Collaborative Research: ABI Development: Building A Community Resource for Neuroscientists

合作研究：ABI 开发：为神经科学家建立社区资源

• 批准号: 1146949
• 负责人: Amitava Majumdar
• 金额: $ 70.66万
• 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: 2012
• 资助国家: 美国
• 起止时间: 2012-05-01 至 2016-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1146949&HistoricalAwards=false
• 关键词: Collaborative; Research; ABI; Development; Building

The University of California-San Diego and Yale University are awarded collaborative grants to develop a Neuroscience Gateway (NSG) that will facilitate access and use of high performance computing (HPC) resources by neuroscientists. Computational modeling of cells and networks has become an essential part of neuroscience research, and investigators are using models to address problems of ever increasing complexity, e.g. large scale network models and optimization or exploration of high dimensional parameter spaces. The NSG will catalyze such research by lowering or eliminating the administrative and technical barriers that currently make it difficult for investigators to use HPC resources. It will offer computer time to neuroscience users through an administratively and technologically streamlined process with a simple web portal-based environment for uploading models, specifying HPC job parameters, querying running job status and receiving job completion notices, and retrieving and storing output data. The URL of the NSG portal is http://www.nsgportal.org. It will also provide a community forum for neuroscientists to collaborate and share data. The NSG architecture will transparently distribute user jobs to appropriate HPC resources provided by NSF supercomputer centers. The NSG team will collaborate with developers of neural simulation software to optimally install, test, and benchmark these applications on HPC machines, and allow developers to test new versions before release. This project will have a transformative impact by enabling access by members of the computational neuroscience community to HPC resources for research and instruction involving compute-intensive simulations (typically large neural networks). Many of these investigators and students would otherwise find it very difficult, if not impossible, to implement and study models that press or exceed the storage and speed capabilities that are under their direct control. Computational modeling offers opportunities for students and researchers at institutions with limited resources for wet lab or experimental infrastructure to participate in leading edge science. Projects such as this, which facilitate access to HPC resources, democratize participation in science by mitigating the financial barriers to research infrastructure. The NSG will enable students and researchers, who lack access to HPC resources and are thus at a significant disadvantage compared to very few who have it, by removing the barriers for progress for many including historically underrepresented groups. The PIs of this project will target the promotion of the NSG to underrepresented minority scientists and minority serving institutions through active participation in summer training academies and a network of previously mentored female and minority students, some now employed at minority serving institutions.

加州大学圣地亚哥分校和耶鲁大学被授予合作资助，共同开发神经科学门户（NSG），该门户将促进神经科学家访问和使用高性能计算（HPC）资源。细胞和网络的计算建模已经成为神经科学研究的重要组成部分，研究人员正在使用模型来解决日益复杂的问题，例如大规模网络模型和高维参数空间的优化或探索。核供应国集团将通过降低或消除目前使研究人员难以使用高性能计算资源的行政和技术障碍来促进这类研究。它将为神经科学用户提供计算机时间，通过管理和技术上简化的流程，通过一个简单的基于web门户的环境来上传模型，指定HPC作业参数，查询运行作业状态，接收作业完成通知，检索和存储输出数据。NSG portal的URL为http://www.nsgportal.org。它还将为神经科学家提供一个合作和共享数据的社区论坛。NSG架构将透明地将用户作业分配给NSF超级计算机中心提供的适当HPC资源。NSG团队将与神经模拟软件的开发人员合作，在高性能计算机器上优化安装、测试和基准测试这些应用程序，并允许开发人员在发布新版本之前测试新版本。该项目将产生变革性的影响，使计算神经科学社区的成员能够访问HPC资源，用于涉及计算密集型模拟（通常是大型神经网络）的研究和指导。否则，这些研究者和学生中的许多人会发现，如果不是不可能的话，实施和研究那些在他们直接控制下的存储和速度能力的模型是非常困难的。计算建模为湿实验室或实验基础设施资源有限的机构的学生和研究人员提供了参与前沿科学的机会。像这样的项目促进了对高性能计算资源的获取，通过减轻研究基础设施的财政障碍，使科学参与民主化。NSG将为包括历史上代表性不足的群体在内的许多群体消除进步的障碍，从而使那些无法获得高性能计算资源的学生和研究人员能够与拥有高性能计算资源的少数人相比处于明显的劣势。该项目的目标是通过积极参与暑期培训学院和以前受过指导的女性和少数民族学生网络，将NSG推广到代表性不足的少数民族科学家和少数民族服务机构，其中一些人现在受雇于少数民族服务机构。