22112 High Performance Computing in Life Science
The course takes place in building 210, auditorium 012, Monday afternoon from 13.00 to 17.00. F2A.
Course content overview
The course is a practical introduction to working with supercomputers in Life Science. Using Computerome, the Danish National Supercomputer for Life Sciences as a basis for lectures and exercises, we will cover subjects such as computer design, queueing systems, distributed computing, algorithms, parallel programming, performance and performance dependencies, database design and use, and practical organization of projects.
Being comfortable with using the Unix shell and being able to navigate the file system is required. If you feel your Unix knowledge lacking, consult this unix tutorial.
Having a good skill in Python programming is mandatory. A course like 22110 should enable you to participate.
There will be weekly exercises, which have to be handed in after 7 days on DTU Learn and peer evaluated the week after. A link to DTU Learn can also be found on DTU Inside for the course. You can only peer evaluate if you have handed in, and at you must have at least 11 out of 13 acceptable (by the teacher) hand-ins and evaluations to pass. The course is graded as pass/fail based on the exercises.
- 03/02 Lesson 1: Computer design
- 10/02 Lesson 2: Queueing System
- 17/02 Lesson 3: Distributed computing
- 24/02 Lesson 4: What affects performance
- 02/03 Lesson 5: Algorithms
- 09/03 Lesson 6: Parallel programming
- 16/03 Lesson 7: More parallelism
- 23/03 Lesson 8: MapReduce and Binary representation
- 30/03 Lesson 9: Hash usage
- 20/04 Lesson 10: Databases
- 27/04 Lesson 11: MySQL
- 04/05 Lesson 12: Coding against databases
- 11/05 Lesson 13: Exercises and Organization