Collaborative Research: SI2-SSI: A Comprehensive Ray Tracing Framework for Visualization in Distributed-Memory Parallel Environments

科学可视化在探索在超级计算机上运行的科学模拟方面发挥着重要作用;通过研究模拟结果的可视化生成的渲染图，经常会有新的发现。渲染几何图形的标准技术是光栅化，最常用的库是OpenGL。许多可视化程序（VisIt，Ensight，VAPOR，ParaView，VTK）使用OpenGL进行渲染。然而，最近在超级计算机上的架构变化为替代渲染技术创造了重要的机会。新兴的众核架构（如TACC上的英特尔至强融核处理器）上的计算能力？的踩踏系统，使光线跟踪，一个更高的质量技术。此外，随着每个节点的几何图形数量的增加，光线跟踪变得越来越具有成本效益，因为其计算成本与屏幕大小而不是几何图形大小成比例。最后，OpenGL的软件实现无法轻松映射到非GPU多核和众核系统，这造成了一个巨大的差距;如果不关闭，可视化将无法直接在大型超级计算机上实现。这种新的、功能更强的体系结构的融合、每个节点几何结构的增加以及对已建立的渲染路径的持久性的关注都促使了这一点 工作为了应对这些趋势，本研究采用了双管齐下的方法。首先，该研究将用一个高性能的开源光线跟踪引擎取代通常用于可视化的OpenGL路径，该引擎可以在CPU和加速器架构上进行交互式渲染。这个新的库将支持OpenGL API，并将立即使用任何基于OpenGL的可视化包，而无需额外的代码修改。其次，这项研究将提供一个高性能的分布式光线跟踪引擎的直接接口，使应用程序可以利用光线跟踪功能不容易暴露通过标准的OpenGL接口，如参与媒体和全局照明模拟。这些功能将使开放科学社区能够轻松创建具有自然光照线索的照片般逼真的图像，以帮助分析和发现。它将进一步扩展现有网络基础设施的能力，以在标准HPC资源上提供交互式可视化。这项工作有可能通过统一（潜在的混合）架构，有效地运行模拟和可视化革命性的原位可视化功能。与代表性不足的群体沟通将是通过PCARP、MITE和妇女参与工程方案进行外联工作的一个主要组成部分。此外，项目团队将通过NSF XD计划、VisIt可视化工具包以及在IEEE可视化、IEEE高性能图形和ACM超级计算等论坛上展出，向公众传播这项工作。

Scientific visualization plays a large role in exploring the scientific simulations that run on supercomputers; new discoveries are often made by studying renderings generated through visualization of simulation results. The standard technique for rendering geometry is rasterization and the most commonly used library for performing this is OpenGL. Many visualization programs (VisIt, Ensight, VAPOR, ParaView, VTK) use OpenGL for rendering. However, recent architectural changes on supercomputers create significant opportunities for alternate rendering techniques. The computational power available on emerging many-core architectures, such as the Intel Xeon Phi processors on TACC?s Stampede system, enable ray-tracing, a higher quality technique. Further, as the amount of geometry per node rises, ray-tracing becomes increasingly cost effective, since its computational costs are proportional to the screen size, not the geometry size. Finally, the software implementation for OpenGL can not be easily mapped to non-GPU multi-core and many-core systems, creating a significant gap; if not closed, visualization will not be possible directly on large supercomputers. This confluence of new, more capable architectures, the increase in geometry per node, and concerns about the durability of the established rendering path all motivate this work. To address these trends, this research uses a two-pronged approach. First, the research will replace the OpenGL pathways that are commonly used for visualization with a high-performance, open-source ray tracing engine that can interactively render on both a CPU and on accelerator architectures. This new library will support the OpenGL API and will be usable immediately by any OpenGL-based visualization package without additional code modification. Second, this research will provide a direct interface to a high-performance distributed ray tracing engine so that applications can take advantage of ray tracing capabilities not easily exposed through the standard OpenGL interface, such as participating media and global illumination simulation. These features will enable the open science community to easily create photo-realistic imagery with natural lighting cues to aid in analysis and discovery. It will further expand the capacity of existing cyberinfrastructure to provide interactive visualization on standard HPC resources. This work has the potential to revolutionize in situ visualization capabilities by unifying the (potentially hybrid) architecture that efficiently run both simulation and visualization. Communicating with underrepresented groups will be a major component of outreach efforts through the PCARP, MITE and Women in Engineering programs. In addition, the project team will disseminate this work to the general public through NSF XD program, the VisIt visualization toolkit and by exhibiting at forums such as IEEE Visualization, IEEE High Performance Graphics and ACM Supercomputing.