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；通过对仿真结果的可视化生成的效果图进行研究，往往会有新的发现。渲染几何图形的标准技术是栅格化，最常用的库是OpenGL。许多可视化程序（VisIt, esight， VAPOR, ParaView， VTK）使用OpenGL进行渲染。然而，最近超级计算机上的体系结构变化为替代渲染技术创造了重要的机会。新兴的多核架构（如TACC上的Intel Xeon Phi处理器）上可用的计算能力？Stampede系统，使光线追踪，一种更高质量的技术。此外，随着每个节点几何体数量的增加，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，而不是几何尺寸。最后，OpenGL的软件实现不能很容易地映射到非gpu的多核和多核系统，造成很大的差距；如果不关闭，可视化将不可能直接在大型超级计算机上实现。新的、更有能力的架构、每个节点几何形状的增加，以及对已建立的渲染路径的持久性的关注，这些因素的融合都激发了这项工作。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、开源的光线追踪引擎取代常用的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，任何基于OpenGL的可视化包都可以立即使用，而无需额外的代码修改。其次，本研究将为高性能分布式光线追踪引擎提供一个直接接口，以便应用程序可以利用不易通过标准OpenGL接口暴露的光线追踪功能，例如参与媒体和全局照明模拟。这些功能将使开放的科学界能够轻松地创建带有自然光线索的逼真图像，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，在标准高性能计算资源上提供交互式可视化。通过统一（潜在的混合）架构，有效地运行仿真和可视化，这项工作有可能彻底改变现场可视化能力。与未被充分代表的群体进行沟通将是通过paccp、MITE和女性参与工程项目开展外展工作的主要组成部分。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.