OptoCloud: Ultra-fast optically interconnected heterogeneous Data Centers

大多数人类活动，包括交通、互联网、银行、公共卫生和娱乐，都依赖于数据中心。预计云流量将呈指数级增长，占全球流量的95%。2015年，全球数据中心的总耗电量高于英国的全国耗电量，预计到2030年将增长至多15倍。目前，所有的数据中心网络都是基于分层电子分组交换网络组成的，但它们跟不上需求，导致数据增长与摩尔定律之间的差距越来越大。因此，尽管计算节点能力(以触发器/S为单位)在过去18年中增加了65倍，但节点通信带宽仅增加了4.8倍，每个触发器的通信字节数减少了8倍。这创建了通信墙的计算，最大限度地减少了数据移动，并限制了应用程序在本地运行。此外，这些系统还存在非常高的中位延迟，O(100微秒)(100微秒量级)和99.9%的尾延迟O(100ms)，这损害了系统和应用程序的性能。OptoCloud联谊会旨在设计和构建一个节能、经济、可扩展、单跳和纳秒速度的光电路交换网络。这将互连由服务器、CPU、加速器、神经形态处理器、存储元件、存储设备组成的异类系统，以支持不同部件(机架、行尾)和不同规模的数据中心(中小型约10-100,000到约1,000,000个服务器群)。至关重要的是，该网络旨在提供零数据丢失，而无需网络内a)缓冲、b)主动交换和路由、以及c)网络报头寻址和处理，以最大限度地降低复杂性，并消耗非常低的功率。此外，该系统还将以同步方式固有地支持1对1、1对N、N对N和N对1连接，而不需要为多播/广播复制数据，这目前是不可能的。这是支持各种工作负载的关键，例如存储缓存、大规模数据库查找、训练分布式深度神经网络、使用通信原语的并行计算，例如ALL REDUTE、BROADCAST和REDUTE、聚集和分散、ALL到ALL等等。为了实现这些目标，OptoCloud将探索亚纳秒光交换、近无接收器低功率收发器和纳秒调度的基本挑战，这些挑战能够每10秒-100纳秒重新配置电路并塑造IT和网络拓扑。PI将与PDRA、博士生、工业伙伴(微软、Finisar、Xilinx、住友电气)以及大学(哥伦比亚大学和雅典国立技术大学)合作，形成独特的计算和光网络生态系统，在方法论上回答基本问题，同时反映对提议概念的所有必要要求，并使用工业驱动的用例场景严格评估开发的技术。

The majority of human activities, including transport, Internet, banking, public health and entertainment, depend on Data Centers. Cloud traffic is forecasted to grow exponentially and account for 95% of global traffic. In 2015, the total power consumption of data centers worldwide was higher than the national power consumption of the UK and is predicted to increase up to 15-times by 2030. Currently, all data center networks are formed based on hierarchical electronic packet switched networks; however, they can't keep up with demand creating a ever increasing gap between data growth and Moore's Law. So, while compute node power, measured in flop/s, has increased by 65 times in the last 18 years, the node communication bandwidth has only increased by 4.8 times and the bytes communicated per flop have decreased 8 times. This creates a computation to communication wall, minimizing data movement and constraining applications to operate locally. In addition, these systems also suffer from very high median latencies, O(100microseconds) (order of 100microseconds), and 99.9-percentile tail latencies, O(100ms), to the detriment of the system and application performance.The OptoCloud fellowship aims to design and build an energy efficient, cost effective, scalable, single hop, and nanosecond speed optical circuit switched network. This will interconnect heterogeneous systems made of servers, CPUs, accelerators, neuromorphic processors, memory elements, storage to support different parts (rack, end-of-row) and sizes of data centers (small-medium size ~10-100,000 to ~1,000,000 server farm). Crucially, the network aims to offer zero data loss, without in-network a) buffering, b) active switching and routing, and c) network header addressing and processing to minimize complexity, and to consume very low power. Furthermore, the system also will inherently support 1-to-1, 1-to-N, N-to-N and N-to-1 connectivity in a synchronous manner without the need for data replication for multi/broad -casting, currently not possible. This is key to support diverse workloads such as storage caching, large-scale database lookups, training distributed deep neural networks, parallel computing that use communication primitives such as allreduce, broadcast and reduce, gather and scatter, all-to-all among others. To achieve these, OptoCloud will explore the fundamental challenges of sub-nanosecond optical switching, near receiver-less low-power transceivers and nanosecond scheduling able to reconfigure circuits and shape IT and network topologies every 10s-100s of nanoseconds. It aims to offer orders of magnitude improvement in a) switching, b) scheduling and network topology re-configuration, c) power consumption, d) medium and tail latency and finally e) throughput with zero data loss.The PI will work with the PDRAs, PhD students, industrial partners (Microsoft, Finisar, Xilinx, Sumitomo Electric), as well as universities (Columbia and National Technical University of Athens) and form a unique compute and optical network ecosystem to methodologically answer fundamental questions while reflecting all necessary requirements on the proposed concepts, and rigorously evaluating developed technologies using industrial driven use case scenarios.