Collaborative Research: Elements: Bifrost - A CPU/GPU Pipeline Framework for High Throughput Data Acquisition and Analysis

协作研究：Elements：Bifrost - 用于高吞吐量数据采集和分析的 CPU/GPU 管道框架

• 批准号: 2103771
• 负责人: Christopher League
• 金额: $ 12万
• 依托单位: Long Island University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2103771&HistoricalAwards=false
• 关键词: Collaborative; Research; Elements; Bifrost; CPU

Modern computers, including cell phones and tablets, have sophisticated Graphics Processing Units (GPUs) that render the beautiful graphic displays in games. We are developing software that takes advantage of these same GPUs for capturing and processing data from astronomical telescopes. This allows us to benefit from all the years of effort spent developing these powerful computational tools. This software, known as Bifrost, is currently in use at the Long Wavelength Array (LWA), a radio telescope for exploration of a broad scientific portfolio ranging from the study of Cosmic Dawn when the first stars and galaxies lit up the Universe, to understanding the properties of the Earth's ionosphere. We are actively developing Bifrost to make it both more powerful and easier to use for other telescopes. Eventually we aim for Bifrost to be available as a more general purpose framework that can be applied to research projects beyond astronomy. About 5 years ago we adopted a commodity equipment design for the second LWA station (LWA-SV) which makes use of computing servers with GPUs to handle the data capture, beamforming, and correlation at the station level. Previously these functions were taken on by dedicated hardware referred to as the Digital Processor. However, this custom-hardware design was expensive to build and maintain, lacks flexibility, and cannot be easily replicated for future LWA stations. In contrast the commodity approach is easier to maintain, much more flexible and expandable, and can be readily adapted to new LWA stations. We are engaged in a concentrated effort to improve the underpinnings of Bifrost. This involves increasing the data rates that Bifrost is capable of handling, improving the application programming interface, and providing tools to make it easier for users to develop and test new pipelines. Through this award we are working with collaborators to incorporate Bifrost in telescopes and instruments currently under development. The availability of Bifrost will increase the scientific return of not only radio astronomy but also other areas where high throughput data processing is needed.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.

包括手机和平板电脑在内的现代计算机都具有复杂的图形处理单元（GPU），可以在游戏中呈现美丽的图形显示。 我们正在开发软件，利用这些相同的GPU来捕获和处理来自天文望远镜的数据。 这使我们能够从多年来开发这些强大的计算工具的努力中受益。这一软件被称为彩虹，目前正在长波长阵列（LWA）中使用，这是一个射电望远镜，用于探索广泛的科学组合，从研究第一批恒星和星系照亮宇宙时的宇宙黎明，到了解地球电离层的特性。 我们正在积极开发彩虹，使其更强大，更容易用于其他望远镜。 最终，我们的目标是使彩虹桥成为一个更通用的框架，可以应用于天文学以外的研究项目。大约5年前，我们为第二个LWA站（LWA-SV）采用了商品设备设计，该设计利用带GPU的计算服务器来处理站级的数据捕获、波束形成和相关性。 以前，这些功能由称为数字处理器的专用硬件承担。然而，这种定制硬件设计的构建和维护成本昂贵，缺乏灵活性，并且不能容易地复制到未来的LWA站。 相比之下，商品方法更容易维护，更灵活和可扩展，并且可以很容易地适应新的LWA站。 我们正集中精力改善彩虹桥的基础。 这包括提高Bifrost能够处理的数据速率，改进应用程序编程接口，并提供工具，使用户更容易开发和测试新的管道。 通过这个奖项，我们正在与合作者合作，将彩虹桥纳入目前正在开发的望远镜和仪器中。 彩虹桥的可用性不仅将增加射电天文学的科学回报，而且还将增加其他需要高通量数据处理的领域的科学回报。该奖项反映了NSF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。