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

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:
$15.0万
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
项目状态:
已结题
起止时间:
2014-10-01 至 2018-09-30

项目摘要

项目成果

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中文摘要
翻译
现代计算系统的趋势是向包含大量异构计算和I/O资源的系统架构发展。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,但它确实以增加不同应用程序工作负载之间的干扰为代价。工作负载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。这可能是由于对共享硬件资源(如最后一级缓存、内存控制器或I/O设备)甚至操作系统管理的软件资源的争用造成的。跨工作负载干扰对于大型共享基础设施(如云托管服务)尤其成问题,这些基础设施依赖于在单个数据中心环境中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完全实现其作为通用计算基础的承诺至关重要。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,该系统既可以检测干扰对应用程序的影响,又可以通过在底层系统软件中提供动态隔离功能来减轻其影响。这种方法依赖于对底层硬件资源进行动态分区的能力,从而在硬件层实现隔离,同时还允许对系统软件进行分区,以避免对系统软件本身中存在的更抽象的资源产生争用。为了实现这些目标,这项工作实现了一个“虚拟平台”抽象,表示分配给特定任务或工作负载并由一个或多个虚拟机实例组成的独立且可隔离的系统域。虚拟平台本身被分配了由独立的“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,又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硬件资源提供了硬件级别的隔离,但它不能解决系统软件产生的干扰。通过多栈虚拟化对系统软件本身进行分区,避免了软件级的干扰。多堆栈虚拟化允许多个独立的系统软件层在同一本地系统上共存,方法是将它们的托管资源限制在分配给虚拟平台的集合中。该系统在硬件和软件层都提供了完整的隔离功能。
英文摘要
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.
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Travel: NSF Student Travel Grant for 2022 ACM Symposium on Cloud Computing (ACM SoCC).
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  • 负责人:
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