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On Data Transfers Over Wide-Area Dedicated Connections

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Proceedings of International Symposium on Sensor Networks, Systems and Security (ISSNSS 2017)

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Abstract

Dedicated wide-area network connections are employed in big data and high-performance computing scenarios, since the absence of cross-traffic promises to make it easier to analyze and optimize data transfers over them. However, nonlinear transport dynamics and end-system complexity due to multi-core hosts and distributed filesystems make these tasks surprisingly challenging. We present an overview of methods to analyze memory and disk file transfers using extensive measurements over 10 Gbps physical and emulated connections with 0–366 ms round-trip times (RTTs). For memory transfers, we derive performance profiles of TCP and UDT throughput as a function of RTT, which show concave regions in contrast to entirely convex regions predicted by previous models. These highly desirable concave regions can be expanded by utilizing large buffers and more parallel flows. We also present Poincaré maps and Lyapunov exponents of TCP and UDT throughput traces that indicate complex throughput dynamics. For disk file transfers, we show that throughput can be optimized using a combination of parallel I/O and network threads under direct I/O mode. Our initial throughput measurements of Lustre filesystems mounted over long-haul connections using LNet routers show convex profiles indicative of I/O limits.

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Acknowledgements

This work is supported in part by the RAMSES and Net2013 projects, Office of Advanced Computing Research, US Department of Energy, and by the Extreme Scale Systems Center, sponsored by US Department of Defense, and performed at Oak Ridge National Laboratory managed by UT-Battelle, LLC for US Department of Energy under Contract DE-AC05-00OR22725.

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Correspondence to Nageswara S. V. Rao .

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Rao, N.S.V., Liu, Q. (2018). On Data Transfers Over Wide-Area Dedicated Connections. In: Rao, N., Brooks, R., Wu, C. (eds) Proceedings of International Symposium on Sensor Networks, Systems and Security. ISSNSS 2017. Springer, Cham. https://doi.org/10.1007/978-3-319-75683-7_2

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  • DOI: https://doi.org/10.1007/978-3-319-75683-7_2

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