Bilateral BBSRC-NSF/BIO: Collaborative Research: ABI Development: Seamless Integration of Neuroscience Models and Tools with HPC - Easy Path to Supercomputing for Neuroscience

双边 BBSRC-NSF/BIO：合作研究：ABI 开发：神经科学模型和工具与 HPC 的无缝集成 - 神经科学超级计算的简单途径

• 批准号: 1458840
• 负责人: Amitava Majumdar
• 金额: $ 77.4万
• 依托单位: University of California-San Diego
• 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: 2015-08-01 至 2020-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1458840&HistoricalAwards=false
• 关键词: Bilateral; BBSRC; NSF; BIO; Collaborative

This project is a collaboration between the University of California San Diego and Yale University to develop a science gateway for the computational neuroscience community. A gateway such as this helps improve our understanding of how the brain works by making it easier for neuroscientists to use complex digital models of brain cells and circuits in their research. Powerful software has been developed for building and using models, and on-line resources such as Open Source Brain (OSB), ModelDB, Neuroscience Information Framework (NIF), and OpenWorm have been created to help neuroscientists find existing models, collaborate in developing new ones, and share the results of their work with others. However, models are becoming too complex for the computer hardware that is available to most neuroscientists, resulting in a critical need to use high performance computing resources (HPC). This work extends an existing Neuroscience Gateway (NSG), which was developed with support from NSF to eliminate or reduce many of the technical and administrative difficulties that previously limited neuroscientists' access to HPC (http://www.nsgportal.org/). That said, NSG users must still log in, upload models, launch simulations, and download results--a process that involves many time-consuming, error-prone steps. The expanded NSG-R will eliminate these steps by enabling on-demand, automated communication between itself and familiar working environments including resources like OSB and others mentioned above, and even with neural simulation software running on neuroscientists' own laptop and desktop computers. This seamless access to HPC is implemented in NSG-R by a software infrastructure that uses REpresentational State Transfer ("REST", the R in NSG-R). NSG-R utilizes set of web services which expose the capabilities of NSG for access via publicly available application programmer interfaces. This will allow users of neuroscience resources such as OSB, ModelDB, NIF and OpenWorm to readily access HPC from their respective websites via NSG-R. This enhances the usefulness of NSG-R, other neuroscience resources like OSB, and widely used neural simulators such as NEURON, GENESIS, PyNN, NEST, Brian and MOOSE. It also results in greater research productivity and enables wider use of large scale computational modeling by scientists and students. NSG-R will accelerate progress in brain science, and have far-reaching beneficial effects on related fields such as robotics and engineering of adaptive and learning systems. It will widen opportunities for educational and career advancement in neuroscience and engineering. Furthermore, by removing barriers that traditionally have limited access to HPC, NSG-R levels the playing field for all students and researchers regardless of their institutional affiliation. NSG-R, a free and open neuroscience gateway infrastructure, will naturally be a ready entry point for students and researchers from historically underrepresented schools and colleges. NSG-R workshops will be hosted at minority serving institutions (MSI) and opportunities for students to do internships with the NSG-R team at the University of California San Diego will be provided.

该项目是加州大学圣地亚哥分校和耶鲁大学的合作项目，旨在为计算神经科学社区开发一个科学门户。通过使神经科学家更容易在他们的研究中使用复杂的脑细胞和电路数字模型，这样的网关有助于提高我们对大脑工作方式的理解。已经开发了用于构建和使用模型的强大软件，并且已经创建了诸如开源大脑（OSB）， ModelDB，神经科学信息框架（NIF）和OpenWorm等在线资源，以帮助神经科学家找到现有模型，合作开发新模型，并与其他人分享他们的工作成果。然而，对于大多数神经科学家可用的计算机硬件来说，模型变得过于复杂，导致对高性能计算资源（HPC）的迫切需要。这项工作扩展了现有的神经科学网关（NSG）， NSG是在NSF的支持下开发的，旨在消除或减少以前限制神经科学家访问HPC的许多技术和管理困难（http://www.nsgportal.org/）。也就是说，NSG用户仍然必须登录，上传模型，启动模拟并下载结果，这一过程涉及许多耗时且容易出错的步骤。扩展后的NSG-R将通过实现自身与熟悉的工作环境（包括OSB等上述资源）之间的按需自动化通信，甚至在神经科学家自己的笔记本电脑和台式电脑上运行神经模拟软件，从而消除这些步骤。这种对HPC的无缝访问是在NSG-R中通过使用REpresentational State Transfer （REST， NSG-R中的R）的软件基础设施实现的。NSG- r利用一组web服务，这些服务通过公开可用的应用程序编程接口公开了NSG的功能。这将允许OSB、ModelDB、NIF和OpenWorm等神经科学资源的用户通过NSG-R从各自的网站轻松访问HPC。这增强了NSG-R、其他神经科学资源（如OSB）以及广泛使用的神经模拟器（如NEURON、GENESIS、PyNN、NEST、Brian和MOOSE）的实用性。它还提高了研究效率，使科学家和学生能够更广泛地使用大规模计算建模。NSG-R将加速脑科学的发展，并对机器人、自适应和学习系统工程等相关领域产生深远的有益影响。它将扩大神经科学和工程领域的教育和职业发展机会。此外，通过消除传统上限制进入HPC的障碍，NSG-R为所有学生和研究人员提供了公平的竞争环境，无论他们隶属于哪个机构。NSG-R是一个免费开放的神经科学门户基础设施，自然会成为历史上代表性不足的学校和大学的学生和研究人员的一个现成的切入点。NSG-R工作坊将在少数民族服务机构（MSI）举办，并为学生提供与加州大学圣地亚哥分校NSG-R团队一起实习的机会。