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Influence of InfiniBand FDR on the performance of remote GPU virtualization

机译:InfiniBand FDR对远程GPU虚拟化性能的影响

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The use of GPUs to accelerate general-purpose scientific and engineering applications is mainstream today, but their adoption in current high-performance computing clusters is impaired primarily by acquisition costs and power consumption. Therefore, the benefits of sharing a reduced number of GPUs among all the nodes of a cluster can be remarkable for many applications. This approach, usually referred to as remote GPU virtualization, aims at reducing the number of GPUs present in a cluster, while increasing their utilization rate. The performance of the interconnection network is key to achieving reasonable performance results by means of remote GPU virtualization. To this end, several networking technologies with throughput comparable to that of PCI Express have appeared recently. In this paper we analyze the influence of InfiniBand FDR on the performance of remote GPU virtualization, comparing its impact on a variety of GPU-accelerated applications with other networking technologies, such as Infini-Band QDR and Gigabit Ethernet. Given the severe limitations of freely available remote GPU virtualization solutions, the rCUDA framework is used as the case study for this analysis. Results show that the new FDR interconnect, featuring higher bandwidth than its predecessors, allows the reduction of the overhead of using GPUs remotely, thus making this approach even more appealing.
机译:如今,使用GPU来加速通用科学和工程应用程序已成为主流,但是由于当前的高性能计算集群而导致的购置成本和功耗降低了GPU的普及率。因此,对于许多应用程序而言,在群集的所有节点之间共享数量减少的GPU的好处可能非常明显。这种方法通常称为远程GPU虚拟化,旨在减少群集中存在的GPU数量,同时提高其利用率。互连网络的性能是通过远程GPU虚拟化获得合理性能结果的关键。为此,近来出现了几种吞吐量可与PCI Express相媲美的联网技术。在本文中,我们分析了InfiniBand FDR对远程GPU虚拟化性能的影响,并与其他网络技术(如Infini-Band QDR和千兆以太网)比较了它对各种GPU加速应用程序的影响。鉴于免费提供的远程GPU虚拟化解决方案的严重局限性,将rCUDA框架用作此分析的案例研究。结果表明,新的FDR互连具有比以前更高的带宽,可以减少远程使用GPU的开销,因此使这种方法更具吸引力。

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