Co-Designing Distributed Applications with Datacenter Networks

科学突破越来越依赖于处理大量信息，以发现数据中的重要模式和关系。这需要的处理能力远远超过单台机器的处理能力。相反，工作被划分并分发到由高速网络连接的机器集群。不幸的是，集群中机器之间的通信流量可能会淹没网络的某些部分，导致网络拥塞，从而限制了处理应用程序的可扩展性和性能。当处理应用被部署在共享环境中（诸如在公共云中）时，来自其他应用的流量进一步加剧了该问题。因此，科学进步可能会因为网络资源利用效率低下而延迟甚至停止。

Scientific breakthroughs increasingly rely on processing vast volumes of information to discover important patterns and relationships in the data. This requires far more processing power than is available on a single machine. Instead, the work is partitioned and distributed to a cluster of machines connected by a high-speed network. Unfortunately, the communication traffic between machines in a cluster can overwhelm parts of the network, resulting in network congestion that limits the scalability and performance of the processing application. The problem is further compounded by traffic from other applications when the processing application is deployed in a shared environment, such as in the public cloud. As a result, scientific progress may be delayed or even halted because of inefficient network resource utilization.