CSR: Small: Collaborative Research: Enhancing Cloud Performance with On-Demand Isolation

CSR：小型：协作研究：通过按需隔离增强云性能

• 批准号: 1422927
• 负责人: Ada Gavrilovska
• 金额: $ 15万
• 依托单位: Georgia Tech Research Corporation
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-10-01 至 2018-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1422927&HistoricalAwards=false
• 关键词: CSR; Small; Collaborative; Research; Enhancing

The modern trend in computing systems is towards system architectures containing a large numbers of heterogeneous computational and I/O resources. Unfortunately, while the increase in scale allows increased workload consolidation, wherein a single system runs multiple independent applications in parallel, it does come at the cost of introducing increased interference across the different application workloads. Workload interference is the result of the behavior of one application impacting the performance of another, even if both applications are running on different hardware resources. This can be due to contention on shared hardware resources (such as last level caches, memory controllers, or I/O devices) or even software resources managed by the operating system. Cross workload interference is especially problematic for large scale shared infrastructures such as cloud hosting services, which rely on co-hosting large numbers of widely disparate workloads inside a single datacenter environment. Preventing interference effects is critical for cloud computing to fully deliver on its promise as a universal computing substrate. This project addresses the problem of cross workload interference, by providing a holistic system that both detects the impact of interference on applications and mitigates its effects by providing dynamic isolation capabilities in the underlying system software. This approach relies on the ability to dynamically partition the underlying hardware resources such that isolation is achieved at the hardware layer, while also allowing the partitioning of system software to avoid contention on more abstract resources present in the system software itself. To achieve these goals this work implements a "Virtual Platform" abstraction representing an individual and isolatable system domain assigned to a particular task or workload and consisting of one or more virtual machine instances. The virtual platform itself is assigned an allocation of hardware resources consisting of independent "isolatable units." These units are created through the decomposition of local hardware resources into the finest grained subdivision of resources that can be both individually allocated and effectively isolated from the rest of the system. While providing partitioned hardware resources to a virtual platform provides hardware level isolation, it does not address interference generated by the system software. Avoiding software level interference is achieved by partitioning the system software itself through Multi-Stack Virtualization. Multi-stack virtualization allows multiple independent system software layers to co-exist on the same local system by restricting their managed resources to the set allocated to a virtual platform. Taken together this system provides full isolation capabilities at both the hardware and software layers.

计算系统中的现代趋势是朝向包含大量异构计算和I/O资源的系统架构。不幸的是，虽然规模的增加允许增加工作负载整合，其中单个系统并行运行多个独立的应用程序，但它确实以跨不同应用程序工作负载引入增加的干扰为代价。干扰是一个应用程序的行为影响另一个应用程序的性能的结果，即使两个应用程序运行在不同的硬件资源上。这可能是由于共享硬件资源（如最后一级缓存，内存控制器或I/O设备）或甚至由操作系统管理的软件资源上的争用。跨工作负载干扰对于诸如云托管服务之类的大规模共享基础设施尤其成问题，云托管服务依赖于在单个数据中心环境内共同托管大量广泛不同的工作负载。防止干扰效应对于云计算充分实现其作为通用计算基底的承诺至关重要。该项目通过提供一个整体系统来解决跨工作负载干扰的问题，该系统可以检测干扰对应用程序的影响，并通过在底层系统软件中提供动态隔离功能来减轻其影响。这种方法依赖于动态划分底层硬件资源的能力，使得在硬件层实现隔离，同时还允许划分系统软件以避免对系统软件本身中存在的更抽象资源的争用。为了实现这些目标，这项工作实现了一个“虚拟平台”的抽象表示一个单独的和可隔离的系统域分配给一个特定的任务或工作负载，并组成一个或多个虚拟机实例。虚拟平台本身被分配由独立的“可隔离单元”组成的硬件资源分配。这些单元是通过将本地硬件资源分解为最细粒度的资源细分而创建的，这些资源既可以单独分配，也可以有效地与系统的其余部分隔离。虽然向虚拟平台提供分区的硬件资源提供了硬件级隔离，但它没有解决由系统软件生成的干扰。通过多堆栈虚拟化对系统软件本身进行分区，避免软件级干扰。多堆栈虚拟化允许多个独立的系统软件层共存于同一个本地系统上，方法是将它们的托管资源限制为分配给虚拟平台的资源集。总之，该系统在硬件和软件层都提供了完全隔离功能。