Toward optimizing disk-to-disk transfer on 100G networks

The recent emergence of ultra high-speed networks up to 100 Gbps has posed numerous challenges and has led to many investigations on efficient protocols to saturate 100 Gbps links. However, end-to-end data transfers involve many compo-nents, not only protocols, affecting overall transfer performance. These components include a disk I10 subsystem, additional computation associated with data streams, and network adapter capacities. For example, achievable bandwidth by TCP may not be implementable if disk I/O or CPU becomes a bottleneck in end-to-end data transfer. In this paper, we first model all the system components involved in end-to-end data transfer as a graph. We then formulate the problem whose goal is to achieve maximum data transfer throughput using parallel data flows. Our contributions lie in how to optimize data transfers considering all the system components involved rather than in accurately modeling all the system components involved. Our proposed formulations and solutions are evaluated through experiments on the ESnet 100G testbed. The experimental results show that our approach is several times faster than Globus Online - 8x faster for datasets with many 10MB files and 3-4x faster for other datasets of larger size files.