CSR: Small: High-Fidelity Datacenter Emulation

本研究解决了数据中心计算作为“云计算”的主导平台的兴起所带来的基本计算机系统挑战。如今，数据中心使用由分布在多个物理网络和地理区域的大型机器组成的复杂系统，为IT、医疗和金融机构托管关键任务服务。这些复杂的服务必须满足严格的设计和性能要求，如水平可伸缩性、容错、自适应和安全性，同时利用低成本的商用硬件。一个关键的挑战是量化硬件变化、软件设计和能源管理策略的影响。关键的是，这样的评估需要真实的代码、工作负载、组件交互、异构硬件和高负载条件来准确地预测性能。本提案研究了构建高保真数据中心仿真平台的技术和体系结构，以将数据中心网络和服务设计从黑色艺术转变为严格，准确和可重复的（科学）过程。这样的设施允许研究人员和架构师开发下一代数据中心设计的原则和最佳实践。通过精确地模拟现实的数据中心规模（10,000多台机器，100多台交换机，多个协作服务），以及数百台机器的适度集群，建议的工作旨在将数据中心实验置于学生，学者和企业的范围内，而无需大型IT公司的财务范围。

This research addresses a fundamental computer systems challenge presented by the rise of datacenter computing as the dominant platform for ``cloud computing.'' Today, datacenters host mission-critical services for IT, health, and financial institutions using complex systems consisting of large ensembles of machines spread across multiple physical networks and geographic regions. These sophisticated services must meet stringent design and performance requirements such as horizontal scalability, fault tolerance, self adaptation, and security while leveraging low-cost commodity hardware. A key challenge is to quantify the impact of hardware changes, software designs, and energy management policies. Critically, such evaluations require the real code, workloads, component interactions, heterogeneous hardware, and high-load conditions to accurately predict performance. This proposal investigates techniques and architectures for building a high-fidelity datacenter emulation platform to transform datacenter network and service design from a black art into a rigorous, accurate, and repeatable (scientific) process. Such a facility allows researchers and architects to develop the principles and best practices for next-generation datacenter design. By accurately emulating realistic datacenter scales (10,000+ machines, 100+switches, multiple cooperating services) with a modest cluster of a few hundred machines, the proposed work aims to place datacenter experimentation within the reach of students, academics, and businesses without the financial reach of large IT firms.