CAREER: Operating System Support for Ephemeral and Malleable Accelerators

随着摩尔定律的衰落，计算机系统越来越依赖于专门的硬件或加速器来提高性能、可扩展性和能源效率。到2025年，数据中心预计将消耗世界总电力的9%到20%，因此提高性能和效率对我们地球的健康至关重要。现场可编程门阵列（fpga）是一种可重新配置的硬件，具有灵活性，可以根据需要成为任何专用硬件。它们在现代数据中心非常引人注目，因为它们可以从单个可重构设备合成各种各样的加速器；亚马逊和微软等供应商现在支持云中的FPGA加速。然而，对于设计用于管理固定功能设备的传统操作系统来说，向可重构硬件的范式转变是巨大的。当前的系统假设单个应用程序对硬件具有独占访问权，缺乏共享支持限制了利用率和效率。本研究的目标是为受保护的FPGA共享开发系统级抽象和端到端操作系统（OS）支持，从而将利用率和吞吐量提高一个数量级或更多。这是具有挑战性的，因为FPGA加速器是短暂的和可延展性的：它们可能会频繁更改，并且能够随着FPGA资源份额的增加而扩展。这些属性与几十年前的操作系统设计假设背道而驰。该项目旨在提供一个完整的开源堆栈，支持服务器进程高效、高利用率的受保护共享，从而将计算卸载到FPGA上，并将其扩展为云FPGA平台的兼容层。对一个名为AmorphOS的初始原型的测量表明，该方法很有前景，可以将运行神经网络（DNN）推理的Microsoft Catapult和Amazon F1系统的利用率和吞吐量提高8倍和32倍。该系统具有广泛应用于支持fpga的数据中心的可能性，工作结果可以指导下一代异构和可重构硬件操作系统的设计。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。

With the decline of Moore's Law, computer systems increasingly rely on specialized hardware, or accelerators to improve performance, scalability and energy efficiency. Data centers are projected to consume between 9% and 20% of the world's total power by 2025, so improved performance and efficiency are important to the health of our planet. Field Programmable Gate Arrays, or FPGAs, are reconfigurable hardware with flexibility to become any specialized hardware on demand. They are compelling in modern data centers because they enable a wide range of accelerators to be synthesized from a single reconfigurable device; providers such as Amazon and Microsoft now support FPGA acceleration in the cloud. However, the paradigm shift to reconfigurable hardware is massive for traditional operating systems, which are designed to manage fixed-function devices. Current systems assume a single application has exclusive access to the hardware, and the lack of sharing support limits utilization and efficiency.The goal of this research is to develop system-level abstractions and end-to-end operating system (OS) support for protected FPGA sharing that improves utilization and throughput by an order of magnitude or more. This is challenging because FPGA accelerators are ephemeral and malleable: they may change frequently and be able to scale with increased shares of FPGA resource. These properties run counter to decades-old OS design assumptions. The project aims for a complete open-source stack that supports efficient high-utilization protected sharing for server processes to offload computations to FPGAs, and will extend it to function as a compatibility layer for cloud FPGA platforms. Measurements of an initial prototype called AmorphOS show that the approach has promise and can improve utilization and throughput by 8X and 32X for Microsoft Catapult and Amazon F1 systems running neural network (DNN) inference. The system has the possibility to be used pervasively in data centers supporting FPGAs, and the results of the work could guide the design of the next generation of operating systems for heterogeneous and reconfigurable hardware.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.