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MDTM: Optimizing Data Transfer Using Multicore-Aware I/O Scheduling

机译:MDTM:使用支持多核的I / O调度优化数据传输

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Bulk data transfer is facing significant challenges in the coming era of big data. There are multiple performance bottlenecks along the end-to-end path from the source to destination storage system. The limitations of current generation data transfer tools themselves can have a significant impact on end-to-end data transfer rates. In this paper, we identify the issues that lead to underperformance of these tools, and present a new data transfer tool with an innovative I/O scheduler called MDTM. The MDTM scheduler exploits underlying multicore layouts to optimize throughput by reducing delay and contention for I/O reading and writing operations. With our evaluations, we show how MDTM successfully avoids NUMA-based congestion and significantly improves end-to-end data transfer rates across high-speed wide area networks.
机译:在即将到来的大数据时代,批量数据传输面临着巨大的挑战。从源到目标存储系统的端到端路径上存在多个性能瓶颈。当前一代数据传输工具本身的局限性可能对端到端数据传输速率产生重大影响。在本文中,我们确定了导致这些工具性能不佳的问题,并提出了一种具有创新I / O调度程序MDTM的新型数据传输工具。 MDTM调度程序通过减少I / O读写操作的延迟和争用,利用底层的多核布局来优化吞吐量。通过我们的评估,我们展示了MDTM如何成功避免基于NUMA的拥塞并显着提高了跨高速广域网的端到端数据传输速率。

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