University of Edinburgh
PhD Studentship
Adaptive Parallel Optimising Compilation using Machine Learning
School of Informatics
Multi-core processors are the most viable means to delivering sustainable performance. However, this potential cannot be realised unless the application has been well parallelised. Unfortunately, efficient parallelisation of a sequential program is a challenging and error-prone task. It is generally agreed that manual code parallelisation by expert programmers results in the most streamlined parallel implementation, but at the same time this is the most costly and time-consuming approach. Parallelising compiler technology, on the other hand, has the potential to greatly reduce cost and time-to-market while ensuring formal correctness of the resulting parallel code. Given that the underlying processor architecture will change many times throughout the lifetime of the code, we would like parallel programs that are performance future proof too.
The project student will investigate new compiler directed approaches to delivering performance in a multi-core environment where the data input, concurrent workload and underlying architecture are evolving.
Probabilistic analysis can be used to determine program parallelism which can then be mapped to available resources. Central to this work will be the use of machine learning as a technique to learn and adapt the parallel code to this changing parallel landscape. The CaRD group at Edinburgh (http://www.icsa. informatics. ed.ac.uk/ compilers/ <http://www.icsa. informatics. ed.ac.uk/ compilers/> ) 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.
The studentship, sponsored by the Centre for Numerical Algorithms and Intelligent Software (NAIS), will be available for study commencing in September 2009.
Suitable candidates will have a first degree in Computer Science and a strong interest in parallel programming and the interface between programs, compilers and computer architecture.
Informal enquiries regarding this studentship can be made to Michael O'Boyle (mob at inf.ed.ac.uk) . Further details about the project can also be found at http://www.dcs. ed.ac.uk/ home/mob/ phdplace. html.
Applications are welcome from UK, EU and overseas candidates. To apply please submit an application using the University's online application system, mentioning "NAIS Studentship" . Further details are at http://www.ed. ac.uk/studying/ postgraduate/ finder/details. php?id=492.
Application deadline: 30 April 2009. Applications after that date may be considered if the studentship has not been allocated.
Saturday, March 21, 2009
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