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

科学可视化在探索运行在超级计算机上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模拟结果的可视化生成的渲染来获得的。渲染几何体的标准技术是光栅化，执行此操作的最常用的库是OpenGL。许多可视化程序(访问、洞察、蒸气、ParaView、VTK)使用OpenGL进行渲染。然而，最近超级计算机的架构变化为替代渲染技术创造了巨大的机会。新兴的多核体系结构上可用的计算能力，如TAcc？S Stampede系统上的Intel Xeon Phi处理器，支持光线跟踪，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，光线跟踪变得越来越经济高效，因为其计算成本与屏幕大小成比例，而不是与几何体大小成比例。最后，OpenGL的软件实现不能很容易地映射到非GPU多核和多核系统，造成了很大的差距；如果不弥合，可视化将不可能直接在大型超级计算机上实现。新的、功能更强大的体系结构的融合、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，所有这些都推动了这项工作。为了应对这些趋势，这项研究采用了双管齐下的方法。首先，这项研究将用高性能、开源的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渲染。这个新的库将支持OpenGL API，并且可以立即被任何基于OpenGL的可视化包使用，而无需修改额外的代码。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，以便应用程序可以利用通过标准OpenGL接口不易暴露的光线跟踪功能，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轻松地创建具有自然光线提示的照片逼真图像，以帮助分析和发现。它将进一步扩大现有网络基础设施的能力，以提供标准高性能计算机资源的交互可视化。这项工作有可能通过统一高效运行模拟和可视化的(潜在的混合)体系结构来彻底改变现场可视化能力。与代表性不足的群体交流将是通过PCARP、MITE和妇女参与工程方案的外联努力的一个主要组成部分。此外，项目组将通过NSF XD计划、访问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的方式，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.