Towards accelerating smoothed particle hydrodynamics simulations for free-surface flows on multi-GPU clusters

Starting from the single graphics processing unit (GPU) version of the Smoothed Particle Hydrodynamics (SPH) code DualSPHysics, a multi-GPU SPH program is developed for free-surface flows. The approach is based on a spatial decomposition technique, whereby different portions (sub-domains) of the physical system under study are assigned to different GPUs. Communication between devices is achieved with the use of Message Passing Interface (MPI) application programming interface (API) routines. The use of the sorting algorithm radix sort for inter-GPU particle migration and sub-domain “halo” building (which enables interaction between SPH particles of different sub-domains) is described in detail. With the resulting scheme it is possible, on the one hand, to carry out simulations that could also be performed on a single GPU, but they can now be performed even faster than on one of these devices alone. On the other hand, accelerated simulations can be performed with up to 32 million particles on the current architecture, which is beyond the limitations of a single GPU due to memory constraints. A study of weak and strong scaling behaviour, speedups and efficiency of the resulting program is presented including an investigation to elucidate the computational bottlenecks. Last, possibilities for reduction of the effects of overhead on computational efficiency in future versions of our scheme are discussed.Xunta de GaliciaEngineering and Physical Sciences Research Council (EPSRC)Research Councils UK (RCUK

Astrophysical data mining with GPU. A case study: Genetic classification of globular clusters

We present a multi-purpose genetic algorithm, designed and implemented with GPGPU/CUDA parallel computing technology. The model was derived from our CPU serial implementation, named GAME (Genetic Algorithm Model Experiment). It was successfully tested and validated on the detection of candidate Globular Clusters in deep, wide-field, single band HST images. The GPU version of GAME will be made available to the community by integrating it into the web application DAMEWARE (DAta Mining Web Application REsource, http://dame.dsf.unina.it/beta_info.html), a public data mining service specialized on massive astrophysical data. Since genetic algorithms are inherently parallel, the GPGPU computing paradigm leads to a speedup of a factor of 200× in the training phase with respect to the CPU based version

Composite modelling of subaerial landslide-tsunamis in different water body geometries and novel insight into slide and wave kinematics

This article addresses subaerial landslide-tsunamis with a composite (experimental-numerical) modelling approach. A shortcoming of generic empirical equations used for hazard assessment is that they are commonly based on the two idealised water body geometries of a wave channel (2D) or a wave basin (3D). A recent systematic comparison of 2D and 3D physical block model tests revealed wave amplitude differences of up to a factor of 17. The present article investigates two of these recently presented 2D-3D test pairs in detail, involving a solitary-like wave (scenario 1) and Stokes-like waves (scenario 2). Results discussed include slide and water particle kinematics and novel pressure measurements on the slide front. Instantaneous slide-water interaction power graphs are derived and potential and kinetic wave energies are analysed. Solitary wave theory is found most appropriate to describe the wave kinematics associated with scenario 1, whereas Stokes theory accurately describes the tsunami in scenario 2. The data of both scenarios are further used to calibrate the smoothed particle hydrodynamics (SPH) code DualSPHysics v3.1, which includes a discrete element method (DEM)-based model to simulate the slide-ramp interaction. Five intermediate geometries, lying between the ideal 2D and 3D cases, are then investigated purely numerically. For a “channel” geometry with a diverging side wall angle of 7.5°, the wave amplitudes along the slide axes were found to lie approximately halfway between the values observed in 2D and 3D. At 45°, the amplitudes are practically identical to those in 3D. The study finally discusses the implications of the findings for engineering applications and illustrates the potential and current limitations of DualSPHysics for landslide-tsunami hazard assessment

