Highly Efficient and Scalable Software for the Simulation of Turbulent Flows in Complex Geometries

Harlacher, Daniel F.; Roller, Sabine; Hindenlang, Florian; Munz, Claus‐Dieter; Kraus, Tim; Fischer, Martin S.; Geurts, Koen; Meinke, Matthias; Klühspies, Tobias; Metsch, Volker; Benkert, Katharina

doi:10.1007/978-3-642-23869-7_22

Cited by 3 publications

(1 citation statement)

References 15 publications

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“…Concerning speed‐up, we remark that although the theoretic peak performances (roughly 50 GFlops (depending on the clock frequency) for the i7‐960 and 1345 GFlops for the GTX 480) allow a maximum speed‐up of about 27 for realistic, compute‐intensive (as opposed to memory‐intensive) applications such as the MI computation, the constraints the hardware imposes onto the programmer (e.g., coherence among concurrently running threads) only allow much lower speed‐ups . Our own experiments showed that even numerical NVIDIA code (namely the CUBLAS project), which can be regarded as highly optimized, runs at performances much lower than the theoretical peak performance: 765 GFlops.…”

Section: Algorithmic Evaluationmentioning

confidence: 99%

Using graphics processing units to investigate molecular coevolution

Waechter

Jaeger

Thuerck

et al. 2013

Concurrency and Computation

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SUMMARYWe present a massively parallel implementation of the computation of (co)evolutionary signals from biomolecular sequence alignments based on mutual information (MI) and a normalization procedure to neutral evolution. The MI is computed for two-point and three-point correlations within any multiple sequence alignment. We meet the high computational demand in the normalization procedure efficiently with an implementation on Graphics Processing Units (GPUs) using NVIDIA's CUDA framework. In particular, the normalization of the MI for three-point 'cliques' of amino acids or nucleotides requires large sampling numbers in the normalization, which we achieve by using GPUs. GPU computation serves as an enabling technology here insofar as MI normalization is also possible using traditional computational methods [1] or cluster computation, but only GPU computation makes MI normalization for sequence analysis feasible in a statistically sufficient sample and in acceptable time given affordable commodity hardware. We illustrate (i) the computational efficiency and (ii) the biological usefulness of two-point and three-point MI by applications to the well-known protein calmodulin and the variable surface glycoprotein (VSG) of Trypanosoma brucei, which are subject to involved evolutionary pressure. Here, we find striking coevolutionary patterns and distinct information on the molecular evolution of these molecules that question previous work that relied on non-efficient MI computations.

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Section: Algorithmic Evaluationmentioning

confidence: 99%

Using graphics processing units to investigate molecular coevolution

Waechter

Jaeger

Thuerck

et al. 2013

Concurrency and Computation

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Information-theoretic analysis of molecular (co)evolution using graphics processing units

Waechter

Jaeger

Weißgraeber

et al. 2012

Proceedings of the 3rd International Workshop on Emerging Computational Methods for the Life Sciences

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We present a massively-parallel implementation of the computation of (co)evolutionary signals from biomolecular sequence alignments based on mutual information (MI) and a normalization procedure to neutral evolution. The MI is computed for two-and three-point correlations within any multiple-sequence alignment. The high computational demand in the normalization procedure is efficiently met by an implementation on Graphics Processing Units (GPUs) using NVIDIA's CUDA framework. GPU computation serves as an enabling technology here insofar as MI normalization is also possible using traditional computational methods [11] but only GPU computation makes MI normalization for sequence analysis feasible in a statistically sufficient sample and in acceptable time. In particular, the normalization of the MI for three-point 'cliques' of amino acids or nucleotides requires large sampling numbers in the normalization, that can only be achieved using GPUs. We illustrate a) the computational efficiency and b) the biological usefulness of two-and three-point MI by an application to the well-known protein calmodulin. Here, we find striking coevolutionary patterns and distinct information on the molecular evolution of this molecule.

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Direct Noise Simulation of Near Field Noise during a Gas Injection Process with a Discontinuous Galerkin Approach

Kraus

Hindenlang

Harlacher

et al. 2012

18th AIAA/CEAS Aeroacoustics Conference (33rd AIAA Aeroacoustics Conference)

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In this paper, we present results on the noise radiated by a supersonic gas jet through a gas injection nozzle which is commonly used in cars powered by compressed natural gas. Direct aeroacoustic simulation results, provided by a discontinuous Galerkin solver for the unsteady compressible Navier Stokes equations, are presented. Due to its local formulation with high order accuracy and low dissipation and dispersion, it is well suited for both flow resolution and wave propagation. The discontinuous Galerkin scheme preserves these properties even on unstructured hybrid grids, allowing to mesh the complex threedimensional geometries. The scheme is fully parallelized and simulations are run on 2048 cores. We show that the sound radiation can be adequately predicted and that sound pressure level spectra are in good agreement with experimental data.

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Highly Efficient and Scalable Software for the Simulation of Turbulent Flows in Complex Geometries

Cited by 3 publications

References 15 publications

Using graphics processing units to investigate molecular coevolution

Using graphics processing units to investigate molecular coevolution

Information-theoretic analysis of molecular (co)evolution using graphics processing units

Direct Noise Simulation of Near Field Noise during a Gas Injection Process with a Discontinuous Galerkin Approach

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