

Start date

30 Aug 2021

Course offering

  • pardis21 Autumn 2021-51281

Language Of Instruction

English

Offered By

EECS/Computer Science

Contacts