Jean-Jacques Roux

LBM based flow simulation using GPU computing processor

Graphics Processing Units (GPUs), originally developed for computer games, now provide computational power for scientific applications. In this paper, we develop a general purpose Lattice Boltzmann code that runs entirely on a single GPU. The results show that: (1) simple precision floating point arithmetic is sufficient for LBM computation in comparison to double precision; (2) the implementation of LBM on GPUs allows us to achieve up to about one billion lattice update per second using single precision floating point; (3) GPUs provide an inexpensive alternative to large clusters for fluid dynamics prediction.

A new approach to the lattice Boltzmann method for graphics processing units

Emerging many-core processors, like CUDA capable nVidia GPUs, are promising platforms for regular parallel algorithms such as the Lattice Boltzmann Method (LBM). Since the global memory for graphic devices shows high latency and LBM is data intensive, the memory access pattern is an important issue for achieving good performances. Whenever possible, global memory loads and stores should be coalescent and aligned, but the propagation phase in LBM can lead to frequent misaligned memory accesses. Most previous CUDA implementations of 3D LBM addressed this problem by using low latency on chip shared memory. Instead of this, our CUDA implementation of LBM follows carefully chosen data transfer schemes in global memory. For the 3D lid-driven cavity test case, we obtained up to 86% of the global memory maximal throughput on nVidias GT200. We show that as a consequence highly efficient implementations of LBM on GPUs are possible, even for complex models.

Multi-GPU implementation of the lattice Boltzmann method

The lattice Boltzmann method (LBM) is an increasingly popular approach for solving fluid flows in a wide range of applications. The LBM yields regular, data-parallel computations; hence, it is especially well fitted to massively parallel hardware such as graphics processing units (GPU). Up to now, though, single-GPU implementations of the LBM are of moderate practical interest since the on-board memory of GPU-based computing devices is too scarce for large scale simulations. In this paper, we present a multi-GPU LBM solver based on the well-known D3Q19 MRT model. Using appropriate hardware, we managed to run our program on six Tesla C1060 computing devices in parallel. We observed up to 2.15x10^9 node updates per second for the lid-driven cubic cavity test case. It is worth mentioning that such a performance is comparable to the one obtained with large high performance clusters or massively parallel supercomputers. Our solver enabled us to perform high resolution simulations for large Reynolds numbers without facing numerical instabilities. Though, we could observe symmetry breaking effects for long-extended simulations of unsteady flows. We describe the different levels of precision we implemented, showing that these effects are due to round off errors, and we discuss their relative impact on performance.

Scalable lattice Boltzmann solvers for CUDA GPU clusters

The lattice Boltzmann method (LBM) is an innovative and promising approach in computational fluid dynamics. From an algorithmic standpoint it reduces to a regular data parallel procedure and is therefore well-suited to high performance computations. Numerous works report efficient implementations of the LBM for the GPU, but very few mention multi-GPU versions and even fewer GPU cluster implementations. Yet, to be of practical interest, GPU LBM solvers need to be able to perform large scale simulations. In the present contribution, we describe an efficient LBM implementation for CUDA GPU clusters. Our solver consists of a set of MPI communication routines and a CUDA kernel specifically designed to handle three-dimensional partitioning of the computation domain. Performance measurement were carried out on a small cluster. We show that the results are satisfying, both in terms of data throughput and parallelisation efficiency.

The TheLMA project: Multi-GPU implementation of the lattice Boltzmann method

In this paper, we describe the implementation of a multi-graphical processing unit (GPU) fluid flow solver based on the lattice Boltzmann method (LBM). The LBM is a novel approach in computational fluid dynamics, with numerous interesting features from a computational, numerical, and physical standpoint. Our program is based on CUDA and uses POSIX threads to manage multiple computation devices. Using recently released hardware, our solver may therefore run eight GPUs in parallel, which allows us to perform simulations at a rather large scale. Performance and scalability are excellent, the speedup over sequential implementations being at least of two orders of magnitude. In addition, we discuss tiling and communication issues for present and forthcoming implementations.

