In the last 30 days

• Open/close Simplifying the parallelization of scientific codes by a function-centric approach in Python

  Jon K Nilsen et al 2010 Comput. Sci. Disc. 3 015003 Tag this article

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  The purpose of this paper is to show how existing scientific software can be parallelized using a separate thin layer of Python code where all parallelization-specific tasks are implemented. We provide specific examples of such a Python code layer, which can act as templates for parallelizing a wide set of serial scientific codes. The use of Python for parallelization is motivated by the fact that the language is well suited for reusing existing serial codes programmed in other languages. The extreme flexibility of Python with regard to handling functions makes it very easy to wrap up decomposed computational tasks of a serial scientific application as Python functions. Many parallelization-specific components can be implemented as generic Python functions, which may take as input those wrapped functions that perform concrete computational tasks. The overall programming effort needed by this parallelization approach is limited, and the resulting parallel Python scripts have a compact and clean structure. The usefulness of the parallelization approach is exemplified by three different classes of application in natural and social sciences.

• Open/close Multiscale methods in turbulent combustion: strategies and computational challenges

  Tarek Echekki 2009 Comput. Sci. Disc. 2 013001 Tag this article

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  A principal challenge in modeling turbulent combustion flows is associated with their complex, multiscale nature. Traditional paradigms in the modeling of these flows have attempted to address this nature through different strategies, including exploiting the separation of turbulence and combustion scales and a reduced description of the composition space. The resulting moment-based methods often yield reasonable predictions of flow and reactive scalars' statistics under certain conditions. However, these methods must constantly evolve to address combustion at different regimes, modes or with dominant chemistries. In recent years, alternative multiscale strategies have emerged, which although in part inspired by the traditional approaches, also draw upon basic tools from computational science, applied mathematics and the increasing availability of powerful computational resources. This review presents a general overview of different strategies adopted for multiscale solutions of turbulent combustion flows. Within these strategies, some specific models are discussed or outlined to illustrate their capabilities and underlying assumptions. These strategies may be classified under four different classes, including (i) closure models for atomistic processes, (ii) multigrid and multiresolution strategies, (iii) flame-embedding strategies and (iv) hybrid large-eddy simulation–low-dimensional strategies. A combination of these strategies and models can potentially represent a robust alternative strategy to moment-based models; but a significant challenge remains in the development of computational frameworks for these approaches as well as their underlying theories.

• Open/close Implementation of accelerated molecular dynamics in NAMD

  Y Wang et al 2011 Comput. Sci. Disc. 4 015002 Tag this article

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  Accelerated molecular dynamics (aMD) is an enhanced sampling method that improves the conformational space sampling by reducing energy barriers separating different states of a system. Here, we present the implementation of aMD in the parallel simulation program NAMD. We show that aMD simulations performed with NAMD have only a small overhead compared with classical MD simulations. Through example applications to the alanine dipeptide, we discuss the choice of acceleration parameters, the interpretation of aMD results, as well as the advantages and limitations of the aMD method.

• Open/close Terascale direct numerical simulations of turbulent combustion using S3D

  J H Chen et al 2009 Comput. Sci. Disc. 2 015001 Tag this article

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  Computational science is paramount to the understanding of underlying processes in internal combustion engines of the future that will utilize non-petroleum-based alternative fuels, including carbon-neutral biofuels, and burn in new combustion regimes that will attain high efficiency while minimizing emissions of particulates and nitrogen oxides. Next-generation engines will likely operate at higher pressures, with greater amounts of dilution and utilize alternative fuels that exhibit a wide range of chemical and physical properties. Therefore, there is a significant role for high-fidelity simulations, direct numerical simulations (DNS), specifically designed to capture key turbulence-chemistry interactions in these relatively uncharted combustion regimes, and in particular, that can discriminate the effects of differences in fuel properties. In DNS, all of the relevant turbulence and flame scales are resolved numerically using high-order accurate numerical algorithms. As a consequence terascale DNS are computationally intensive, require massive amounts of computing power and generate tens of terabytes of data. Recent results from terascale DNS of turbulent flames are presented here, illustrating its role in elucidating flame stabilization mechanisms in a lifted turbulent hydrogen/air jet flame in a hot air coflow, and the flame structure of a fuel-lean turbulent premixed jet flame. Computing at this scale requires close collaborations between computer and combustion scientists to provide optimized scaleable algorithms and software for terascale simulations, efficient collective parallel I/O, tools for volume visualization of multiscale, multivariate data and automating the combustion workflow. The enabling computer science, applied to combustion science, is also required in many other terascale physics and engineering simulations. In particular, performance monitoring is used to identify the performance of key kernels in the DNS code, S3D and especially memory intensive loops in the code. Through the careful application of loop transformations, data reuse in cache is exploited thereby reducing memory bandwidth needs, and hence, improving S3D's nodal performance. To enhance collective parallel I/O in S3D, an MPI-I/O caching design is used to construct a two-stage write-behind method for improving the performance of write-only operations. The simulations generate tens of terabytes of data requiring analysis. Interactive exploration of the simulation data is enabled by multivariate time-varying volume visualization. The visualization highlights spatial and temporal correlations between multiple reactive scalar fields using an intuitive user interface based on parallel coordinates and time histogram. Finally, an automated combustion workflow is designed using Kepler to manage large-scale data movement, data morphing, and archival and to provide a graphical display of run-time diagnostics.

