第165回（特別版 第3回）

Effective use of data management techniques for analysis and visualization of massive scientific data is a crucial ingredient for the success of any supercomputing center and cyberinfrastructure for data-intensive scientific investigation. In the progress towards exascale computing, the data movement challenges have fostered innovation leading to complex streaming workflows that take advantage of any data processing opportunity arising while the data is in motion. This technology finds practical use in a number of industry applications including precision agriculture and tele-medicine. In this talk I will present a number of techniques developed at the Center for Extreme Data Management Analysis and Visualization (CEDMAV) that allow to build a scalable data movement infrastructure for fast I/O while organizing the data in a way that makes it immediately accessible for analytics and visualization. In addition, I will present a topological analytics framework that allows processing data in-situ and achieve massive data reductions while maintaining the ability to explore the full parameter space for feature selection. Overall, this leads to a flexible data streaming workflow that allows working with massive simulation models without compromising the interactive nature of the exploratory process that is characteristic of the most effective data analytics and visualization environment.

※ストリーミング型大規模データ可視化ツールOpenViSUSのチュートリアルを3月20日に行います。
詳細はOpenViSUS ストリーミング型大規模データ可視化チュートリアル（2019年3月20日）をご覧下さい。