Zhe Fan

GPU Cluster for High Performance Computing

Inspired by the attractive Flops/dollar ratio and the incredible growth in the speed of modern graphics processing units (GPUs), we propose to use a cluster of GPUs for high performance scientific computing. As an example application, we have developed a parallel flow simulation using the lattice Boltzmann model (LBM) on a GPU cluster and have simulated the dispersion of airborne contaminants in the Times Square area of New York City. Using 30 GPU nodes, our simulation can compute a 480x400x80 LBM in 0.31 second/step, a speed which is 4.6 times faster than that of our CPU cluster implementation. Besides the LBM, we also discuss other potential applications of the GPU cluster, such as cellular automata, PDE solvers, and FEM.

Blowing in the wind

We present an approach for simulating the natural dynamics that emerge from the coupling of a flow field to lightweight, mildly deformable objects immersed within it. We model the flow field using a Lattice Boltzmann Model (LBM) extended with a subgrid model and accelerate the computation on commodity graphics hardware to achieve real-time simulations. We demonstrate our approach using soap bubbles and a feather blown by wind fields, yet our approach is general enough to apply to other light-weight objects. The soap bubbles illustrate Fresnel reflection, reveal the dynamics of the unseen flow field in which they travel, and display spherical harmonics in their undulations. The free feather floats and flutters in response to lift and drag forces. Our single bubble simulation allows the user to directly interact with the wind field and thereby influence the dynamics in real time.

Lattice-based flow field modeling

We present an approach for simulating the natural dynamics that emerge from the interaction between a flow field and immersed objects. We model the flow field using the lattice Boltzmann model (LBM) with boundary conditions appropriate for moving objects and accelerate the computation on commodity graphics hardware (GPU) to achieve real-time performance. The boundary conditions mediate the exchange of momentum between the flow field and the moving objects resulting in forces exerted by the flow on the objects as well as the back-coupling on the flow. We demonstrate our approach using soap bubbles and a feather. The soap bubbles illustrate Fresnel reflection, reveal the dynamics of the unseen flow field in which they travel, and display spherical harmonics in their undulations. Our simulation allows the user to directly interact with the flow field to influence the dynamics in real time. The free feather flutters and gyrates in response to lift and drag forces created by its motion relative to the flow. Vortices are created as the free feather falls in an otherwise quiescent flow.

Zippy: A Framework for Computation and Visualization on a GPU Cluster

Due to its high performance/cost ratio, a GPU cluster is an attractive platform for large scale general‐purpose computation and visualization applications. However, the programming model for high performance general‐purpose computation on GPU clusters remains a complex problem. In this paper, we introduce the Zippy frame‐work, a general and scalable solution to this problem. It abstracts the GPU cluster programming with a two‐level parallelism hierarchy and a non‐uniform memory access (NUMA) model. Zippy preserves the advantages of both message passing and shared‐memory models. It employs global arrays (GA) to simplify the communication, synchronization, and collaboration among multiple GPUs. Moreover, it exposes data locality to the programmer for optimal performance and scalability. We present three example applications developed with Zippy: sort‐last volume rendering, Marching Cubes isosurface extraction and rendering, and lattice Boltzmann flow simulation with online visualization. They demonstrate that Zippy can ease the development and integration of parallel visualization, graphics, and computation modules on a GPU cluster.

Visual Simulation of Heat Shimmering and Mirage

We provide a physically-based framework for simulating the natural phenomena related to heat interaction between objects and the surrounding air. We introduce a heat transfer model between the heat source objects and the ambient flow environment, which includes conduction, convection, and radiation. The heat distribution of the objects is represented by a novel temperature texture. We simulate the thermal flow dynamics that models the air flow interacting with the heat by a hybrid thermal lattice Boltzmann model (HTLBM). The computational approach couples a multiple-relaxation-time LBM (MRTLBM) with a finite difference discretization of a standard advection-diffusion equation for temperature. In heat shimmering and mirage, the changes in the index of refraction of the surrounding air are attributed to temperature variation. A nonlinear ray tracing method is used for rendering. Interactive performance is achieved by accelerating the computation of both the MRTLBM and the heat transfer, as well as the rendering on contemporary graphics hardware (GPU)

Lattice-Based Volumetric Global Illumination

We describe a novel volumetric global illumination framework based on the face-centered cubic (FCC) lattice. An FCC lattice has important advantages over a Cartesian lattice. It has higher packing density in the frequency domain, which translates to better sampling efficiency. Furthermore, it has the maximal possible kissing number (equivalent to the number of nearest neighbors of each site), which provides optimal 3D angular discretization among all lattices. We employ a new two-pass (illumination and rendering) global illumination scheme on an FCC lattice. This scheme exploits the angular discretization to greatly simplify the computation in multiple scattering and to minimize illumination information storage. The GPU has been utilized to further accelerate the rendering stage. We demonstrate our new framework with participating media and volume rendering with multiple scattering, where both are significantly faster than traditional techniques with comparable quality.

