SBIR Phase I: Customized Computing for Big Data Applications

SBIR第一阶段：大数据应用定制计算

• 批准号: 1520449
• 负责人: Peng Zhang
• 金额: $ 15万
• 依托单位: Falcon Computing Solutions, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-07-01 至 2015-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1520449&HistoricalAwards=false
• 关键词: SBIR; Phase; Customized; Computing; Big

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is that it will result in a significant reduction in the energy usage of datacenters worldwide, which is increasing at an alarming rate. Some of the large Internet service providers employ several million computing servers in their datacenters with an annual total energy usage in the order of multi-billion kilowatt hours. For many big data applications that constitute a significant portion of workload in datacenters, using field programmable gate array (FPGA) as a customizable computing device can provide significantly better performance and energy efficiency. Using the software tools and IP solutions developed from this project, one may replace several computing servers with one server augmented with one or more FPGA acceleration cards, resulting in significant cost and energy reduction. The wide deployment of customized computing technology in datacenters as enabled by the solutions developed in this project will lead to substantial energy savings, significant reduction of carbon emissions, and more importantly, more sustainable growth of computing infrastructures so that they can better scale in the future to meet the rapidly increasing computing demands as our society embraces further digital revolution in the coming decades.This Small Business Innovation Research (SBIR) Phase I project focuses on enabling energy-efficient customized computing for big data applications in datacenters. The most significant barrier for widespread adoption of FPGA-based customized computing is the difficulty in programming FPGAs. The innovation of this project includes the development of a set of highly automated compilation, runtime scheduling and resource management tools, as well as high-performance FPGA acceleration libraries to enable efficient and transparent utilization of FPGA resources at the datacenter scale for acceleration of many large-scale distributed computing applications. The software and IP solutions developed under this proposal will enable widespread use of FPGAs in datacenters by a wide range of application developers, resulting in significant improvement in programming productivity by the application developers and substantial energy and cost reduction by the datacenter operators (while delivering the same performance). The goal of this project is to demonstrate the viability and advantage of FPGA-based customized computing in datacenters for some big data application domains against modern multi-core servers and GPUs in terms of performance, energy-efficiency, programmability, and ease of use.

该小型企业创新研究 (SBIR) 第一阶段项目更广泛的影响/商业潜力在于，它将导致全球数据中心的能源使用量大幅减少，而全球数据中心的能源使用量正以惊人的速度增长。一些大型互联网服务提供商在其数据中心使用数百万台计算服务器，每年的总能源使用量约为数十亿千瓦时。对于构成数据中心工作负载很大一部分的许多大数据应用来说，使用现场可编程门阵列 (FPGA) 作为可定制的计算设备可以提供显着更好的性能和能效。使用该项目开发的软件工具和IP解决方案，人们可​​以用一台配备一个或多个FPGA加速卡的服务器取代多台计算服务器，从而显着降低成本和能源。通过本项目开发的解决方案，在数据中心中广泛部署定制计算技术将带来大量能源节约、显着减少碳排放，更重要的是，计算基础设施将实现更可持续的增长，以便它们能够在未来更好地扩展，以满足随着我们的社会在未来几十年进一步拥抱数字革命而快速增长的计算需求。这个小型企业创新研究（SBIR）第一阶段项目的重点是 为数据中心的大数据应用提供节能的定制计算。广泛采用基于 FPGA 的定制计算的最大障碍是 FPGA 编程的难度。该项目的创新点包括开发了一套高度自动化的编译、运行时调度和资源管理工具，以及高性能FPGA加速库，以实现在数据中心规模上高效、透明地利用FPGA资源，从而加速许多大规模分布式计算应用。根据该提案开发的软件和 IP 解决方案将使众多应用程序开发人员能够在数据中心广泛使用 FPGA，从而显着提高应用程序开发人员的编程效率，并大幅降低数据中心运营商的能源和成本（同时提供相同的性能）。该项目的目标是展示数据中心中基于 FPGA 的定制计算在某些大数据应用领域相对于现代多核服务器和 GPU 在性能、能效、可编程性和易用性方面的可行性和优势。