A pilgrimage to gravity on GPUs

In this short review we present the developments over the last 5 decades that have led to the use of Graphics Processing Units (GPUs) for astrophysical simulations. Since the introduction of NVIDIA's Compute Unified Device Architecture (CUDA) in 2007 the GPU has become a valuable tool for N-body simulations and is so popular these days that almost all papers about high precision N-body simulations use methods that are accelerated by GPUs. With the GPU hardware becoming more advanced and being used for more advanced algorithms like gravitational tree-codes we see a bright future for GPU like hardware in computational astrophysics.Comment: To appear in: European Physical Journal "Special Topics" : "Computer Simulations on Graphics Processing Units" . 18 pages, 8 figure

Computational Physics on Graphics Processing Units

The use of graphics processing units for scientific computations is an emerging strategy that can significantly speed up various different algorithms. In this review, we discuss advances made in the field of computational physics, focusing on classical molecular dynamics, and on quantum simulations for electronic structure calculations using the density functional theory, wave function techniques, and quantum field theory.Comment: Proceedings of the 11th International Conference, PARA 2012, Helsinki, Finland, June 10-13, 201

Dynamical Processes in Globular Clusters

Globular clusters are among the most congested stellar systems in the Universe. Internal dynamical evolution drives them toward states of high central density, while simultaneously concentrating the most massive stars and binary systems in their cores. As a result, these clusters are expected to be sites of frequent close encounters and physical collisions between stars and binaries, making them efficient factories for the production of interesting and observable astrophysical exotica. I describe some elements of the competition among stellar dynamics, stellar evolution, and other processes that control globular cluster dynamics, with particular emphasis on pathways that may lead to the formation of blue stragglers.Comment: Chapter 10, in Ecology of Blue Straggler Stars, H.M.J. Boffin, G. Carraro & G. Beccari (Eds), Astrophysics and Space Science Library, Springe

A Problem Solving Environment for Modelling Stony Coral Morphogenesis

Apart from experimental and theoretical approaches, computer simulation is an important tool in testing hypotheses about stony coral growth. However, the construction and use of such simulation tools needs extensive computational skills and knowledge that is not available to most research biologists. Problem solving environments (PSEs) aim to provide a framework that hides implementation details and allows the user to formulate and analyse a problem in the language of the subject area. We have developed a prototypical PSE to study the morphogenesis of corals using a multi-model approach. In this paper we describe the design and implementation of this PSE, in which simulations of the coral's shape and its environment have been combined. We will discuss the relevance of our results for the future development of PSEs for studying biological growth and morphogenesis

Gravitational Dynamics of Large Stellar Systems

Internal dynamical evolution can drive stellar systems into states of high central density. For many star clusters and galactic nuclei, the time scale on which this occurs is significantly less than the age of the universe. As a result, such systems are expected to be sites of frequent interactions among stars, binary systems, and stellar remnants, making them efficient factories for the production of compact binaries, intermediate-mass black holes, and other interesting and eminently observable astrophysical exotica. We describe some elements of the competition among stellar dynamics, stellar evolution, and other mechanisms to control the dynamics of stellar systems, and discuss briefly the techniques by which these systems are modeled and studied. Particular emphasis is placed on pathways leading to massive black holes in present-day globular clusters and other potentially detectable sources of gravitational radiation.Comment: 21 pages, invited talk presented at the 18th International Conference on General Relativity and Gravitation (GRG18), Sydney, July 2007. To appear in Classical and Quantum Gravit

Preparing, exploring and comparing cancer simulation results within a large parameter space

The ACGT Oncosimulator is an integrated Grid-based system, under development within a 25-partner European-Japanese project, for patient-specific simulation of the response of a tumour and surrounding tissue to various forms of therapy. The validation of the simulation code is an activity requiring extensive human-driven visual investigation of the influence of each of the dozens of parameters to the code, and comparison of the simulation results against the known outcomes of past patient treatments. This activity therefore calls for a visualisation environment that supports users in working with an extremely large potential result space, and in rapidly setting up visualisations that highlight the differences between chosen subsets of available results. We describe the innovative features of the OncoRecipeSheet, an environment designed to meet these requirements

Validating the ACGT Oncosimulator with a Grid-Supported Visualisation Environment

The ACGT Oncosimulator is an integrated Grid-based system, under development within a 25-partner European-Japanese project, for patient-specific simulation of the response of a tumour and its surrounding tissue to various forms of therapy. The validation of the simulation code is an activity requiring extensive human-driven visual investigation of the influence of each of the dozens of parameters to the code, initially by comparing results from simulations carried out with different parameter values. This activity requires that users be supported in specifying simulation runs based on chosen parameter-value combinations, submitting the runs for execution on the Grid, then obtaining result visualisations that help in making the necessary comparisons. We report on our development and early use of the OncoRecipeSheet, an environment designed to meet these requirements