1 Analyzing Data Movements and Identifying Techniques for Next-generation High-bandwidth Networks

High-bandwidth networks are poised to provide new opportunities in tackling large data challenges in today's scientific applications. However, increasing the bandwidth is not sufficient by itself; we need careful evaluation of future high-bandwidth networks from the applications ’ perspective. We have investigated data transfer requirements of climate applications as a typical scientific example and evaluated how the scientific community can benefit from next generation high-bandwidth networks. We have experimented with current state-of-the-art data movement tools, and realized that there is no single solution for presetting transfer parameters for optimal use of the available bandwidth. Thus, we developed an adaptive transfer methodology for tuning and optimization in wide-area data transfers. This worked well with large files. However, typical scientific datasets may include many small files. Current file-centric data transfer protocols do not perform well with managing the transfer of small files, even when using parallel streams or concurrent transfers over high bandwidth networks. In order to overcome this problem, we develop a new block-based data movement method (in contrast to the current file-based methods) to improve data movement performance and efficiency in moving large scientific datasets that contain many small files. We implemented the new block-based data movement tool, which takes the approach of aggregating files into blocks and providing dynamic data channel management