PhD Studentship in Machine-Learning Guided Compilation
4 weeks ago
Fixed-term: The funds for this post are available for 48 months.
The Project
Applications are invited for a PhD student to work on machine-learning guided and verifiably correct code generation.
Creating optimised libraries is a difficult and time-consuming task, requiring significant manual engineering effort. This process must be repeated for each new processor to take advantage of additional features, especially when it implements the latest architecture with new instructions or significant new architectural extensions, like Arm's SVE and SME. However, advances in machine learning point towards a low-cost solution to this task by automating code generation through a series of provably correct steps. A machine-learning model will guide the search for optimised code sequences, learning the best instructions to use for given intermediate code fragments and alleviating manual engineering effort.
The successful candidate will develop new code-generation strategies using machine-learning models and verification tools, suitable for deployment by library writers within the compilation toolchain, working closely with project partner, Arm.
Research Group
Our group consists of PostDocs and PhD students investigating performance, reliability and security in future many-core systems. We develop solutions within compilers, computer architectures and all associated tools, with a strong focus on parallelism. The position is within the Computer Architecture Research Group at the University of Cambridge Department of Computer Science and Technology, a vibrant and internationally leading environment. Collaboration with researchers at other universities and industry around the world is encouraged and there are strong links within the group with local, national and international companies.
Candidates
We seek candidates with a strong background in Computer Science (1st class honours degree or equivalent, although a Master's is particularly desirable) with a particular interest in compilers or binary modification tools and machine learning. Experience of writing code for a tool such as LLVM or DynamoRIO would be helpful, as would familiarity with working in teams with robust engineering practices (version control, continuous integration, automated testing)..
Full details of the University's entrance requirements and scholarships are specified on the following link:
Application Process
More Information
The funds are available for a start date in October 2024 but there is some flexibility to enable a start at other points in the academic year.
Further details may be obtained from Prof. Timothy Jones,
The University actively supports equality, diversity and inclusion and encourages applications from all sections of society.
The University has a responsibility to ensure that all employees are eligible to live and work in the UK.
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