Programming Languages Research

Discovery

Discovery: Pattern Discovery and Program Shaping for Manycore Systems

Computing pervades our lives, impacting our health, work, entertainment and social interaction. Over recent years, the technology inside the devices providing these services has undergone a radical change: where once, processing was undertaken by relatively homogeneous “sequential” devices, in which essentially one thing happened at a time, the new systems compose a range of specialized devices, some targeting specific problem sub domains, and almost all exhibiting considerable “parallelism”, where many things can happen at the same time. This is true on all scales, from the internals of a mobile phone, to the massive data centres which serve web applications such as Google. This poses a substantial challenge for the software industry: writing correct and efficient programs for heterogeneous, highly parallel systems is much harder than for current technologies and most developers lack the skills and training to write safe and efficient code. Faced with this difficulty, software developers will often avoid writing parallel code completely, or else will use inappropriate, non-scalable and error-prone approaches based on explicit threads of program execution. Given the hardware trend towards increasingly complex, increasing parallel (manycore) systems, this is an inherently short-term strategy that is doomed to failure,

Our project addresses this issue. Our key insight is that humans in general, are very good at using patterns to understand, predict and act in the real world. This insight translates into the world of software engineering in general, and parallel heterogeneous programming in particular. Our work will help programmers to recognize patterns in pre-existing and new applications, and to transform these pattern occurrences into forms which allow them to be exploited, adapted and run effectively on the new hardware platforms. The systems we develop will work in partnership with software developers, reducing the complexity of the task, automating and semi-automating the development task. The result will help the industry to develop new applications, and to update existing applications, with less effort, fewer errors and better resilience as the underlying technology continues to evolve.

Contact: Dr John Thomson, Dr Susmit Sarkar, Dr Vladimir Janjic, Dr Chris Brown.