Three-dimensional numerical modeling of vertical ground heat exchangers: Domain decomposition and state model reduction

Modeling of vertical ground heat exchangers is relatively complex because of the three-dimensional transient nature of the problem inside the borehole and in the surrounding ground. Furthermore, the system is characterized by various time scales with rapid changes inside the borehole and slow variations of ground temperature far away from the borehole. Most existing numerical models require important computational resources to adequately represent the short time-scale heat transfer occurring in the immediate vicinity of the borehole, which warrant their use for annual energy simulations. In this article, a three-dimensional reduced model (3D-RM), based on domain decomposition and state model reduction techniques, is proposed to reduce computation time and computer memory. Domain decomposition is used to sub-structure the domain and to vary the time-step values in each sub-domain, and state model reduction is applied to each resulting sub-zone. A comparison with a complete three-dimensional dynamic model indicates that the proposed 3D-RM model reduces computational time by a factor of about 30 without loss of accuracy. A comparison with experimental results shows that the relatively fast transients occurring in the borehole are well predicted by the 3D-RM model not only for the outlet fluid temperature but also for the tube wall temperatures at different depths.

Global memory access modelling for efficient implementation of the lattice Boltzmann method on graphics processing units

In this work, we investigate the global memory access mechanism on recent GPUs. For the purpose of this study, we created specific benchmark programs, which allowed us to explore the scheduling of global memory transactions. Thus, we formulate a model capable of estimating the execution time for a large class of applications. Our main goal is to facilitate optimisation of regular data-parallel applications on GPUs. As an example, we finally describe our CUDA implementations of LBM flow solvers on which our model was able to estimate performance with less than 5% relative error.

Towards aeraulic simulations at urban scale using the lattice Boltzmann method

The lattice Boltzmann method (LBM) is an innovative approach in computational fluid dynamics (CFD). Due to the underlying lattice structure, the LBM is inherently parallel and therefore well suited for high performance computing. Its application to outdoor aeraulic studies is promising, e.g. applied on complex urban configurations, as an alternative approach to the commonplace Reynolds-averaged Navier–Stokes and large eddy simulation methods based on the Navier–Stokes equations. Emerging many-core devices, such as graphic processing units (GPUs), nowadays make possible to run very large scale simulations on rather inexpensive hardware. In this paper, we present simulation results obtained using our multi-GPU LBM solver. For validation purpose, we study the flow around a wall-mounted cube and show agreement with previously published experimental results. Furthermore, we discuss larger scale flow simulations involving nine cubes which demonstrate the practicability of CFD simulations in building external aeraulics.

High-performance implementations and large-scale validation of the link-wise artificial compressibility method

The link-wise artificial compressibility method (LW-ACM) is a recent formulation of the artificial compressibility method for solving the incompressible Navier-Stokes equations. Two implementations of the LW-ACM in three dimensions on CUDA enabled GPUs are described. The first one is a modified version of a state-of-the-art CUDA implementation of the lattice Boltzmann method (LBM), showing that an existing GPU LBM solver might easily be adapted to LW-ACM. The second one follows a novel approach, which leads to a performance increase of up to 1.8x compared to the LBM implementation considered here, while reducing the memory requirements by a factor of 5.25. Large-scale simulations of the lid-driven cubic cavity at Reynolds number Re=2000 were performed for both LW-ACM and LBM. Comparison of the simulation results against spectral elements reference data shows that LW-ACM performs almost as well as multiple-relaxation-time LBM in terms of accuracy.

Influence of Diffuse Damage on the Water Vapour Permeability of Fibre-Reinforced Mortar

The study of moisture transfer inside building materials is an important issue in building physics. The hygric characterization of such materials has become a common practice for the estimation of the hygrothermal performance of buildings. However, their aging caused by mechanical loading and environmental factors inevitably affects their permeability to moisture ingress, and the knowledge of how this permeability is affected by damage and cracks is still incomplete. The effects of diffuse damage caused by mechanical loading on the water vapour permeability of fibre-reinforced mortar were studied. A full experimental setup is presented including observation of the porous structure, mechanical, and hygric characterization. Uniaxial tensile loading was applied on prismatic samples while their damage level was measured. Then, the moisture content of damaged and undamaged samples was monitored during variations of ambient relative humidity. Two numerical methods are presented and used for the comparison of the water vapour permeability of multiple samples presenting various levels of damage. By this methodology, diffuse damage caused by mechanical loading is shown to have an impact on the water vapour transfer inside the material.