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

科学可视化在探索超级计算机上运行的科学模拟方面发挥着重要作用；新的发现通常是通过研究通过模拟结果可视化生成的渲染来获得的。渲染几何的标准技术是光栅化，执行此操作最常用的库是 OpenGL。许多可视化程序（VisIt、Ensight、VAPOR、ParaView、VTK）使用 OpenGL 进行渲染。然而，超级计算机最近的架构变化为替代渲染技术创造了重要机会。新兴多核架构（例如 TACC 的 Stampede 系统上的英特尔至强融核处理器）所提供的计算能力支持光线追踪，这是一种更高质量的技术。此外，随着每个节点的几何体数量的增加，光线追踪变得越来越经济有效，因为它的计算成本与屏幕尺寸成正比，而不是与几何体尺寸成正比。最后，OpenGL的软件实现无法轻松映射到非GPU多核和众核系统，造成很大差距；如果不关闭，将无法直接在大型超级计算机上进行可视化。新的、功能更强大的架构的融合、每个节点几何体的增加以及对已建立的渲染路径的持久性的担忧都推动了这项工作。为了应对这些趋势，本研究采用了双管齐下的方法。首先，该研究将用高性能开源光线追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渲染。这个新库将支持 OpenGL API，并且可以立即由任何基于 OpenGL 的可视化包使用，无需额外的代码修改。其次，这项研究将为高性能分布式光线追踪引擎提供直接接口，以便应用程序可以利用不易通过标准 OpenGL 接口公开的光线追踪功能，例如参与媒体和全局照明模拟。这些功能将使开放科学界能够利用自然光线索轻松创建逼真的图像，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，以提供标准 HPC 资源的交互式可视化。这项工作有可能通过统一有效运行模拟和可视化的（可能是混合的）架构来彻底改变现场可视化功能。通过 PCARP、MITE 和女性工程项目，与代表性不足的群体进行沟通将成为外展工作的一个重要组成部分。此外，项目团队还将通过 NSF XD 计划、VisIt 可视化工具包以及在 IEEE Visualization、IEEE High Performance Graphics 和 ACM Supercomputing 等论坛上进行展示，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.