SHF: Small: Collaborative Research: Coupling Computation and Communication in FPGA-Enhanced Clouds and Clusters

SHF：小型：协作研究：FPGA 增强型云和集群中的耦合计算和通信

• 批准号: 1618303
• 负责人: Martin Herbordt
• 金额: $ 22.5万
• 依托单位: Trustees of Boston University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-06-15 至 2020-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1618303&HistoricalAwards=false
• 关键词: SHF; Small; Collaborative; Research; Coupling

The introduction of Field Programmable Gate Arrays (FPGAs) to accelerate clusters of servers in datacenters and clouds provides a great, immediate opportunity to leverage a new technology in high-end computing. With their flexible logic and native massive communication capability, FPGAs are ideal for high-performance computing in the post-Moore?s Law world. Since the hardware adapts to the application higher efficiency can be achieved, and since FPGAs are hybrid communication/computation processors, they can be interconnected directly chip-to-chip. Large-scale communication can consequently proceed with both higher bandwidth, lower latency, and less processor impact. These features are crucial to enhancing performance beyond current levels. The proposed design allows for useful processing while data is in flight in the network resulting in reduced software overhead in parallel middleware and reduced network congestion. The key tenets of the research are to achieve programmable, intelligent acceleration of applications while emphasizing overlap of communication and computation at low latency, while also cutting substantially software overhead. The research project, FC5 (an FPGA framework for coupling communication and computation in clouds and clusters) has several thrusts. First, hardware support for FC5 and investigation of methods of configurability in FC5 to reduce communication latency and support computing in the network are studied. A second outcome is a prototype version of the Open MPI open source version of MPI-3.1 parallel middleware that utilizes FC5 to deliver the features and performance enhancements involving data movement between and within servers, mathematical data reductions, and bulk data reorganizations. Third, proof-of-concept versions of multiple FC5 software models, including direct hardware access, a transparent MPI-in-OpenCL, and an API-based mechanism that exposes essential functionality. Finally, because FC5 is evolving rapidly with major new announcements expected imminently, continued refinement is essential. At least two model applications, Molecular Dynamics and Map-Reduce, will be used as test cases. With the continued consolidation of computing services into the cloud, the potential broader impact is to increase both the scale and availability of parallel applications. The broad range of uses of cloud and cluster computing for commercial, government, and academic applications means that acceleration offered will have a widespread impact applicable across many sectors. The growing acceptance of high performance computing in industry (e.g., fast machine learning) is one particular potential commercial sector that will be enhanced by this project.

引入现场可编程栅极阵列（FPGA）来加速数据中心和云中的服务器簇，这为在高端计算中利用新技术提供了一个很好的直接机会。 FPGA凭借其灵活的逻辑和本地大规模的沟通能力，非常适合在后月经后的法律世界中进行高性能计算。由于硬件适应应用程序可以提高效率，并且FPGA是混合通信/计算处理器，因此可以直接互连芯片到芯片。因此，大规模沟通可以通过更高的带宽，较低的潜伏期和更少的处理器影响进行。这些功能对于提高超出当前水平的性能至关重要。所提出的设计允许在网络中数据中的数据中进行有用的处理，从而导致并行中间件中的软件开销减少并减少网络拥塞。研究的主要原则是实现可编程，智能加速应用程序，同时强调低潜伏期的通信和计算重叠，同时还将大量的软件开销。研究项目FC5（用于云和集群中耦合通信和计算的FPGA框架）有多个推力。首先，研究了针对FC5的硬件支持以及研究FC5中可配置的方法，以减少网络中的通信延迟和支持计算。第二个结果是MPI 3.1平行中间件的开放MPI开源版本的原型版本，该版本利用FC5来提供涉及服务器之间和内部数据移动的功能和性能增强功能，数学数据减少以及批量数据重组。第三，多个FC5软件模型的概念验证版本，包括直接硬件访问，透明的MPI-In-Opencl和一种基于API的机制，该机制揭示了基本功能。最后，由于FC5随着预期的重大新公告的迅速发展，因此持续的改进至关重要。至少两个模型应用，分子动力学和地图还原将用作测试用例。随着计算服务持续合并到云中，潜在的更广泛的影响是增加并行应用的规模和可用性。云和集群计算在商业，政府和学术应用中的广泛用途意味着所提供的加速度将在许多领域具有广泛的影响。对行业中高性能计算（例如，快速机器学习）的日益增长的接受是该项目将增强的一个特殊潜在商业领域。