Data science at scale

Building upon advances in high-performance computer architectures, through algorithm-architecture co-design, with applications including health and life science.


Advances in high-performance computer architectures, and the way algorithms can take advantage of them, have been transformative for a variety of data science tasks.

This scientific programme at the Turing, in partnership with Intel, will build upon these successes through co-design of algorithms and computer architectures, a range of applications, and by training a new generation of data scientists with the computational skills required to solve the major data analysis tasks of the future.

Researchers from both Turing and Intel are working collaboratively under the shared goal to shape the future of computation for data science.

Programme challenges

Researchers from both Turing and Intel are working collaboratively under the shared goal to shape the future of computation for data science. This involves the following challenges and aims.

Algorithm-architecture co-design

As data science continues to grow as an industry and research sector, data-driven algorithms such as those required by deep learning – multi-level networks that gradually identify things at higher levels of detail – take up an increasing amount of valuable time and energy in data centres. This provokes a need to rethink how the technical challenges caused by this emerging new science are managed.

Hardware needs to be designed to suit the needs of data science algorithms, and algorithms need to similarly be designed to suit the capabilities of the hardware.

Training a new generation

The significant industry, government, and academic demand for data science skills creates a supply problem, with the UK facing a major skills gap which could inhibit the anticipated potential of data science and AI for our economy and society.

As well as conducting research, this programme’s partnership is training a new generation of data scientists through the Turing’s doctoral programme, ensuring students are equipped with the latest data science techniques, tools, and methodologies.

Improving hardware

Intel has dedicated a hardware architecture team at the Institute’s facilities in the University of Edinburgh.

The programme aims to dramatically increase the speed and efficiency of data-driven computing tasks and provide Intel with the tools to build the next generation of computer processors and high-performance systems.


Collaboration between the programme and the NHS

An announcement was made about a collaboration between the data science at scale programme and the University of Warwick, Intel, and University Hospitals Coventry & Warwickshire NHS Trust (UHCW). The collaboration involves using ground-breaking artificial intelligence techniques to detect and classify cancer cells more efficiently and accurately.

Scientists at the University of Warwick’s Tissue Image Analytics (TIA) Laboratory – led by Professor Nasir Rajpoot from the Department of Computer Science – are creating a large, digital repository of a variety of tumour and immune cells found in thousands of human tissue samples, and are developing algorithms to recognize these cells automatically.

Professor David Snead, clinical lead for cellular pathology and director of the UHCW Centre of Excellence, comments that ‘the successful adoption of these tools will stimulate better organisation of services, gains in efficiency, and above all, better care for patients, especially those with cancer.”

Read the ZDNet article about the announcement – “NHS taps artificial intelligence to crack cancer detection”