PhD Studentship: Hardware Acceleration of Exome Sequencing

Location
United Kingdom
Posted
Dec 21, 2016
Closes
Dec 20, 2017
Organization Type
University and College
Hours
Full Time
PhD Studentship: Hardware Acceleration of Exome Sequencing

Engineering & the Environment

Location: Highfield Campus

Closing Date:  Wednesday 20 December 2017

Reference: 820516F2

PROJECT REFERENCE: NGCM - 0062

This project aims to develop novel methods to accelerate genome sequencing using Field Programmable Gate Arrays (FPGAs) as configurable processing elements.

Genome sequencing offers the possibility of identifying the genetic mutations responsible for many serious medical conditions. It is not necessary, however, to sequence an entire genome – a selected subset, an exome, is sufficient.

Exome sequencing has conventionally been performed on sequential computers. Although only about 1% of a genome is analysed, the task is computationally intensive because there remain about 30 million base pairs and 10s of individuals may be compared at a time. While naive, task-level parallelism is achievable, the computational cost remains high.

The aim of this project is to investigate how significant computational speed up can be achieved by using hardware accelerators – FPGAs.

The basic computational task is relatively simple, which suggests that such accelerators are practical. The implementation of such tasks requires specialist knowledge. A second aim, therefore, is to develop a tool flow that can be used by other researchers. These tools will be made open source, thus aligning the project with the growing open source hardware industry.

The simplicity of the computation and the fact that it can be parallelised means that data needs to be supplied very rapidly to keep the hardware accelerator busy. Therefore, a third aim of the project is to identify any bottlenecks in getting the data to the processing elements and to develop ways to minimise their effects.

Because of justified concerns about privacy and security, it will not be possible to use human data in this project. It is entirely reasonable and practical to use plant or animal data both as proof of concept and as an end in itself.

If you wish to discuss any details of the project informally, please contact Prof Mark Zwolinski, EEE research group, Email: mz@ecs.soton.ac.uk, Tel: +44 (0) 2380 59 3528.

This project is run through participation in the EPSRC Centre for Doctoral Training in Next Generation Computational Modelling (http://ngcm.soton.ac.uk). For details of our 4 Year PhD programme, please see http://www.findaphd.com/search/PhDDetails.aspx?CAID=331&LID;=2652

For a details of available projects click here http://www.ngcm.soton.ac.uk/projects/index.html

Further details:

  • Job Description and Person Specification