Designing Scalable and High-Performance MPI Libraries on Amazon Elastic Fabric Adapter
Designing Scalable and High-Performance MPI Libraries on Amazon Elastic Fabric Adapter
复制标题
在 Amazon Elastic Fabric Adapter 上设计可扩展且高性能的 MPI 库
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
D. Panda
中科院分区：
文献类型：
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作者：
Sourav Chakraborty;Shulei Xu;H. Subramoni;D. Panda
亚马逊最近宣布了一个名为Elastic Fabric Adapter（EFA）的新网络接口，该接口针对紧密耦合的HPC工作负载。在本文中，我们的特点，功能和性能的适配器。我们还探讨了它的传输模型，如UD和SRD（可扩展的可靠数据报）如何影响高性能MPI库的设计。我们的评估表明，由SRD提供的硬件级可靠性可以显着提高MPI通信的性能。我们还提出了一种新的零拷贝传输机制，在不可靠和无序的通道，可以减少大消息的通信延迟。与供应商提供的MPI库相比，所提出的设计在集体和应用程序性能方面也有显着改进。
Amazon has recently announced a new network interface named Elastic Fabric Adapter (EFA) targeted towards tightly coupled HPC workloads. In this paper, we characterize the features, capabilities and performance of the adapter. We also explore how its transport models such as UD and SRD (Scalable Reliable Datagram) impact the design of high-performance MPI libraries. Our evaluations show that hardware level reliability provided by SRD can significantly improve the performance of MPI communication. We also propose a new zero-copy transfer mechanism over unreliable and orderless channels that can reduce the communication latency of large messages. The proposed design also shows significant improvement in collective and application performance against the vendor provided MPI library.