Writing optimising compilers is difficult. The range of programs that may be presented to the compiler is huge and the system on which they run are complex, heterogeneous, non-deterministic, and constantly changing. Machine learning has been shown to make writing compiler heuristics easier, but many issues remain.
In this talk I will discuss recent advances in using deep learning to solve compiler issues: learning heuristics and testing compiler correctness.
Hugh is a reader (associate professor) at the University of Edinburgh. His research involves all elements of compilers and operating systems, usually targeting performance and energy optimisation, often with a focus on using machine learning for those tasks. After his PhD, also at Edinburgh, he was a Fellow of the Royal Society of Engineering. Before returning to academia, he was an engineer at Microsoft and architect and team leader at Trilogy, delivering multi-million dollar projects to Fortune 500 companies.
- When: 9th April 2019 14:00 - 15:00
- Where: Cole 1.33a
- Series: School Seminar Series
- Format: Seminar