Machine Learning based Parallelisation and HW/SW co-Design of
4 PhD studentships are available to study Machine Learning based Parallelisation and HW/SW co-Design of
for Heterogeneous multi-cores. The studentship will be held under thesupervision of
Prof. Michael O'Boyle, within the
Institute for Computing Systems Architecture, at the
School of Informatics, University of
Edinburgh, to begin in 2011, start date flexible.
The project will look at a variety of
projects in the areas of parallelisation and co-design where machine
learning is a key technique to select the best optimisation or design.
Parallelisation topics include the
development of new techniques for mapping parallelism using machine
learning; investigating dynamic compilation in the prescence of
workload as well as and prototyping OpenCL (or similar)
implementations where appropriate.
HW/SW co-Design projects include design
space exploration of the compiler/heterogeneous architecture co-space,
compiler-directed selection of hardware confifgurations and dynamic
hardware configuration based on runtime load.
Typical topics include:
The project topics are however flexible and can change based on the
The CaRD group at Edinburgh is internationally
leading in the use of machine learning for compiler and architecture
co-design and optimisation - this will form the backbone to this project.
Suitable candidates will have a strong first degree in Computer
Science and a strong interest in parallel programming, design space exploration, optimizing
compilers or machine learning. The exact topic of the PhD is flexible
depending on the candidate's interests. We are looking for the
brightest minds to pursue research in a cutting-edge arena.
The anticipated start date is Sept 2011 but this is flexible
Applying for the Studentship Candidates are encouraged to
contact Michael O'Boyle to
informally discuss the project further. Formal application will be
through the School's normal PhD