PhD Studentships in Optimisation for Deep Learning on Embedded Devices
Two PhD studentships are available in collaboration with ARM
Two PhD studentships are available under the supervision of Prof. Michael O'Boyle within the Institute for Computing Systems Architecture, at the School of Informatics, The University of Edinburgh, to begin in 2017 which start date are flexible. Both these studentships are in collaboration with ARM. The projects are concerned with efficient implementation of deep learning networks on constrained devices. While there has been much activity in how to efficiently learn a network with large training data, there is much less on how to deploy it efficiently on an constrained resource device. The best network and code structure depends on scenario and there will be a trade-off between space, time, energy and accuracy.
The projects will investigate code optimisations, to explore these trade-offs, such as;
- code specialisation,
- higher-parameter exploration,
- auto-tuned libraries,
- reduced bit data representation etc.
How to update and adapt the network to new data could also be an an area of research.
See 'Bonseyes PhD places' for more details.