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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.

The StarPlane project enables users to dynamically control network photonic paths. Applications running on the Distributed ASCI Supercomputer (DAS-3) can manipulate wavelengths in the Dutch research and education network SURFnet6. The goal is to achieve fast switching times so that when the computational pattern in the computing clusters changes, the underlying network topology adapts rapidly to the new traffic flow. StarPlane develops: the software to perform optimal traffic engineering; the management plane to map the users’ request into directives for the network control plane, as well as the integration to the DAS-3 Grid middleware. We present here some preliminary results obtained with few selected Grid applications that make use of StarPlane.

We describe the implementation of a transport simulation in a parallel environment. The implementation is based on a graphical parallel programming environment called P-GRADE. The transport simulator, called MadCity, simulates a specific road network of a city and shows cars moving on the roads. To achieve scalability of the traffic simulation, the use of templates is necessary. This helps to control the number of participating processes required for the simulation without making modifications to the simulator's source code. Performance results are collected from four, eight and sixteen nodes of the Parsifal cluster and compared with the sequential execution results of the simulator. The implementation of the transport simulator is extended further to support the simulation of multiple cities within the same cluster and on the Grid.