Contrastin M.,University of Cambridge |
Rice A.,University of Cambridge |
Danish M.,University of Cambridge |
Orchard D.,Imperial College London |
Orchard D.,Software Sustainability Institute
Computing in Science and Engineering | Year: 2016
The authors argue that they can increase confidence in Fortran programs with unit annotations and CamFort units-of-measure analysis. © 2016 IEEE.
MacLean D.,Norwich Research Park |
Aleksic J.,University of Cambridge |
Alexa A.,DNAdigest |
Attwood T.K.,University of Manchester |
And 14 more authors.
F1000Research | Year: 2015
One of the foundations of the scientific method is to be able to reproduce experiments and corroborate the results of research that has been done before. However, with the increasing complexities of new technologies and techniques, coupled with the specialisation of experiments, reproducing research findings has become a growing challenge. Clearly, scientific methods must be conveyed succinctly, and with clarity and rigour, in order for research to be reproducible. Here, we propose steps to help increase the transparency of the scientific method and the reproducibility of research results: specifically, we introduce a peer-review oath and accompanying manifesto. These have been designed to offer guidelines to enable reviewers (with the minimum friction or bias) to follow and apply open science principles, and support the ideas of transparency, reproducibility and ultimately greater societal impact. Introducing the oath and manifesto at the stage of peer review will help to check that the research being published includes everything that other researchers would need to successfully repeat the work. Peer review is the lynchpin of the publishing system: encouraging the community to consciously (and conscientiously) uphold these principles should help to improve published papers, increase confidence in the reproducibility of the work and, ultimately, provide strategic benefits to authors and their institutions. © 2015 Aleksic J et al.
Agency: GTR | Branch: EPSRC | Program: | Phase: Fellowship | Award Amount: 488.45K | Year: 2016
Advances in High Performance Computing (HPC) and scientific software development will have increasingly significant societal impact through the computational design of new products, medicines, materials and industrial processes. However, the complexity of modern HPC hardware means that scientific software development now requires teams of scientists and programmers to work together, with different and non-overlapping skill-sets required from each member of the group. This complexity can lead to software development projects stalling. Investments in software development are in danger of being lost, either because key members of a team move on, or because a lack of planning or engagement means that a sustainable user and developer community has failed to gel around a particular code. Research Software Engineers (RSEs) can solve this problem. RSEs have the skills and training necessary to support software development projects as they move through different stages of the academic software lifecycle. Academic software evolves along this lifecycle, from being a code used by an initial team of researchers, through to a large multi-site community code used by academics and industrialists from across the UK and around the World. RSEs provide the training and support needed to help academic software developers structure their projects to support the sustainable growth of their user and developer communities. RSEs are also highly skilled programmers who can train software developers in advanced HPC techniques, and who can support developers in the implementation, optimisation and testing of complex and intricate code. Together with academic software developers, RSEs can support UK investment in HPC, and ensure that the potential of computational science and engineering to revolutionise the design of future products and industrial processes is realised. This project aims to develop sustainable RSE career pathways and funding at Bristol. This will support the growth of a sustainable team of RSEs at the University. Software development projects that will be supported include; the building of code to interface real biological cells with virtual simulated cells, so to support the rapid design of new biomanufacturing control processes; the development of code to more quickly model the behaviour of electrons in novel materials, to support the design of new fuel cells and batteries; code to improve our understanding of glass-like matter, so to help design new materials with exciting new properties; software to support modelling of the quantum interaction between laser light and microscopic nanoparticles, to support the design of optical tweezers and new optically driven nanomachines; and code to design new medicinal drugs and to understand why existing treatments are no longer working, thereby supporting the development of 21st century medicine. Finally, this project aims to create a coherent set of teaching materials in programming and research software engineering. These, together with the development of software to support science and programming lessons held in an interactive 3D planetarium, will help inspire and educate the next generation of scientists and RSEs. These materials will showcase how maths, physics, computing and chemistry can be used in the real world to create the high-tech tools and industries of the future.
Agency: GTR | Branch: EPSRC | Program: | Phase: Training Grant | Award Amount: 3.94M | Year: 2014
The achievements of modern research and their rapid progress from theory to application are increasingly underpinned by computation. Computational approaches are often hailed as a new third pillar of science - in addition to empirical and theoretical work. While its breadth makes computation almost as ubiquitous as mathematics as a key tool in science and engineering, it is a much younger discipline and stands to benefit enormously from building increased capacity and increased efforts towards integration, standardization, and professionalism. The development of new ideas and techniques in computing is extremely rapid, the progress enabled by these breakthroughs is enormous, and their impact on society is substantial: modern technologies ranging from the Airbus 380, MRI scans and smartphone CPUs could not have been developed without computer simulation; progress on major scientific questions from climate change to astronomy are driven by the results from computational models; major investment decisions are underwritten by computational modelling. Furthermore, simulation modelling is emerging as a key tool within domains experiencing a data revolution such as biomedicine and finance. This progress has been enabled through the rapid increase of computational power, and was based in the past on an increased rate at which computing instructions in the processor can be carried out. However, this clock rate cannot be increased much further and in recent computational architectures (such as GPU, Intel Phi) additional computational power is now provided through having (of the order of) hundreds of computational cores in the same unit. This opens up potential for new order of magnitude performance improvements but requires additional specialist training in parallel programming and computational methods to be able to tap into and exploit this opportunity. Computational advances are enabled by new hardware, and innovations in algorithms, numerical methods and simulation techniques, and application of best practice in scientific computational modelling. The most effective progress and highest impact can be obtained by combining, linking and simultaneously exploiting step changes in hardware, software, methods and skills. However, good computational science training is scarce, especially at post-graduate level. The Centre for Doctoral Training in Next Generation Computational Modelling will develop 55+ graduate students to address this skills gap. Trained as future leaders in Computational Modelling, they will form the core of a community of computational modellers crossing disciplinary boundaries, constantly working to transfer the latest computational advances to related fields. By tackling cutting-edge research from fields such as Computational Engineering, Advanced Materials, Autonomous Systems and Health, whilst communicating their advances and working together with a world-leading group of academic and industrial computational modellers, the students will be perfectly equipped to drive advanced computing over the coming decades.
Crouch S.,Software Sustainability Institute |
Crouch S.,University of Southampton |
Hong N.C.,Software Sustainability Institute |
Hong N.C.,University of Edinburgh |
And 16 more authors.
Computing in Science and Engineering | Year: 2013
To effect change, the Software Sustainability Institute works with researchers, developers, funders, and infrastructure providers to identify and address key issues with research software. © 2013 IEEE.