HPC环境下基于分布式粒子的大数据可视化渲染框架

J. Nonaka, Naohisa Sakamoto, Takashi Shimizu, M. Fujita, K. Ono, K. Koyamada
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引用次数: 5

摘要

本文提出了一种基于PBVR (Particle based Volume Rendering)方法的高性能计算环境分布式数据可视化框架。PBVR方法是一种基于点的渲染方法,其中要可视化的体积数据被表示为一组小而不透明的颗粒。该方法具有对象空间和图像空间变体,由生成粒子数据集的位置(对象或图像空间)定义。我们专注于对象空间方法,它在处理大型模拟数据集(如由现代HPC系统生成的数据集)时具有优势。在对象空间方法中,粒子生成和随后的渲染过程可以很容易地解耦。在这项工作中,我们利用这种可分离性来实现所提出的分布式呈现框架。粒子生成过程利用KVS(京都可视化系统)提供的功能,粒子渲染过程利用HIVE(异构集成可视化分析环境)提供的功能。提出的分布式可视化框架的目标是在没有任何硬件图形加速能力的系统上工作,这在现代HPC操作环境中很常见。我们在K计算机操作环境中评估了这种基于pbvr的分布式可视化基础架构,利用仅cpu的处理服务器进行粒子数据的生成和渲染。在这个初步评估中,使用一些CFD(计算流体动力学)模拟数据集,我们获得了令人鼓舞的结果,推动了进一步的发展,以便使该系统成为高性能计算用户的有效可视化替代方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distributed Particle-Based Rendering Framework for Large Data Visualization on HPC Environments
In this paper, we present a distributed data visualization framework for HPC environments based on the PBVR (Particle Based Volume Rendering) method. The PBVR method is a kind of point-based rendering approach where the volumetric data to be visualized is represented as a set of small and opaque particles. This method has the object-space and image-space variants, defined by the place (object or image- space) where the particle data sets are generated. We focused on the object-space approach, which has the advantage when handling large-scale simulation data sets such as those generated by modern HPC systems. In the object-space approach, the particle generation and the subsequent rendering processes can be easily decoupled. In this work, we took advantage of this separability to implement the proposed distributed rendering framework. The particle generation process utilizes the functionalities provided by the KVS (Kyoto Visualization System), and the particle rendering process utilizes the functionalities provided by the HIVE (Heterogeneously Integrated Visual- analytics Environment). The proposed distributed visualization framework is targeted to work also on systems without any hardware graphics acceleration capability, which are commonly found on modern HPC operational environments. We evaluated this PBVR-based distributed visualization infrastructure on the K computer operational environment by utilizing a CPU-only processing server for the particle data generation and rendering. In this preliminary evaluation, using some CFD (Computational Fluid Dynamics) simulation data sets, we obtained encouraging results for pushing further the development in order to make this system available as an effective visualization alternative for the HPC users.
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