SPX: Collaborative Research: Rethinking Data Center Abstractions Utilizing Warehouse-Scale Shared Memory

仓库规模的计算机（或数据中心）对于人们每天依赖的技术至关重要：从购物到叫车，再到与朋友分享体验。为仓库规模的计算机编程需要专门的软件来协调组成数据中心的许多独立计算机，同时确保系统在任何一台机器出现故障时仍能继续运行。不幸的是，这种数据中心软件与为单台计算机开发的软件（即大多数计算机科学专业的学生所学习的软件）存在根本差异，导致开发时间长，性能差。这项提议的工作将弥合当前数据中心使用的软件系统与大多数程序员（和计算机专业学生）可用的软件系统之间的差距。这项提议的工作将允许数据中心内的个人计算机通过“共享内存”进行通信，这种机制与小型计算机（从电话到笔记本电脑再到单独的服务器）使用的机制相同。该项目有可能使每个人都更容易使用仓库规模的计算。特别是，它将允许在普通机器（笔记本电脑、台式机）上运行的软件轻松过渡到数据中心。此外，该项目将通过加强课堂项目和为本科生创造研究机会来创造许多教育机会。该项目的显著特点是对新的计算硬件和操作系统进行了整体设计，以允许这种“共享内存”抽象来提供专用数据中心软件的规模和容错能力。先前的硬件采用“全部共享”或“不共享”的方法，而提议的硬件将允许在硬件子集之间共享数据子集。然后，操作系统将被扩展为自动管理对这个共享内存的访问，这样程序员就不需要知道其中的区别。通过协调软件和硬件管理，该项目将克服先前共享内存的可伸缩性和容错挑战。它还将允许轻松共享数据中心资源，防止碎片化并降低使用数据中心和云计算的成本。该奖项反映了美国国家科学基金会的法定使命，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。

Warehouse-scale computers (or data centers) are essential for the technology that people rely on every day: from making purchases, to hailing rides, to sharing experiences with friends. Programming warehouse-scale computers requires specialized software that coordinates the many individual computers that make up the data center, while ensuring that the system will continue to operate if any machine fails. Unfortunately, this data center software has fundamental differences from that developed for single computers (i.e., that is taught to most computer science students) resulting in long development times and poor performance. The proposed work will bridge the gap between the software systems used in current data centers and what is available to most programmers (and computing students). The proposed work will allow individual computers within a data center to communicate through "shared memory"---the same mechanism used within small-scale computers from phones to laptops to individual servers. The project has the potential to make warehouse scale computing much more accessible to everyone. In particular, it will allow an easy transition for software that runs on common machines (laptops, desktops) to the datacenter. Additionally, the project will create many educational opportunities through enhanced classroom projects and creation of research opportunities for undergraduates.The project's distinguishing feature is a holistic design of new computing hardware and operating systems to allow this "shared memory" abstraction to provide both the scale and failure tolerance of specialized data center software. While prior hardware takes an approach of "share all" or "share nothing", the proposed hardware will allow subsets of data to be shared across subsets of hardware. Then, the operating system will be extended to automatically manage the access to this shared memory, so that programmers do not need to be aware of the difference. By coordinating software and hardware management, the project will overcome prior scalability and failure tolerance challenges of sharing memory. It will also allow easy sharing of datacenter resources, preventing fragmentation and reducing the cost of using datacenters and cloud computing.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.