INF5380 – High Performance Computing in Bioinformatics

Schedule, syllabus and examination date

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Changes in the course due to coronavirus

Autumn 2020 the exams of most courses at the MN Faculty will be conducted as digital home exams or oral exams, using the normal grading scale. The semester page for your course will be updated with any changes in the form of examination.

See general guidelines for examination at the MN Faculty autumn 2020.

Course content

This course focuses on the application of high performance computing (HPC) to bioinformatics analysis. The main target is to provide a background on how to effectively use HPC clusters for running computationally or data intensive bioinformatics applications. The course will mainly include teaching students selected bioinformatics tools and workflows, and how to use HPC platforms to speed up and maximize the overall throughput of intensive bioinformatics analysis. This would include, e.g. how to optimize the use of available compute nodes, and how to adapt the application to the available resources on each compute node.The course will cover both how to efficiently use parallelism when writing your own programs, as well as how to adapt and wrap existing tools in manner that efficiently exploits resources available on parallel architectures.

Learning outcome

After finishing the course the students should know:

  • Resource intensive bioinformatics tools for, e.g. assembly, mapping/alignment, and multiple alignment. This would include the use of commandline tools and portal based tools, e.g. Galaxy.
  • How those tools work, how this would influence the runtime, and the possibility of parallelizing the computation.
  • When to use parallelization and distribution.
  • The basic structure of HPC clusters, and how to run jobs on a cluster
  • How to evaluate the use of resources on a cluster, and how to optimize the use of memory and CPUs
  • How to adapt or write wrappers around existing tools to process large datasets efficiently using parallellisation

Admission to the course

This course is only avaliable if the PhD version has capacity.

Basic unix competence and basic knowledge of bioinformatics applications is required. Basic programming skills, preferably in Python.

Overlapping courses

Teaching

This as an intensive two weeks course with lectures and hands on exercises 7 hours a day, Monday to Friday. About half the time with lectures and the other half with exercises. In total lectures and exercises are estimated to 70 hours. Selfstudy/reading of curriculum is estimated to 30 hours. Preparation time for written report (home exam) is estimated to 40 hours. The total workload for the course is estimated to 140 hours.

Examination

Practical student project (home exam) with hand-in of written report.

Grading scale

Grades are awarded on a scale from A to F, where A is the best grade and F is a fail. Read more about the grading system.

Resit an examination

Special examination arrangements, use of sources, explanations and appeals

See more about examinations at UiO

Last updated from FS (Common Student System) Nov. 1, 2020 12:17:50 AM

Facts about this course

Credits
5
Level
Master
Teaching

Spring 2020

Spring 2022

Every other spring starting 2016

Examination
Spring
Teaching language
English