On the Usage of GPUs for Efficient Motion Estimation in Medical Image Sequences

Images are ubiquitous in biomedical applications from basic research to clinical practice. With the rapid increase in resolution, dimensionality of the images and the need for real-time performance in many applications, computational requirements demand proper exploitation of multicore architectures. Towards this, GPU-specific implementations of image analysis algorithms are particularly promising. In this paper, we investigate the mapping of an enhanced motion estimation algorithm to novel GPU-specific architectures, the resulting challenges and benefits therein. Using a database of three-dimensional image sequences, we show that the mapping leads to substantial performance gains, up to a factor of 60, and can provide near-real-time experience. We also show how architectural peculiarities of these devices can be best exploited in the benefit of algorithms, most specifically for addressing the challenges related to their access patterns and different memory configurations. Finally, we evaluate the performance of the algorithm on three different GPU architectures and perform a comprehensive analysis of the results

Report of the user requirements and web based access for eResearch workshops

The User Requirements and Web Based Access for eResearch Workshop, organized jointly by NeSC and NCeSS, was held on 19 May 2006. The aim was to identify lessons learned from e-Science projects that would contribute to our capacity to make Grid infrastructures and tools usable and accessible for diverse user communities. Its focus was on providing an opportunity for a pragmatic discussion between e-Science end users and tool builders in order to understand usability challenges, technological options, community-specific content and needs, and methodologies for design and development. We invited members of six UK e-Science projects and one US project, trying as far as possible to pair a user and developer from each project in order to discuss their contrasting perspectives and experiences. Three breakout group sessions covered the topics of user-developer relations, commodification, and functionality. There was also extensive post-meeting discussion, summarized here. Additional information on the workshop, including the agenda, participant list, and talk slides, can be found online at http://www.nesc.ac.uk/esi/events/685/ Reference: NeSC report UKeS-2006-07 available from http://www.nesc.ac.uk/technical_papers/UKeS-2006-07.pd

Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie

Toward interoperable bioscience data

© The Author(s), 2012. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Nature Genetics 44 (2012): 121-126, doi:10.1038/ng.1054.To make full use of research data, the bioscience community needs to adopt technologies and reward mechanisms that support interoperability and promote the growth of an open 'data commoning' culture. Here we describe the prerequisites for data commoning and present an established and growing ecosystem of solutions using the shared 'Investigation-Study-Assay' framework to support that vision.The authors also acknowledge the following funding sources in particular: UK Biotechnology and Biological Sciences Research Council (BBSRC) BB/I000771/1 to S.-A.S. and A.T.; UK BBSRC BB/I025840/1 to S.-A.S.; UK BBSRC BB/I000917/1 to D.F.; EU CarcinoGENOMICS (PL037712) to J.K.; US National Institutes of Health (NIH) 1RC2CA148222-01 to W.H. and the HSCI; US MIRADA LTERS DEB-0717390 and Alfred P. Sloan Foundation (ICoMM) to L.A.-Z.; Swiss Federal Government through the Federal Office of Education and Science (FOES) to L.B. and I.X.; EU Innovative Medicines Initiative (IMI) Open PHACTS 115191 to C.T.E.; US Department of Energy (DOE) DE-AC02- 06CH11357 and Arthur P. Sloan Foundation (2011- 6-05) to J.G.; UK BBSRC SysMO-DB2 BB/I004637/1 and BBG0102181 to C.G.; UK BBSRC BB/I000933/1 to C.S. and J.L.G.; UK MRC UD99999906 to J.L.G.; US NIH R21 MH087336 (National Institute of Mental Health) and R00 GM079953 (National Institute of General Medical Science) to A.L.; NIH U54 HG006097 to J.C. and C.E.S.; Australian government through the National Collaborative Research Infrastructure Strategy (NCRIS); BIRN U24-RR025736 and BioScholar RO1-GM083871 to G.B. and the 2009 Super Science initiative to C.A.S

e-Science and its implications

After a definition of e-science and the Grid, the paper begins with an overview of the technological context of Grid developments. NASA’s Information Power Grid is described as an early example of a ‘prototype production Grid’. The discussion of e-science and the Grid is then set in the context of the UK e-Science Programme and is illustrated with reference to some UK e-science projects in science, engineering and medicine. The Open Standards approach to Grid middleware adopted by the community in the Global Grid Forum is described and compared with community based standardization processes used for the Internet, MPI, Linux and the Web. Some implications of the imminent data deluge that will arise from the new generation of e-science experiments in terms of archiving and curation are then considered. The paper concludes with remarks about social and technological issues posed by Grid enabled ‘collaboratories’ in both scientific and commercial contexts