Voxels on Fire

We introduce a method for the animation of fire propagation and the burning consumption of objects represented as volumetric data sets. Our method uses a volumetric fire propagation model based on an enhanced distance field. It can simulate the spreading of multiple fire fronts over a specified isosurface without actually having to create that isosurface. The distance field is generated from a specific shell volume that rapidly creates narrow spatial bands around the virtual surface of any given isovalue. The complete distance field is then obtained by propagation from the initial bands. At each step multiple fire fronts can evolve simultaneously on the volumetric object. The flames of the fire are constructed from streams of particles whose movement is regulated by a velocity field generated with the hardware-accelerated Lattice Boltzmann Model (LBM). The LBM provides a physically-based simulation of the air flow around the burning object. The object voxels and the splats associated with the flame particles are rendered in the same pipeline so that the volume data with its external and internal structures can be displayed along with the fire.

Efficient LBM Visual Simulation on Face-Centered Cubic Lattices

The Lattice Boltzmann method (LBM) for visual simulation of fluid flow generally employs cubic Cartesian (CC) lattices such as the D3Q13 and D3Q19 lattices for the particle transport. However, the CC lattices lead to suboptimal representation of the simulation space. We introduce the face-centered cubic (FCC) lattice, fD3Q13, for LBM simulations. Compared to the CC lattices, the fD3Q13 lattice creates a more isotropic sampling of the simulation domain and its single lattice speed (i.e., link length) simplifies the computations and data storage. Furthermore, the fD3Q13 lattice can be decomposed into two independent interleaved lattices, one of which can be discarded, which doubles the simulation speed. The resulting LBM simulation can be efficiently mapped to the GPU, further increasing the computational performance. We show the numerical advantages of the FCC lattice on channeled flow in 2D and the flow-past-a-sphere benchmark in 3D. In both cases, the comparison is against the corresponding CC lattices using the analytical solutions for the systems as well as velocity field visualizations. We also demonstrate the performance advantages of the fD3Q13 lattice for interactive simulation and rendering of hot smoke in an urban environment using thermal LBM.

Dispersion Simulation and Visualization For Urban Security

We present a system for simulating and visualizing the propagation of dispersive contaminants with an application to urban security. In particular, we simulate airborne contaminant propagation in open environments characterised by sky-scrapers and deep urban canyons. Our approach is based on the multiple relaxation time lattice Boltzmann model (MRTLBM), which can efficiently handle complex boundary conditions such as buildings. In addition, we model thermal effects on the flow field using the hybrid thermal MRTLBM. Our approach can also accommodate readings from various sensors distributed in the environment and adapt the simulation accordingly. We accelerate the computation and efficiently render many buildings with small textures on the GPU. We render streamlines and the contaminant smoke with self-shadowing composited with the textured buildings.

Adapted unstructured LBM for flow simulation on curved surfaces

Flow motion on curved surfaces of arbitrary topology is an interesting visual effect but a complex dynamics to simulate. In this paper, we introduce a novel and effective way to model such dynamics. We propose a technique that adapts a recently emerged computational fluid dynamics (CFD) model, unstructured lattice Boltzmann model (Unstructured LBM), from the 2D unstructured meshes to the 3D surface meshes. Unlike previous methods in modeling flows on surfaces, which start from the macroscopic point of view and modify the Navier Stokes solvers for the curved surfaces, our method is based on the microscopic kinetic equations for discrete particle distribution functions. All computations on the surface mesh only involve the information within local neighborhoods. This model lends itself the following advantages: (i) simplicity and explicit parallelism in computation, (ii) great capability in handling complex interactions, such as the interactions between flow and boundaries and the interactions of multiple-component fluids; (iii) no need of global surface parameterization which may cause strong distortions; (iv) capability of being applied to meshes with arbitrary connectivity.