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

SPX：协作研究：为下一代网络功能虚拟化提供高效的计算机架构和系统支持

基本信息

批准号：
1822985
负责人：
Weili Wu
金额：
$ 46万
依托单位：
University of Texas at Dallas
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-08-01 至 2025-01-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1822985&HistoricalAwards=false
关键词：
SPX Collaborative Research Enabling Efficient

项目摘要

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.

网络功能虚拟化 (NFV) 已被电信和互联网服务提供商广泛采用，以提高性能、灵活性和适应性，并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 工作负载能够在当前的商用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个挑战。主要原因是现有的解决方案仅起到特定层的优化作用。由于跨系统和架构层的松耦合优化，这些解决方案缺乏整体和协同的视角来保证 5G NFV 特性带来的性能、弹性和弹性。该项目旨在优化 5G NFV 在商用服务器架构和系统上的整合效率。该项目的贡献是：(1) 重新思考当前 NFV 部署和优化的各个层中采用的机制，以及 (2) 重新架构层和应用程序之间的抽象。该项目的影响将为 5G 时代的下一代 NFV 开启新型高效可扩展计算平台的大门。该项目还将通过吸引代表性不足的群体、教育和培训研究基础设施/工具/基准传播以及向行业转让技术来为社会做出贡献。该项目建议开发：全系统分析工具以及自动的、架构统计感知的 NFV 工作负载编排和基准测试框架；新技术允许 NFV 应用程序利用虚拟化图形处理单元 (GPU)，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）和新颖的架构来提高整合效率、并行性和可扩展性；操作系统和加速器的新颖算法和抽象，以改善线程、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价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

期刊论文数量（14）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Characterizing and Understanding the Architectural Implications of Cloudnative Edge NFV Workloads

DOI：
10.1109/nfv-sdn47374.2019.9039983
发表时间：
2019-11
期刊：
2019 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN)
影响因子：
0
作者：
Jianda Wang;Yang Hu
通讯作者：
Jianda Wang;Yang Hu

An FPGA Implementation of Stochastic Computing-Based LSTM