Retroactively Parallelizing a Large Python System

In the field of bioinformatics, the immense increase in the generation of genomic scale data poses an unmet analytical challenge, due to a lack of established methodology with the required flexibility and power. The Hyperbrowser (http://hyperbrowser.uio.no) is a framework written in Python for comparative analysis of sequence-level genomic data and aims to solve this problem. It is currently a single-threaded system, and in order to both be able to scale better and to reduce the analysis time, parallelization is desirable.

The goal of the task is to parallelize the HyperBrowser system, and in using this as a case also exploring general issues connected to retroactively parallelizing systems, as well as issues related to providing interactive functionality with a queueing system under the hood. Both a powerful SMP system as well as the Titan compute cluster is available, and ideally both should be utilized in order to maximize the speedup gained from parallelization.

Students should be skilled in programming and have background knowledge on parallelization. No prior knowledge of biology is needed.