SPX: Collaborative Research: Enabling Efficient Computer Architectural and System Support for Next-Generation Network Function Virtualization

网络功能虚拟化(NFV)因其更高的性能、灵活性和适应性而被电信和互联网服务提供商广泛采用，被视为即将到来的第五代(5G)无线网络最有前途的技术。然而，确保整合的下一代NFV工作负载可以在当前商用的服务器和系统上高效运行，同时保持最佳的服务器/网络利用率仍然是一项挑战。主要原因是现有的解决方案只是作为特定于层的优化。由于跨系统和架构层的松散耦合优化，这些解决方案缺乏整体和协同的视角，无法保证5G NFV功能带来的性能、弹性和弹性。该项目旨在优化在商用服务器架构和系统上整合5G NFV的效率。该项目的贡献是：(1)重新思考当前NFV部署和优化的各个层所使用的机制，以及(2)重新设计层和应用之间的抽象。该项目的影响将为5G时代的下一代NFV打开新一代高效可扩展计算平台的大门。该项目还将通过吸引代表不足的群体、为教育和培训传播研究基础设施/工具/基准以及向各行业转让技术，为社会作出贡献。该项目提议开发：全系统的概况分析工具和一个自动的、具有建筑统计意识的NFV工作负荷协调和基准框架；使NFV应用程序能够利用虚拟图形处理单元(GPU)的新技术，并改进GPU和智能网络接口卡(NIC)之间的数据移动调度；新的抽象，允许NFV应用程序和构建块利用新兴的卸载技术(例如，智能NIC和GPU远程直接内存访问)和新的体系结构，以提高整合效率、并行性和可扩展性；以及操作系统和加速器的新算法和抽象，以改进线程、缓存和内存管理以及跨层并行性。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Network Function Virtualization (NFV) has been widely adopted by telecommunication and internet service providers for greater performance, flexibility, and adaptability, and is treated as the most promising technology for the upcoming fifth generation (5G) wireless networks. However, ensuring that consolidated next-generation NFV workloads can efficiently run on current, commercially available servers and systems while maintaining optimal server/network utilization remains a challenge. The main reason is that existing solutions only serve as layer-specific optimizations. Due to the loose-coupled optimizations across the system and architectural layers, these solutions lack the holistic and synergistic view to guarantee the performance, resilience, and elasticity posed by the features of 5G NFV. This project aims to optimize the efficiency of consolidation of 5G NFV on commercially available server architectures and systems. The contributions of this project are: (1) rethinking the mechanisms employed in various layers of current NFV deployment and optimization, and (2) re-architecting the abstractions between the layers and applications. The impacts of this project will open the door for a new class of efficient scalable computing platforms for next-generation NFV in the 5G era. This project will also contribute to society through engaging under-represented groups, research infrastructure/tools/benchmarks dissemination for education and training, and technology transfer to industries.This project proposes to develop: system-wide profiling tools and an automatic, architectural statistics-aware NFV workloads orchestration and benchmarking framework; new techniques that allow NFV applications to leverage virtualized graphic processing units (GPU), and that improve the scheduling of data movement between GPU and smart network interface cards (NICs); new abstractions that allow NFV applications and building blocks to leverage emerging offloading techniques (e.g. smart NIC and GPU remote direct memory access) and a novel architecture to improve the consolidation efficiency, parallelism, and scalability; and novel algorithms and abstractions for operating systems and accelerators to improve the thread, cache and memory management and cross-layer parallelism.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.