Parallelism has become an essential component of mainstream computer systems, pervasive across all scales, from system-on-chip to cloud computing.
We have a four year PhD programme combining advanced coursework and independent PhD-level research.
Check out some examples of the wide-ranging research in pervasive parallelism currently being performed by Centre faculty.
Our team of over 45 academic staff carry out exciting research in all areas of data science.
- How should we design parallel programming languages and compilers?
- How should we design and implement parallel architectures and communication networks?
- What theories do we need to prove properties of such systems, or to model and reason about their performance?
- How can concurrent and distributed systems be made secure?
- How can we trade performance for energy in context sensitive ways?
- How can we make algorithms and applications robust against the failures inevitable in exascale systems?
In the Centre for Doctoral Training in Pervasive Parallelism we seek to develop the research leaders of the future across these areas. Our core principle is that the most important research insights will be achieved by those who have deep knowledge and awareness across the parallelism spectrum. Our programme is designed to develop these characteristics in our student cohort.