CNS Core: Small: Semeru: A memory-disaggregated managed runtime

现代计算严重依赖云计算系统。云计算系统由大型数据中心提供动力。每个数据中心包含部署在全球各地的数千台机器。这些数据中心通常配备为不同类型的工作负载设计的异构硬件设备。高效、可靠地使用这些机器和设备的能力是它们可能提供的服务质量的关键，因此对云计算系统提供商来说至关重要。近年来，资源分解作为提高数据中心可靠性和资源利用率的有效手段被提出。资源分解将每种资源类型构建为一个独立的资源，称为“刀片”，并将不同的资源刀片通过网络连接起来。sememeru项目开发运行时和操作系统（OS）支持，允许用户在资源分解的数据中心中高效地运行托管云应用程序。sememeru主要关注三个主要的推力，以改进应用程序的局部性和管理这些应用程序内存的垃圾收集（GC）。首先，它在中央处理统一（CPU）和内存服务器之间开发了一个统一的内存抽象，称为统一Java堆。这允许CPU和内存服务器看到Java堆的相同虚拟地址空间。其次，它开发了一个分布式垃圾收集器（GC），它将部分GC转移到内存服务器，利用它们的空闲和弱计算能力来执行连续的、接近数据的对象跟踪。对象跟踪可以显著提高GC性能。第三，它共同优化运行时和操作系统内核，以便操作系统可以提供有效的交换支持以及对运行时的新系统调用。sememeru项目为托管云工作负载构建了一个内存分解的运行时，从而可以将低级硬件的进步转化为托管云应用程序可以享受的可见性能优势。该项目的发展包括一名博士后学者以及几名研究生和本科生，其中包括少数民族学生。它不仅提高了资源分解的技术水平，而且还培训了当前和未来的计算系统开发人员。该项目生成一组工件，包括技术报告、发表的论文以及代码存储库。这些文物都可以在http://www.cs.ucla.edu/~harryxu.This上在线获得，奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Modern computing relies heavily on cloud computing systems. The cloud computing systems are powered by large datacenters. Each datacenter contains thousands of machines deployed across the globe. These datacenters are often equipped with heterogeneous hardware devices designed for different kinds of workloads. The ability to use these many machines and devices efficiently and reliably is key to the quality of the services they may provide, and therefore paramount to cloud computing system providers. Recently, resource disaggregation has been proposed as an effective means to improve datacenter reliability and resource utilization. Resource disaggregation builds each resource type as a standalone resource, called a “blade", and connects different resource blades with a network. The Semeru project develops runtime and operating system (OS) support that allows users to run managed cloud applications efficiently in resource-disaggregated datacenters. Semeru focuses on three major thrusts for improving locality for applications and garbage collection (GC) that manages memory for these applications. First, it develops a unified memory abstraction between the Central Processing Unity (CPU) and memory servers, referred to as the Unified Java Heap. This allows CPU and memory servers to see the same virtual address space for the Java heap. Second, it develops a distributed garbage collector (GC) that offloads part of the GC to memory servers, utilizing their idle and weak compute capability to perform continuous, close-to-data object tracing. Object tracing can significantly improve the GC performance. Third, it co-optimizes the runtime and OS kernel so that the OS can provide efficient swapping support as well as new system calls for the runtime. The Semeru project builds a memory-disaggregated runtime for managed cloud workloads, making it possible to translate low-level hardware advances to visible performance benefits that managed cloud applications can enjoy. The development of the project includes a postdoctoral scholar as well as several graduate and undergraduate students, including students from minority groups. It not only advances the state of the art of resource disaggregation, but also trains current and future computing system developers.The project produces a set of artifacts including technical reports, published papers, as well as code repositories. These artifacts are all made available online at http://www.cs.ucla.edu/~harryxu.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.