Dates: 18th – 29th April 2016
Location: University of Oslo
Lecturers: Torbjørn Rognes, Abdulrahman Azab, Merete Molton Worren and Lex Nederbragt
Course code:INF9380
Credits: 5 ECTS
Registration: 1st February for exam and credits / 1st March for following lectures
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. Read more [ddownload id=”323″ text=”here”], and find practical information here.
Registration for this course is dual. Note that we have a limited number of seats available.
- If you are a PhD student, and want to earn 5 credits for this course, you must first sign up formally for the course and exam through the UiO student webpages here, by 1st February. You must then register with NORBIS here, preferably at once.
- We also invite other participants to follow this course, without taking the exam and earning credits (post docs, experienced PhD students, other researchers…). Please register here
Important note: students from other institutions than the University of Oslo must have been granted status as a visiting PhD student in order to register to the course. The deadline for submitting this application was 6th January 2016. Please contact NORBIS if you missed that date and still want to follow the course, we will try to work it out with UiO.