To develop, embed and exploit expertise in leading edge algorithms for numerical linear algebra to enable the development of the next generation software for the computer architecture of tomorrow.
80,306
2014-10-01 to 2016-09-30
Collaborative R&D
Spectral microscopy is a rapidly growing field critical with applications in pharmaceutical development, biomedical diagnostics and forensics. This project aims to develop reliable, validated, high speed data analysis tools for exploration and analysis of multi-mode spectral microscopy data. Spectral microscopy is used for label- free detection of molecular compounds within the micro and nano-scale structures of cells, tissues and materials. It encompasses a wide range of techniques such as Raman Microscopy and Mass Spectrometry Imaging and is of increasing importance in biomedical research. Applications are found in pharmaceutical development, disease detection, biomaterials design, forensic analysis, and characterization of nano-structured materials. Analysis of the very large hyperspectral image stacks acquired by these instruments is computationally challenging. Accurate interpretation often depends on combining multiple complementary imaging modes. The tools developed in the project will allow non-ICT experts to combine multiple types of imaging data and efficiently explore these data sets to create novel insights.
2013-05-01 to 2013-10-31
Knowledge Transfer Partnership
To translate specialised mathematical algorithms for evaluating matrix functions into software and embed processes and expertise in developing matrix functions software.
2012-06-01 to 2013-12-31
Knowledge Transfer Partnership
To develop, tune and integrate key components of the Parallel Linear Algebra for Scalable Multicore Architectures library to support its products.