INF9380 - High Performance Computing in Bioinformatics
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.
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 write your own tools that works efficiently on parallel hardware
- How to adapt or write wrappers around existing tools to process large datasets efficiently using parallellisation
PhD candidates from the University of Oslo should apply for classes and register for examinations through Studentweb.
If a course has limited intake capacity, priority will be given to PhD candidates who follow an individual education plan where this particular course is included. Some national researchers’ schools may have specific rules for ranking applicants for courses with limited intake capacity.
PhD candidates who have been admitted to another higher education institution must apply for a position as a visiting student within a given deadline.
A maximum of 30 PhD-student can get admission to this course. The course is mainly for PhD-students in the NORBIS program. It may be possible to take the course for others if it is capacity.
Recommended previous knowledge
Basic unix competence and basic knowledge of bioinformatics applications is required. Basic programming skills, preferably in Python.
5 credits overlap with INF5380 - High Performance Computing in Bioinformatics
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.
Practical student project (home exam) with hand-in of written report.
Language of examination
The exam can be written in English or Norwegian
Grades are awarded on a pass/fail scale. Read more about the grading system.
Explanations and appeals
Resit an examination
Withdrawal from an examination
It is possible to take the exam up to 3 times. If you withdraw from the exam after the deadline or during the exam, this will be counted as an examination attempt.
Special examination arrangements
Application form, deadline and requirements for special examination arrangements.