Paulo A. Pagliosa

A new physics engine with automatic process distribution between CPU-GPU

The Graphics Processing Units or simply GPUs have evolved into extremely powerful and flexible processors. This flexibility and power have allowed new concepts in general purpose computation to emerge. This paper presents a new architecture for physics engines focusing on the simulation of rigid bodies with some of its methods implemented on the GPU. Sending physics computation to the GPU enables the unloading of the required computations from the CPU, allowing it to process other tasks and optimizations. Another important reason for using the GPU is to allow physics engines to process a higher number of bodies in the simulation. It also presents an automatic process distribution scheme between CPU and GPU. The importance of the automatic distribution for physics simulation arises from the fact that, sometimes, the simulated scene characteristics may change during the simulation and by using an automatic distribution scheme the system may obtain the best performance of both processors (CPU and GPU). Also, with an automatic distribution mode, the developer does not have to decide which processor will do the work allowing the system to choose between CPU and GPU. This paper also presents an uncoupled multithread game loop used by the physics engine.

An adaptative game loop architecture with automatic distribution of tasks between CPU and GPU

This article presents a new architecture to implement all game loop models for games and real-time applications that use the GPU as a mathematics and physics coprocessor, working in parallel processing mode with the CPU. The presented model applies automatic task distribution concepts. The architecture can apply a set of heuristics defined in Lua scripts in order to get acquainted with the best processor for handling a given task. The model applies the GPGPU (general-purpose computation on GPUs) paradigm. In this article we propose an architecture that acquires knowledge about the hardware by running tasks in each processor and, by studying their performance over time, finding the best processor for a group of tasks.

A game loop architecture for the GPU used as a math coprocessor in real-time applications

This article concerns the use of a graphics processor unit (GPU) as a math co-processor in real-time applications in special games and physics simulations. To validate this approach, we present a new game loop architecture that employs GPUs for general-purpose computations (GPGPUs). A critical issue here is the process distribution between the CPU and the GPU. The architecture consists of a model for distribution, and our implementation offers many advantages in comparison to other approaches without the GPGPU stage. This architecture can be used either by a general-purpose language such as the Compute Unified Device Architecture (CUDA), or shader languages such as the High-Level Shader Language (HLSL) and the OpenGL Shading Language (GLSL). Although the architecture proposed here aims at supporting mathematics and physics on the GPU, it is possible to adapt any kind of generic computation. This article discusses the model implementation in an open-source game engine and presents the results of using this platform.

Projection inspector: Assessment and synthesis of multidimensional projections

Abstract As the number and complexity of visualization techniques have grown, it has become progressively more difficult to make a decision as to which technique to employ for any given situation or application. A particular case is that of multidimensional data visualization utilizing projections, which have gained much attention lately and are being utilized in a growing number of applications. With their popularity, many new variations of multidimensional projections have been proposed in the literature. Numerical evaluations are varied and are useful, but do not reflect visual properties of projections accurately. In this paper we present Projection Inspector, an approach that contributes to the problem of understanding the difference amongst projections. It is an interactive assessment method that allows a user to explore a “space” of known projection techniques and view their results, as well as to identify the differences between them. In addition, it generates “on-the-fly” new projection techniques via interpolations of existing techniques as the user explores the projection space. We present the theoretical foundations of the projection exploration space and an interactive tool that implements a view of this space. We demonstrate the approach with case studies that demonstrate the need for projection assessment and the value of combining projections into new, better suited, projection alternatives.

SPH Fluids for Viscous Jet Buckling

We present a novel meshfree technique for animating free surface viscous liquids with jet buckling effects, such as coiling and folding. Our technique is based on Smoothed Particle Hydrodynamics (SPH) fluids and allows more realistic and complex viscous behaviors than the preceding SPH frameworks in computer animation literature. The viscous liquid is modeled by a non-Newtonian fluid flow and the variable viscosity under shear stress is achieved using a viscosity model known as Cross model. The proposed technique is efficient and stable, and our framework can animate scenarios with high resolution of SPH particles in which the simulation speed is significantly accelerated by using Computer Unified Device Architecture (CUDA) computing platform. This work also includes several examples that demonstrate the ability of our technique.

Fluid Simulation with Two-Way Interaction Rigid Body Using a Heterogeneous GPU and CPU Environment

Simulation of natural phenomena, such as water and smoke, is a very important topic to increase real time scene realism in video-games. Besides the graphical aspect, in order to achieve realism, it is necessary to correctly simulate and solve its complex governing equations, requiring an intense computational work.Fluid simulation is achieved by solving the Navier-Stokes set of equations, using a numerical method in CPU or GPU, independently, as these equations do not have an analytical solution. The real time simulacraon also requires the simulation of interaction of the particles with objects in the scene, requiring many collision and contact forces calculation, which may drastically increase the computational time. In this paper we propose an heterogeneous multicore CPU and GPU hybrid architecture for fluid simulation with two-ways of interaction between them, and with a fine granularity control over rigid bodys shape collision. We also show the impact of this heterogeneous architecture over GPU and CPU bounded simulations, which is commonly used for this kind of application. The heterogeneous architecture developed in this work is developed to best fit the Single Instruction Multiple Thread (SIMT) model used by GPUs in all simulation stages, allowing a high level performance increase.

