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Your search keyword '"Mantovani, Filippo"' showing total 5 results
Start Over Author "Mantovani, Filippo" Topic lattice boltzmann methods
5 results on '"Mantovani, Filippo"'

1. A Multi-GPU Implementation of a D2Q37 Lattice Boltzmann Code

Author

Biferale, Luca, Mantovani, Filippo, Pivanti, Marcello, Pozzati, Fabio, Sbragaglia, Mauro, Scagliarini, Andrea, Schifano, Sebastiano Fabio, Toschi, Federico, Tripiccione, Raffaele, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Wyrzykowski, Roman, editor, Dongarra, Jack, editor, Karczewski, Konrad, editor, and Waśniewski, Jerzy, editor

Published
2012
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2. A multi-GPU implementation of a D2Q37 lattice Boltzmann code

Author

Luca Biferale, Mantovani, Filippo, Pivanti, Marcello, Pozzati, Fabio, Sbragaglia, Mauro, Scagliarini, Andrea, Schifano, Sebastiano Fabio, Toschi, Federico, Tripiccione, Raffaele, Wyrzykowski, R., Dongarra, J., Karczewski, K., Wasniewski, J., Scientific Computing, Fluids and Flows, and Computational Multiscale Transport Phenomena (Toschi)

Subjects
GP-GPUs computing, Computer science, Computational fluid-dynamics, Lattice Boltzmann methods, Computer Science (all), Theoretical Computer Science, Parallel computing, Settore FIS/02 - Fisica Teorica, Modelli e Metodi Matematici, NO, Computational science, Computer Science::Performance, Computer Science::Graphics, Code (cryptography), Cluster (physics), Computer Science::Mathematical Software, Multi gpu, ComputingMethodologies_COMPUTERGRAPHICS
Abstract

We describe a parallel implementation of a compressible Lattice Boltzmann code on a multi-GPU cluster based on Nvidia Fermi processors. We analyze how to optimize the algorithm for GP-GPU architectures, describe the implementation choices that we have adopted and compare our performance results with an implementation optimized for latest generation multi-core CPUs. Our program runs at ˜¿30% of the double-precision peak performance of one GPU and shows almost linear scaling when run on the multi-GPU cluster. Keywords: Computational fluid-dynamics – Lattice Boltzmann methods – GP-GPUs computing

Published
2012

3. Implementation and optimization of a thermal Lattice Boltzmann algorithm on a multi-GPU cluster.

Author

Bertazzo, Alessio, Mantovani, Filippo, Pivanti, Marcello, Pozzati, Fabio, Schifano, Sebastiano F., and Tripiccione, Raffaele

Abstract

Lattice Boltzmann (LB) methods are widely used today to describe the dynamics of fluids. Key advantages of this approach are the relative ease with which complex physics behavior, e.g. associated to multi-phase flows or irregular boundary conditions can be modeled, and - from a computational perspective - the large degree of available parallelism, that can be easily exploited on massively parallel systems. The advent of multi-core and many-core processors, including General Purpose Graphics Processing Unit (GP-GPU), has pushed the quest for parallelization also at the intra-processor level. From this point of view, LB methods may strongly benefit from these new architectures. In this paper we describe the implementation and optimization of a recently proposed thermal LB model - the so called D2Q37 model - on multi-GPU systems. We describe in details the optimization techniques that we have used at both the intra-processor and inter-processor level, present performance and scaling figures and analyze bottlenecks associated to this implementation. [ABSTRACT FROM PUBLISHER]

Published
2012
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4. Optimization of Multi-Phase Compressible Lattice Boltzmann Codes on Massively Parallel Multi-Core Systems.

Author

Biferale, Luca, Mantovani, Filippo, Pivanti, Marcello, Pozzati, Fabio, Sbragaglia, Mauro, Scagliarini, Andrea, Schifano, Sebastiano Fabio, Toschi, Federico, and Tripiccione, Raffaele

Subjects
COMPUTATIONAL fluid dynamics, MULTIPHASE flow, LATTICE Boltzmann methods, MATHEMATICAL optimization, PARALLEL computers, MULTICORE processors, INTEL microprocessors, COMPUTER architecture
Abstract

Abstract: We develop a Lattice Boltzmann code for computational fluid-dynamics and optimize it for massively parallel systems based on multi-core processors. Our code describes 2D multi-phase compressible flows. We analyze the performance bottlenecks that we find as we gradually expose a larger fraction of the available parallelism, and derive appropriate solutions. We obtain a sustained performance for this ready-for-physics code that is a large fraction of peak. Our results can be easily applied to most present (or planned) HPC architectures, based on latest generation multi-core Intel processor architectures. [Copyright &y& Elsevier]

Published
2011
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5. An optimized D2Q37 Lattice Boltzmann code on GP-GPUs.

Author

Biferale, Luca, Mantovani, Filippo, Pivanti, Marcello, Pozzati, Fabio, Sbragaglia, Mauro, Scagliarini, Andrea, Schifano, Sebastiano Fabio, Toschi, Federico, and Tripiccione, Raffaele

Subjects
*MATHEMATICAL optimization, *LATTICE Boltzmann methods, *GRAPHICS processing units, *FERMI level, *ALGORITHMS, *COMPARATIVE studies
Abstract

Abstract: We describe the implementation of a thermal compressible Lattice Boltzmann algorithm on an NVIDIA Tesla C2050 system based on the Fermi GP-GPU. We consider two different versions, including and not including reactive effects. We describe the overall organization of the algorithm and give details on its implementations. Efficiency ranges from 25% to 31% of the double precision peak performance of the GP-GPU. We compare our results with a different implementation of the same algorithm, developed and optimized for many-core Intel Westmere CPUs. [Copyright &y& Elsevier]

Published
2013
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