Pseudospectra of the Linear Navier-Stokes Evolution Operator and Instability of Plane Poiseuille and Couette Flows: (preliminary report)

This is a rough, interim report on some new results concerning the stability of plane Poiseuille and Couette fluid flows, following upon recent work by Henningson and Reddy, Butler and Farrell, Gustavsson and others. We emphasize that the conclusions proposed here have not yet been checked carefully and are subject to change. Our principal results are as follows: 1. Plots of the spectra of the "full" Navier-Stokes operator for Poiseuille and Couette flows, i.e., without restriction to a wave number pair ($\alpha, \beta$) or to even or odd modes ($\S\S$4,5). 2. Analogous plots for the pseudospectra of this operator. Comparison of the pseudospectra with the spectra gives a new interpretation of why the physics of these linear flow problems is not controlled by the location of the most unstable eigenvalue ($\S\S$4,5). 3. Demonstration that these pseudospectra predict the Butler-Farrell "optimal" transient energy growth ratios to within a factor of about 2 ($\S$6). 4. Demonstration that about 90% of the Butler-Farrell growth can be achieved by a 3$\times$3 linear model obtained by projecting the Navier-Stokes problem onto the space spanned by three dominant eigenmodes, for Couette flow, or four in the case of Poiseuille flow ($\S$8). 5. Demonstration that although 1 Orr-Sommerfeld mode and 3 Squire modes suffice for the 4$\times$4 model in the Poiseuille case, in keeping with a recent result of Gustavsson, one can do equally well with 2 modes of each kind or with 3 Orr-Sommerfeld modes and 1 Squire mode ($\S$8). 6. Demonstration that the minimal operator perturbation required to destabilize a stable flow has norm of order $R^-$$^2$, where $R$ is the Reynolds number, though the distance of the least stable eigenvalue from the real axis is $O (R^-$$^1$) ($\S$7). 7. Presentation of a 2$\times$2 model illustrating that if the linear problems described above are capable of transient energy growth of order $M$ (e.g., $M\approx$1000 according to Butler and Farrell), a weak and intrinsically energy-conserving nonlinear term can "bootstrap" that growth to a higher order such as $M^2$. This supports the view that although nonlinear terms are of course essential to the subcritical instability of fluid flows, the detailed nature of the nonlinear interactions may sometimes be relatively unimportant ($\S$2). 8. Adaptation of this "bootstrapping" idea to the fluid flows considered earlier, particularly the 3$\times$3 approximation for Couette flow with $R$=1000

Cyberinfrastructure for e-Science

Here we describe the requirements of an e-Infrastructure to enable faster, better, and different scientific research capabilities. We use two application exemplars taken from the United Kingdom’s e-Science Programme to illustrate these requirements and make the case for a service-oriented infrastructure. We provide a brief overview of the UK ‘‘plug-and-play composable services’’ vision and the role of semantics in such an e-Infrastructure

The UK e-Science Core Programme and the Grid

This paper describes the £ 120M UK 'e-Science' (http://www.research-councils.ac.uk/and http://www.escience-grid.org.uk) initiative and begins by defining what is meant by the term e-Science. The majority of the £ 120M, some £ 75M, is funding large-scale e-Science pilot projects in many areas of science and engineering. The infrastructure needed to support such projects must permit routine sharing of distributed and heterogeneous computational and data resources as well as supporting effective collaboration between groups of scientists. Such an infrastructure is commonly referred to as the Grid. Apart from £ 10M towards a Teraflop computer, the remaining funds, some £ 35M, constitute the e-Science 'Core Programme'. The goal of this Core Programme is to advance the development of robust and generic Grid middleware in collaboration with industry. The key elements of the Core Programme will be outlined including details of a UK e-Science Grid testbed. The pilot e-Science projects that have so far been announced are then briefly described. These projects span a range of disciplines from particle physics and astronomy to engineering and healthcare, and illustrate the breadth of the UK e-Science Programme. In addition to these major e-Science projects, the Core Programme is funding a series of short-term e-Science demonstrators across a number of disciplines as well as projects in network traffic engineering and some international collaborative activities. We conclude with some remarks about the need to develop a data architecture for the Grid that will allow federated access to relational databases as well as flat files