1,712 research outputs found
Large-scale lattice Boltzmann simulations of complex fluids: advances through the advent of computational grids
During the last two years the RealityGrid project has allowed us to be one of
the few scientific groups involved in the development of computational grids.
Since smoothly working production grids are not yet available, we have been
able to substantially influence the direction of software development and grid
deployment within the project. In this paper we review our results from large
scale three-dimensional lattice Boltzmann simulations performed over the last
two years. We describe how the proactive use of computational steering and
advanced job migration and visualization techniques enabled us to do our
scientific work more efficiently. The projects reported on in this paper are
studies of complex fluid flows under shear or in porous media, as well as
large-scale parameter searches, and studies of the self-organisation of liquid
cubic mesophases.
Movies are available at
http://www.ica1.uni-stuttgart.de/~jens/pub/05/05-PhilTransReview.htmlComment: 18 pages, 9 figures, 4 movies available, accepted for publication in
Phil. Trans. R. Soc. London Series
Load Balancing Regular Meshes on SMPS with MPI
Domain decomposition for regular meshes on parallel computers has
traditionally been performed by attempting to exactly partition the work among the available processors (now cores). However, these
strategies often do not consider the inherent system noise which can hinder MPI application scalability to emerging peta-scale machines
with 10000+ nodes. In this work, we suggest a solution that uses a tunable hybrid static/dynamic scheduling strategy that can be incorporated into current MPI implementations of mesh codes. By applying this strategy to a 3D jacobi algorithm, we achieve performance gains
of at least 16% for 64 SMP nodes
Steering in computational science: mesoscale modelling and simulation
This paper outlines the benefits of computational steering for high
performance computing applications. Lattice-Boltzmann mesoscale fluid
simulations of binary and ternary amphiphilic fluids in two and three
dimensions are used to illustrate the substantial improvements which
computational steering offers in terms of resource efficiency and time to
discover new physics. We discuss details of our current steering
implementations and describe their future outlook with the advent of
computational grids.Comment: 40 pages, 11 figures. Accepted for publication in Contemporary
Physic
Mixing multi-core CPUs and GPUs for scientific simulation software
Recent technological and economic developments have led to widespread availability of
multi-core CPUs and specialist accelerator processors such as graphical processing units
(GPUs). The accelerated computational performance possible from these devices can be very
high for some applications paradigms. Software languages and systems such as NVIDIA's
CUDA and Khronos consortium's open compute language (OpenCL) support a number of
individual parallel application programming paradigms. To scale up the performance of some
complex systems simulations, a hybrid of multi-core CPUs for coarse-grained parallelism and
very many core GPUs for data parallelism is necessary. We describe our use of hybrid applica-
tions using threading approaches and multi-core CPUs to control independent GPU devices.
We present speed-up data and discuss multi-threading software issues for the applications
level programmer and o er some suggested areas for language development and integration
between coarse-grained and ne-grained multi-thread systems. We discuss results from three
common simulation algorithmic areas including: partial di erential equations; graph cluster
metric calculations and random number generation. We report on programming experiences
and selected performance for these algorithms on: single and multiple GPUs; multi-core CPUs;
a CellBE; and using OpenCL. We discuss programmer usability issues and the outlook and
trends in multi-core programming for scienti c applications developers
Recommended from our members
Accelerating solid-fluid interaction using Lattice-Boltzmann and Immersed Boundary coupled simulations on heterogeneous platforms
We propose a numerical approach based on the Lattice-Boltzmann (LBM) and Immersed Boundary (IB) methods to tackle the problem of the interaction of solids with an incompressible fluid flow. The proposed method uses a Cartesian uniform grid that incorporates both the fluid and the solid domain. This is a very optimum and novel method to solve this problem and is a growing research topic in Computational Fluid Dynamics. We explain in detail the parallelization of the whole method on both GPUs and an heterogeneous GPU-Multicore platform and describe different optimizations, focusing on memory management and CPU-GPU communication. Our performance evaluation consists of a series of numerical experiments that simulate situations of industrial and research interest. Based on these tests, we have shown that the baseline LBM implementation achieves satisfactory results on GPUs. Unfortunately, when coupling LBM and IB methods on GPUs, the overheads of IB degrade the overall performance. As an alternative we have explored an heterogeneous implementation that is able to hide such overheads and allows us to exploit both Multicore and GPU resources in a cooperative way
Optimal Renormalization Group Transformation from Information Theory
Recently a novel real-space RG algorithm was introduced, identifying the
relevant degrees of freedom of a system by maximizing an information-theoretic
quantity, the real-space mutual information (RSMI), with machine learning
methods. Motivated by this, we investigate the information theoretic properties
of coarse-graining procedures, for both translationally invariant and
disordered systems. We prove that a perfect RSMI coarse-graining does not
increase the range of interactions in the renormalized Hamiltonian, and, for
disordered systems, suppresses generation of correlations in the renormalized
disorder distribution, being in this sense optimal. We empirically verify decay
of those measures of complexity, as a function of information retained by the
RG, on the examples of arbitrary coarse-grainings of the clean and random Ising
chain. The results establish a direct and quantifiable connection between
properties of RG viewed as a compression scheme, and those of physical objects
i.e. Hamiltonians and disorder distributions. We also study the effect of
constraints on the number and type of coarse-grained degrees of freedom on a
generic RG procedure.Comment: Updated manuscript with new results on disordered system
High-order implicit palindromic discontinuous Galerkin method for kinetic-relaxation approximation
We construct a high order discontinuous Galerkin method for solving general
hyperbolic systems of conservation laws. The method is CFL-less, matrix-free,
has the complexity of an explicit scheme and can be of arbitrary order in space
and time. The construction is based on: (a) the representation of the system of
conservation laws by a kinetic vectorial representation with a stiff relaxation
term; (b) a matrix-free, CFL-less implicit discontinuous Galerkin transport
solver; and (c) a stiffly accurate composition method for time integration. The
method is validated on several one-dimensional test cases. It is then applied
on two-dimensional and three-dimensional test cases: flow past a cylinder,
magnetohydrodynamics and multifluid sedimentation
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