Machine Learning based Parallelisation for Heterogeneous multi-cores
2 PhD studentships are available to study Machine Learning based Parallelisation 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 2010, start date flexible.
Project
The efficient mapping of program parallelism to multi-core,
heterogeneous processors is extremely challenging and highly dependent
on the underlying architecture. The overall objective of this project
is to investigate a novel parallel compiler approach that can
automatically learn how to best map program parallelism to multi-core,
heterogeneous platforms. Rather than hard-coding a compiler strategy
for each parallel platform, we aim to explore an innovative, portable,
parallel compiler approach that can automatically self-adapt to any
heterogeneous hardware and can improve its performance over time.
This is achieved by employing machine learning approaches which first
learn the optimisation space off-line and then automatically derive a
strategy that attempts to generate the ``best'' mapping for any user
program. This predictive modelling approach can be further extended to
on-line adaptation to manage contention for resources. This project
is aimed at exploring multi-core system software that is ``future
scalable'' and if successful, will have a wide range of applications
from desktops to embedded mobile devices. It will allow portable
performance of parallel programs across platforms.
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.
Candidate Profile
Suitable candidates will have a strong first degree in Computer
Science and a strong interest in parallel programming, 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.
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
application process.