Toward simulation-time data analysis and I/O acceleration on leadership-class systems
Toward simulation-time data analysis and I/O acceleration on leadership-class systems
复制标题
DOI：
10.1109/ldav.2011.6092178
复制
发表时间：
2011-12
期刊：
影响因子：
--
通讯作者：
V. Vishwanath;M. Hereld;M. Papka
中科院分区：
文献类型：
--
作者：
V. Vishwanath;M. Hereld;M. Papka
当前一代HPC系统的计算和I/O组件之间的性能不匹配使得I/O成为科学应用的关键瓶颈。因此，尽可能高效地进行数据移动并促进模拟时数据分析和可视化以减少写入存储的数据至关重要。这些将是至关重要的，使我们能够从模拟中收集新的见解。我们在GLEAN中展示了我们的工作，GLEAN是一个灵活的框架，用于在极端规模下进行数据分析和I/O加速。GLEAN利用应用程序的数据语义，充分利用不同的系统拓扑结构和特性。我们讨论了GLEAN的模拟时间分析和I/O加速的性能，并在领导级系统上进行了大规模模拟
The performance mismatch between computing and I/O components of current-generation HPC systems has made I/O the critical bottleneck for scientific applications. It is therefore critical to make data movement as efficient as possible, and, to facilitate simulation-time data analysis and visualization to reduce the data written to storage. These will be of paramount importance to enabling us to glean novel insights from simulations. We present our work in GLEAN, a flexible framework for data-analysis and I/O acceleration at extreme scale. GLEAN leverages the data semantics of applications, and fully exploits the diverse system topologies and characteristics. We discuss the performance of GLEAN for simulation-time analysis and I/O acceleration with simulations at scale on leadership class systems