Completed Materials & Manufacturing Computing & AI

Application Customisation: Enhancing Design Quality and Developer Productivity

In plain English

AI plain-English summary

Computer chips are about to get a radical redesign, swapping fixed processors for flexible hardware that can reshape itself on the fly. The problem is that programming these customisable chips is currently so difficult that most developers avoid them, despite their huge potential for speed and energy savings. This project aims to solve that bottleneck by creating new design tools and automation methods that make custom computing systems as easy to program as ordinary computers. If successful, the work could transform how data centres operate, slashing energy use while accelerating tasks like genomic analysis for cancer diagnosis. The team has already shown that their approach can reduce bisulfite sequence alignment from hours to minutes—a leap that could speed up non-invasive prenatal testing and cancer screening. Beyond healthcare, the same technology could improve big data processing, cloud computing, and system reliability. The grant is primarily a platform for high-risk, exploratory research. It will support a team of researchers to test new ideas in three strategic areas: automated design tools, reconfigurable cloud architectures, and reliable system development. This flexible funding model has already proven its worth, helping 12 research associates secure permanent positions while producing disruptive advances like the first field-programmable chip capable of generating new configurations in a single clock cycle.

View original technical description
There have not been many shake-ups in mainstream processor architectures, since von Neumann articulated their basic principles in 1945 and Hoff developed the microprocessor architecture in 1969. This is changing: field programmable technology has been adopted by major companies such as Microsoft and Intel for datacentre computing, and new architectures are expected which integrate processor cores and field programmable resources on the same chip. These developments are largely motivated by improvements in performance and energy efficiency of field programmable technology, which are so promising that industrial adoption takes place despite the significant challenge of developing applications for custom computing systems based on field programmable technology. Our vision is to address this challenge by advancing the foundation and applications of customisation, which involves developing hardware and software to fit design requirements. The proposed Platform project aims to pioneer new capabilities for enhancing design quality and designer productivity of custom computing systems, with potential to revolutionise many applications including those with needs for big data processing or for improved reliability and security. It builds on success of disruptive research funded by our previous Platform (EP/I012036/1). An example of such success is research in runtime reconfiguration of custom computing systems: we developed new analysis methods to enable reconfiguration to remove idle functions; we showed how reconfiguration can benefit many applications such as genomic data processing and finite-difference computation. Our work is disruptive since, in contrast to current focus on partial reconfiguration, it demonstrates that full reconfiguration can provide significant energy-efficient acceleration over conventional multicore and manycore processors reducing, for example, runtime of Bisulfite sequence alignment from hours to minutes for non-invasive prenatal and cancer diagnosis. Moreover, we invented the first field programmable architecture capable of single-cycle on-chip configuration generation, while current commercial devices are based on off-chip configuration generation that can take hours. Such exciting progress is only possible because the Platform Grant enabled high-risk research by researchers who would otherwise suffer from funding gaps: 12 Research Associates in our team enjoyed Platform support before they found permanent positions. Renewed Platform support will allow continuing development of our dynamic and ambitious research team to explore next-generation computer systems and their applications. The flexibility of the renewed Platform Grant will be used to address three new strategic areas, on which we are uniquely capable of making major impacts; we will conduct exploratory research to identify promising projects for responsive mode or other forms of funding: 1. Multi-level tradeoff-aware design automation, which includes investigating customisation strategies and the associated tradeoffs, automation of effective customisation strategies, and developing reusable demonstration facilities and testbeds. 2. Reconfigurable big data and cloud architectures, which include customisable big data processing, runtime design generation and optimisation, and domain-specific cloud optimisation. 3. Reliable system development life cycle, which includes codesign of reliable and resilient systems, high-coverage testing and verification strategies, and reliability and resilience life cycle management. The added-value aspects for this Platform Grant proposal include: (a) ensuring a critical mass of researchers in key areas, (b) exploring significant strategic areas, (c) contributing to research infrastructure, (d) attracting fresh talents, (e) pioneering and strengthening international collaborations, and (f) accelerating technology transfer.

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Researchers

Christos Bouganis (Co-Investigator)Cristian Cadar (Co-Investigator)David Thomas (Co-Investigator)George Constantinides (Co-Investigator)Nobuko Yoshida (Co-Investigator)Paul Kelly (Co-Investigator)Peter Pietzuch (Co-Investigator)Peter Y K Cheung (Co-Investigator)Wayne Luk (Principal Investigator)

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Original classification

Research Grant

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