• Open/close An anisotropic preconditioning for the Wilson fermion matrix on the lattice

  Bálint Joó et al 2010 Comput. Sci. Disc. 3 015001 Tag this article

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  A preconditioning for the Wilson fermion matrix on the lattice is defined, which is particularly suited to the case when the temporal lattice spacing is much smaller than the spatial one. Details on the implementation of the scheme are given. The method is tested in numerical studies of quantum chromodynamics on anisotropic lattices.

• Open/close High performance parallel computing of flows in complex geometries: II. Applications

  N Gourdain et al 2009 Comput. Sci. Disc. 2 015004 Tag this article

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  Present regulations in terms of pollutant emissions, noise and economical constraints, require new approaches and designs in the fields of energy supply and transportation. It is now well established that the next breakthrough will come from a better understanding of unsteady flow effects and by considering the entire system and not only isolated components. However, these aspects are still not well taken into account by the numerical approaches or understood whatever the design stage considered. The main challenge is essentially due to the computational requirements inferred by such complex systems if it is to be simulated by use of supercomputers. This paper shows how new challenges can be addressed by using parallel computing platforms for distinct elements of a more complex systems as encountered in aeronautical applications. Based on numerical simulations performed with modern aerodynamic and reactive flow solvers, this work underlines the interest of high-performance computing for solving flow in complex industrial configurations such as aircrafts, combustion chambers and turbomachines. Performance indicators related to parallel computing efficiency are presented, showing that establishing fair criterions is a difficult task for complex industrial applications. Examples of numerical simulations performed in industrial systems are also described with a particular interest for the computational time and the potential design improvements obtained with high-fidelity and multi-physics computing methods. These simulations use either unsteady Reynolds-averaged Navier–Stokes methods or large eddy simulation and deal with turbulent unsteady flows, such as coupled flow phenomena (thermo-acoustic instabilities, buffet, etc). Some examples of the difficulties with grid generation and data analysis are also presented when dealing with these complex industrial applications.

• Open/close Deterministic point inclusion methods for computational applications with complex geometry

  Ahmed Khamayseh and Andrew Kuprat 2008 Comput. Sci. Disc. 1 015004 Tag this article

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  A fundamental problem in computation is finding practical and efficient algorithms for determining if a query point is contained within a model of a three-dimensional solid. The solid is modeled using a general boundary representation that can contain polygonal elements and/or parametric patches. We have developed two such algorithms: the first is based on a global closest feature query, and the second is based on a local intersection query. Both algorithms work for two- and three-dimensional objects. This paper presents both algorithms, as well as the spatial data structures and queries required for efficient implementation of the algorithms. Applications for these algorithms include computational geometry, mesh generation, particle simulation, multiphysics coupling, and computer graphics. These methods are deterministic in that they do not involve random perturbations of diagnostic rays cast from the query point in order to avoid 'unclean' or 'singular' intersections of the rays with the geometry. Avoiding the necessity of such random perturbations will become increasingly important as geometries become more convoluted and complex.

• Open/close The RAGE radiation-hydrodynamic code

  Michael Gittings et al 2008 Comput. Sci. Disc. 1 015005 Tag this article

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  We describe RAGE, the 'radiation adaptive grid Eulerian' radiation-hydrodynamics code, including its data structures, its parallelization strategy and performance, its hydrodynamic algorithm(s), its (gray) radiation diffusion algorithm, and some of the considerable amount of verification and validation efforts. The hydrodynamics is a basic Godunov solver, to which we have made significant improvements to increase the advection algorithm's robustness and to converge stiffnesses in the equation of state. Similarly, the radiation transport is a basic gray diffusion, but our treatment of the radiation–material coupling, wherein we converge nonlinearities in a novel manner to allow larger timesteps and more robust behavior, can be applied to any multi-group transport algorithm.

• Open/close Virtual materials design using databases of calculated materials properties

  T R Munter et al 2009 Comput. Sci. Disc. 2 015006 Tag this article

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  Materials design is most commonly carried out by experimental trial and error techniques. Current trends indicate that the increased complexity of newly developed materials, the exponential growth of the available computational power, and the constantly improving algorithms for solving the electronic structure problem, will continue to increase the relative importance of computational methods in the design of new materials. One possibility for utilizing electronic structure theory in the design of new materials is to create large databases of materials properties, and subsequently screen these for new potential candidates satisfying given design criteria. We utilize a database of more than 81 000 electronic structure calculations. This alloy database is combined with other published materials properties to form the foundation of a virtual materials design framework (VMDF). The VMDF offers a flexible collection of materials databases, filters, analysis tools and visualization methods, which are particularly useful in the design of new functional materials and surface structures. The applicability of the VMDF is illustrated by two examples. One is the determination of the Pareto-optimal set of binary alloy methanation catalysts with respect to catalytic activity and alloy stability; the other is the search for new alloy mercury absorbers.

• Open/close High-performance gravitational N-body simulations on a planet-wide-distributed supercomputer

  Derek Groen et al 2011 Comput. Sci. Disc. 4 015001 Tag this article

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  We report on the performance of our cold dark matter cosmological N-body simulation that was carried out concurrently using supercomputers across the globe. We ran simulations on 60–750 cores distributed over a variety of supercomputers in Amsterdam (The Netherlands, Europe), in Tokyo (Japan, Asia), Edinburgh (UK, Europe) and Espoo (Finland, Europe). Regardless of the network latency of 0.32 s and the communication over 30 000 km of optical network cable, we are able to achieve ~87% of the performance compared to an equal number of cores on a single supercomputer. We argue that using widely distributed supercomputers in order to acquire more compute power is technically feasible and that the largest obstacle is introduced by local scheduling and reservation policies.