DualSPHysics: from fluid dynamics to multiphysics problems

DualSPHysics is a weakly compressible smoothed particle hydrodynamics (SPH) Navier–Stokes solver initially conceived to deal with coastal engineering problems, especially those related to wave impact with coastal structures. Since the first release back in 2011, DualSPHysics has shown to be robust and accurate for simulating extreme wave events along with a continuous improvement in efficiency thanks to the exploitation of hardware such as graphics processing units for scientific computing or the coupling with wave propagating models such as SWASH and OceanWave3D. Numerous additional functionalities have also been included in the DualSPHysics package over the last few years which allow the simulation of fluid-driven objects. The use of the discrete element method has allowed the solver to simulate the interaction among different bodies (sliding rocks, for example), which provides a unique tool to analyse debris flows. In addition, the recent coupling with other solvers like Project Chrono or MoorDyn has been a milestone in the development of the solver. Project Chrono allows the simulation of articulated structures with joints, hinges, sliders and springs and MoorDyn allows simulating moored structures. Both functionalities make DualSPHysics especially suited for the simulation of offshore energy harvesting devices. Lately, the present state of maturity of the solver goes beyond single-phase simulations, allowing multi-phase simulations with gas–liquid and a combination of Newtonian and non-Newtonian models expanding further the capabilities and range of applications for the DualSPHysics solver. These advances and functionalities make DualSPHysics an advanced meshless solver with emphasis on free-surface flow modelling

Accelerating Scientific Computing Models Using GPU Processing

GPGPUs offer significant computational power for programmers to leverage. This computational power is especially useful when utilized for accelerating scientific models. This thesis analyzes the utilization of GPGPU programming to accelerate scientific computing models. First the construction of hardware for visualization and computation of scientific models is discussed. Several factors in the construction of the machines focus on the performance impacts related to scientific modeling. Image processing is an embarrassingly parallel problem well suited for GPGPU acceleration. An image processing library was developed to show the processes of recognizing embarrassingly parallel problems and serves as an excellent example of converting from a serial CPU implementation to a GPU accelerated implementation. Genetic algorithms are biologically inspired heuristic search algorithms based on natural selection. The Tetris genetic algorithm with A* pathfinding discusses memory bound limitations that can prevent direct algorithm conversions from the CPU to the GPU. An analysis of an existing landscape evolution model, CHILD, for GPU acceleration explores that even when a model shows promise for GPU acceleration, the underlying data structures can have a significant impact upon that ability to move to a GPU implementation. CHILD also offers an example of creating tighter MATLAB integration between existing models. Lastly, a parallel spatial sorting algorithm is discussed as a possible replacement for current spatial sorting algorithms implemented in models such as smoothed particle hydrodynamics

High-performance tsunami modelling with modern GPU technology

PhD ThesisEarthquake-induced tsunamis commonly propagate in the deep ocean as long waves and develop into sharp-fronted surges moving rapidly coastward, which may be effectively simulated by hydrodynamic models solving the nonlinear shallow water equations (SWEs). Tsunamis can cause substantial economic and human losses, which could be mitigated through early warning systems given efficient and accurate modelling. Most existing tsunami models require long simulation times for real-world applications. This thesis presents a graphics processing unit (GPU) accelerated finite volume hydrodynamic model using the compute unified device architecture (CUDA) for computationally efficient tsunami simulations. Compared with a standard PC, the model is able to reduce run-time by a factor of > 40. The validated model is used to reproduce the 2011 Japan tsunami. Two source models were tested, one based on tsunami waveform inversion and another using deep-ocean tsunameters. Vertical sea surface displacement is computed by the Okada model, assuming instantaneous sea-floor deformation. Both source models can reproduce the wave propagation at offshore and nearshore gauges, but the tsunameter-based model better simulates the first wave amplitude. Effects of grid resolutions between 450-3600 m, slope limiters, and numerical accuracy are also investigated for the simulation of the 2011 Japan tsunami. Grid resolutions of 1-2 km perform well with a proper limiter; the Sweby limiter is optimal for coarser resolutions, recovers wave peaks better than minmod, and is more numerically stable than Superbee. One hour of tsunami propagation can be predicted in 50 times on a regular low-cost PC-hosted GPU, compared to a single CPU. For 450 m resolution on a larger-memory server-hosted GPU, performance increased by ~70 times. Finally, two adaptive mesh refinement (AMR) techniques including simplified dynamic adaptive grids on CPU and a static adaptive grid on GPU are introduced to provide multi-scale simulations. Both can reduce run-time by ~3 times while maintaining acceptable accuracy. The proposed computationally-efficient tsunami model is expected to provide a new practical tool for tsunami modelling for different purposes, including real-time warning, evacuation planning, risk management and city planning