A hybrid GPU rasterized and ray traced rendering pipeline for real time rendering of per pixel effects

Rendering in 3D games typically uses rasterization approaches in order to guarantee interactive frame rates, since ray tracing, a superior method for rendering photorealistic images, has greater computational cost. With the advent of massively parallel processors in the form of GPUs, parallelized ray tracing have been investigated as an alternative to rasterization techniques. While many works present parallelization methods for the classical ray tracing algorithm, in order to achieve interactive, or even real time ray tracing rendering, we present a rasterized and ray traced hybrid technique, completely done in GPU. While a deferred render model determines the colors of primary rays, a ray tracing phase compute other effects such as specular reflection and transparency, in order to achieve effects that are not easily obtained with rasterization. We also present a heuristic approach that select a subset of relevant objects to be ray traced, avoiding traversing rays for objects that might not have a significant contribution to the real time experience. This selection is capable of maintaining the real time requirement of games, while offering superior visual effects.

Neighborhood grid

This paper introduces a novel and efficient data structure, called neighborhood grid, capable of supporting large number of particle based elements on GPUs (graphics processing units), and is used for optimizing fluid animation with the use of GPU computing. The presented fluid simulation approach is based on SPH (smoothed particle hydrodynamics) and uses a unique algorithm for the neighborhood gathering. The brute force approach to neighborhood gathering of n particles has complexity O ( n 2 ) , since it involves proximity queries of all pairs of fluid particles in order to compute the relevant mutual interactions. Usually, the algorithm is optimized by using spatial data structures which subdivide the environment in cells and then classify the particles among the cells based on their position, which is not efficient when a large number of particles are grouped in the same cell. Instead of using such approach, this work presents a novel and efficient data structure that maintains the particles into another form of proximity data structure, called neighborhood grid. In this structure, each cell contains only one particle and does not directly represent a discrete spatial subdivision. The neighborhood grid does process an approximate spatial neighborhood of the particles, yielding promising results for real time fluid animation, with results that goes up to 9 times speedup, when compared to traditional GPU approaches, and up to 100 times when compared against CPU implementations. We present a new data structure for the neighborhood gathering on fluid simulation, called neighborhood grid.The neighborhood grid has an expressive speedup against the uniform grid on GPUs.The neighborhood grid uses less memory when compared with the uniform grid.

Particle-based fluids for viscous jet buckling

In this paper, we introduce a novel meshfree framework for animating free surface viscous liquids with jet buckling effects, such as coiling and folding. Our method is based on Smoothed Particle Hydrodynamics (SPH) fluids and allows more realistic and complex viscous behaviors than the previous SPH frameworks in computer animation literature. The viscous liquid is modeled by a non-Newtonian fluid flow and the variable viscosity under shear stress is achieved using a viscosity model known as Cross model. We demonstrate the efficiency and stability of our framework in a wide variety of animations, including scenarios with arbitrary geometries and high resolution of SPH particles. The interaction of the viscous liquid with complex solid obstacles is performed using boundary particles. Our framework is able to deal with different inlet velocity profiles and geometries of the injector, as well as moving inlet jet along trajectories given by cubic Hermite splines. Moreover, the simulation speed is significantly accelerated by using Computer Unified Device Architecture (CUDA) computing platform. Graphical abstractDisplay Omitted HighlightsOur method models viscous liquid in which the viscosity is governed by Cross model.We introduce a SPH first order approximation for viscous term.We use CUDA to simulate the jet buckling effect in affordable computational times.Our method allows different inlet velocities and geometries of the injector.Our implementation supports jet buckling on complex surfaces.

A heterogeneous system based on GPU and multi-core CPU for real-time fluid and rigid body simulation

Computational fluid dynamics in simulation has become an important field not only for physics and engineering areas but also for simulation, computer graphics, virtual reality and even video game development. Many efficient models have been developed over the years, but when many contact interactions must be processed, most models present difficulties or cannot achieve real-time results when executed. The advent of parallel computing has enabled the development of many strategies for accelerating the simulations. Our work proposes a new system which uses some successful algorithms already proposed, as well as a data structure organisation based on a heterogeneous architecture using CPUs and GPUs, in order to process the simulation of the interaction of fluids and rigid bodies. This successfully results in a two-way interaction between them and their surrounding objects. As far as we know, this is the first work that presents a computational collaborative environment which makes use of two different paradigms of hardware architecture for this specific kind of problem. Since our method achieves real-time results, it is suitable for virtual reality, simulation and video game fluid simulation problems.