GPU-based four-dimensional general-relativistic ray tracing
GPU-based four-dimensional general-relativistic ray tracing
复制标题
基于GPU的四维广义相对论光线追踪
DOI：
10.1016/j.cpc.2012.04.030
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
D. Weiskopf
中科院分区：
文献类型：
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作者：
Daniel Kuchelmeister;Thomas Müller;M. Ament;G. Wunner;D. Weiskopf
本文提出了一种新的广义相对论射线追踪器，利用图形处理单元（gpu）的性能，在交互式基础上实现图像合成。该应用程序能够可视化恒星背景的扭曲以及围绕紧凑质量运行的移动天体的轨迹。它的源代码包括Schwarzschild和Kerr时空的度量定义，依靠其面向对象的设计，可以很容易地扩展到其他度量定义。其基本功能包括基于脚本语言Lua的场景描述界面、实时图像输出以及在运行时编辑几乎所有参数的能力。光线追踪代码本身是使用NVidia的计算统一设备架构（CUDA）在GPU上并行执行的，与单个CPU相比，这导致性能提高了一个数量级，并使应用程序与小型CPU集群架构相竞争。项目摘要项目名称：GpuRay4D目录标识符：AEMV_v1_0项目摘要URL: http://cpc.cs.qub.ac.uk/summaries/AEMV_v1_0.html项目来源：北爱尔兰贝尔法斯特女王大学CPC项目库许可条款：标准CPC许可，http://cpc.cs.qub.ac.uk/licence/licence.html号。分布式程序的行数，包括测试数据等：73649分发格式：tar.gz编程语言：c++， CUDA。计算机：Linux平台，支持NVidia CUDA GPU（计算能力1.3或更高），c++编译器，NVCC （CUDA编译器驱动程序）。操作系统：Linux。内存：2gb分类：1.5。外部例程：OpenGL Utility Toolkit开发文件，NVidia CUDA Toolkit 3.2, Lua5.2问题性质：四维洛伦兹时空中的光线追踪。求解方法：光线数值积分，基于gpu的CUDA并行编程，OpenGL 3d渲染。运行时间：取决于问题，从几秒到几小时不等。
This paper presents a new general-relativistic ray tracer that enables image synthesis on an interactive basis by exploiting the performance of graphics processing units (GPUs). The application is capable of visualizing the distortion of the stellar background as well as trajectories of moving astronomical objects orbiting a compact mass. Its source code includes metric definitions for the Schwarzschild and Kerr spacetimes that can be easily extended to other metric definitions, relying on its object-oriented design. The basic functionality features a scene description interface based on the scripting language Lua, real-time image output, and the ability to edit almost every parameter at runtime. The ray tracing code itself is implemented for parallel execution on the GPU using NVidia’s Compute Unified Device Architecture (CUDA), which leads to performance improvement of an order of magnitude compared to a single CPU and makes the application competitive with small CPU cluster architectures. Program summary Program title: GpuRay4D Catalog identifier: AEMV_v1_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEMV_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 73649 No. of bytes in distributed program, including test data, etc.: 1334251 Distribution format: tar.gz Programming language: C++, CUDA. Computer: Linux platforms with a NVidia CUDA enabled GPU (Compute Capability 1.3 or higher), C++ compiler, NVCC (The CUDA Compiler Driver). Operating system: Linux. RAM: 2 GB Classification: 1.5. External routines: OpenGL Utility Toolkit development files, NVidia CUDA Toolkit 3.2, Lua5.2 Nature of problem: Ray tracing in four-dimensional Lorentzian spacetimes. Solution method: Numerical integration of light rays, GPU-based parallel programming using CUDA, 3D-Rendering via OpenGL. Running time: Problem dependent, several seconds up to hours.