GPU-accelerated molecular visualization on petascale supercomputing platforms

J. Stone, Kirby L. Vandivort, K. Schulten
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引用次数: 55

Abstract

Petascale supercomputers create new opportunities for the study of the structure and function of large biomolecular complexes such as viruses and photosynthetic organelles, permitting all-atom molecular dynamics simulations of tens to hundreds of millions of atoms. Together with simulation and analysis, visualization provides researchers with a powerful "computational microscope". Petascale molecular dynamics simulations produce tens to hundreds of terabytes of data that can be impractical to transfer to remote facilities, making it necessary to perform visualization and analysis tasks in-place on the supercomputer where the data are generated. We describe the adaptation of key visualization features of VMD, a widely used molecular visualization and analysis tool, for GPU-accelerated petascale computers. We discuss early experiences adapting ray tracing algorithms for GPUs, and compare rendering performance for recent petascale molecular simulation test cases on Cray XE6 (CPU-only) and XK7 (GPU-accelerated) compute nodes. Finally, we highlight opportunities for further algorithmic improvements and optimizations.
千万亿次超级计算平台上gpu加速的分子可视化
千万亿次超级计算机为研究大型生物分子复合物(如病毒和光合细胞器)的结构和功能创造了新的机会,允许对数千万到数亿个原子进行全原子分子动力学模拟。与模拟和分析相结合,可视化为研究人员提供了一个强大的“计算显微镜”。千万亿次分子动力学模拟产生数十到数百tb的数据,这些数据无法传输到远程设施,因此有必要在生成数据的超级计算机上执行可视化和分析任务。本文描述了一种广泛使用的分子可视化和分析工具VMD在gpu加速的千万亿次计算机上的关键可视化特性。我们讨论了早期在gpu上采用光线追踪算法的经验,并比较了最近在Cray XE6(仅cpu)和XK7 (gpu加速)计算节点上的千万亿次分子模拟测试用例的渲染性能。最后,我们强调了进一步算法改进和优化的机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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