Kursussøgning, efter- og videreuddannelse – Københavns Universitet

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Kursussøgning, efter- og videreuddannelse

Cluster Architectures and Computations

Practical information
Study year 2016/2017
Time
Block 3
Programme level Full Degree Master
ECTS 7,5 ECTS
Course responsible
  • Brian Vinter (6-887b808677845280747b407d8740767d)
Phone 35 32 14 21
  • The Niels Bohr Institute
Course number: NFYK13012U

Course content

To introduce parallel computers as target platform for applications that require either much memory or large computing power, or both.

The purpose of the class is to provide the student an understanding and practical experience with cluster-computing. Cluster-computing is becoming known to the general scientific community, including industry, and is increasingly becoming an alternative to classic supercomputers. The class covers classic supercomputer architectures and how these are programmed, as well as how clusters may emulate these so that applications and programming-techniques from different supercomputers may be used on clustercomputers. The target is that students obtain a detailed understanding of the problems that surround clustercomputers, as well as their known solutions and the limitations of these solutions. Topics: Parallel supercomputer architectures, advanced topics in CPU architecture, communication technology and machine-topology. Parallel algorithms, parallel programming and scientific computing. Programming using; threads, parallel virtual machines, message passing interface, remote memory and distributed shared memory.

Learning outcome

Skills
At the course completion the student should be able to:
1. Design and implement parallel applications
2. Design a cluster-computer for a specific purpose
3. Use threads for shared memory architectures
4. Use Message Passing Interface
5. Manage vectorization of operations
 

Competences
The overall purpose of this course is to enable the student to write high performance parallel applications on cluster-type architectures. In addition the successful candidate will become familiar with a number of classic parallel computer architectures and a set of high performance scientific applications.

 

 

Knowledge
The students will understand the challenges in addressing parallelization of applications and limitations of the available hardware. In addition the students should have an ingrained skeptic approach to commercially presented buzzwords and benchmarks and be able to objectively select the best platform for a given problem.

 

 

Recommended prerequisites

The student must be experienced with writing applications, especially applications for scientific modeling, simulation or data-processing.

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Education

M.Sc. programme in physics
M.Sc. programme in computer science

Studyboard

Study Board of Physics, Chemistry and Nanoscience

Course type

Single subject courses (day)

Duration

1 block

Schedulegroup

C
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Teaching and learning methods

Lectures and written projects.

Capacity

No restriction to number of participants

Language

English

Literature

Notes and articles.

Workload

Category Hours
Lectures 28
Preparation 178
English 206

Exam

Type of assessment

Continuous assessment
The class is evaluated through a set of reports that is written throughout the class. The final grade is the average of the best 3 reports. Each of these 3 reports must be passed separately with a grade of at least 02.

Aid

All aids allowed

Marking scale

7-point grading scale

Criteria for exam assessment

See Skills.

Censorship form

No external censorship
More internal examiners

Re-exam

Rexam: Three reports plus one week take home exam. The reports will be with known subjects identical to three of the reports given during the course. Approved reports from the course may be re-submitted no later than 2 weeks before the take-home exam, but will be re-evaluated. The take-home exam will be issued with an unknown subject. All four parts count equally in the final grade.

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