Arvutiteaduse instituut
  1. Kursused
  2. 2017/18 kevad
  3. Teadusarvutuste taristud (MTAT.08.037)
EN
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Teadusarvutuste taristud 2017/18 kevad

  • Pealeht
  • Praktikumid
    • Esitamine
  • Projektid
  • Viited

Scientific computing infrastructures

Introductory e-course on using clusters and remote computers to run workflows related to scientific computing. It is primarily intended as a general introduction to using high performance and distributed computing resources in Estonia and will be offered as an e-course with no lectures, but weekly reading and assignments with detailed feedback. Optional consultation sessions will also be available. The required background is some introductory programming experience (for example writing a python program or creating a web page using HTML) and the course is suitable for a wide audience. The course should be useful to:

  1. People running computational chemistry, physics and bioinformatics packages
  2. People who need to work with large data sets and share them (for example using parallel R)
  3. People who need to share information with their colleagues by deploying applications in the cloud (for example setting up your own Wordpress blogging instance, moodle teaching platform, email server, online shop)
  4. People that have programs that can utilize graphical processing units to speed up calculations and/or information processing
  5. People who want to produce computer animations using distributed rendering (for example using Blender distributed rendering)

The course is not meant to be a detailed introduction to parallel programming or code optimization.

The course will comprise the following topics:

  • Overview of Estonian and European scientific computing infrastructures, security
  • Introduction to linux, filesystem performance and slurm job scheduler
  • Introduction to MPI, OpenMP and accelerators
  • Overview of OpenStack - installing and running your own cloud service application
  • Hands on cluster/cloud construction with mini computers
  • Project

Grading: Basic grading guidelines will be used: A 91-100, B 81-90, C 71-80, D 61-70, E 51-60, F 0-51

Points distribution: Lab submissions 60%, final project 20%, exam 20%

Tutors:

  • Benson Muite (benson punkt muite at ut punkt ee)
  • Joonas Puura

Attach:ExamQuestions.pdf

  • Arvutiteaduse instituut
  • Loodus- ja täppisteaduste valdkond
  • Tartu Ülikool
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