Improving Throughput by Dynamically Adapting Concurrency of Data Transfer
Authors: Prasanna Balaprakash (Argonne National Laboratory), Vitali Morozov (Argonne National Laboratory), Rajkumar Kettimuthu (Argonne National Laboratory)
Abstract: Improving the throughput of data transfer over high-speed long-distance networks has become increasingly difficult and complex. Numerous factors such as varying congestion scenarios, external factors which are hard to characterize analytically, dynamics of the underlying transfer protocol, contribute to this difficulty. In this study, we consider optimizing memory to memory transfer via TCP, where the data is transferred from a source memory to a destination memory using TCP.
Inspired by the simplicity and the effectiveness of additive increase and multiplicative decrease scheme of TCP variants, we propose a tuning algorithm that can dynamically adapt the number of parallel TCP streams to improve the aggregate throughput of data transfers. We illustrate the effectiveness of the proposed algorithm on a controlled environment. Preliminary results show significant throughput improvement under congestion.
Two-page extended abstract: pdf