JADE: Joint Academic Data science Endeavour - 2

JADE：联合学术数据科学努力 - 2

• 批准号: EP/T022205/1
• 负责人: Wesley Armour
• 金额: $ 858.78万
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FT022205%2F1
• 关键词: JADE; Joint; Academic; Data; science

This proposal brings together 19 universities, including 12 out of 16 newly established UKRI CDTs in Artificial Intelligence. Led by the University of Oxford, with support from the Alan Turing Institute (Turing), Bath, Bristol, Cambridge, Exeter, Imperial, KCL, Leeds, Loughborough, Newcastle, QMUL, Sheffield, Southampton, Surrey, Sussex, UCL, Warwick and York, our proposal aims to build on the success of the JADE Tier 2 facility. The current JADE facility represents a unique national resource providing state of the art GPU computing facilities to world leading experts in the areas of Artificial Intelligence/Machine Learning (AI/ML) and molecular dynamics (MD) research. In addition to providing a leading compute resource, the JADE facility has also provided a nucleus around which a national consortium of AI researchers has formed, making it the de facto national compute facility for AI research. By providing a much-needed shared resource to these communities, JADE has also delivered an outstanding level of world leading science, evidenced in the twenty two pages of preliminary case studies submitted to EPSRC on 11/09/18. JADE2 will build upon these successes by providing increased computational capabilities to these communities and delivering a stronger, more robust service to address the lessons learned from the initial service. The architecture for JADE2 will be a similar to that of JADE, based on NVIDIA's DGX platform. JADE is formed from 22x DGX1V nodes. JADE2 will be over twice the size of JADE and employ the more cost effective DGX1 Max Q platform. Differences between Max Q and the premium DGX1V are centred on on a slightly reduced bandwidth to GPU memory and lower peak compute performance.Tests of relevant codes on these platforms show that, for AI/ML and Molecular Dynamics, Max Q achieves at least 3/4 performance, using 2/3 the power for 1/2 of the price. The system will be run as a national facility, providing free access to all academic users through a lightweight Resource Allocation Panel (RAP). HECBioSim will run the RAP for MD users, ATI will run the corresponding RAP for AI/ML users.

该提案汇集了 19 所大学，其中包括 16 所新成立的 UKRI 人工智能 CDT 中的 12 所。由牛津大学领导，并得到艾伦图灵研究所（图灵）、巴斯、布里斯托尔、剑桥、埃克塞特、帝国理工学院、KCL、利兹、拉夫堡、纽卡斯尔、QMUL、谢菲尔德、南安普顿、萨里、苏塞克斯、伦敦大学学院、沃里克和约克，我们的提案旨在以 JADE 二级设施的成功为基础。目前的 JADE 设施代表了一种独特的国家资源，为人工智能/机器学习 (AI/ML) 和分子动力学 (MD) 研究领域的世界领先专家提供最先进的 GPU 计算设施。除了提供领先的计算资源外，JADE 设施还提供了一个核心，围绕该核心组建了一个国家人工智能研究人员联盟，使其成为事实上的国家人工智能研究计算设施。通过向这些社区提供急需的共享资源，JADE 还提供了世界领先科学的杰出水平，这一点在 2018 年 11 月 9 日提交给 EPSRC 的 22 页初步案例研究中得到了证明。 JADE2 将在这些成功的基础上，为这些社区提供增强的计算能力，并提供更强大、更稳健的服务，以吸取从初始服务中吸取的经验教训。 JADE2 的架构将与 JADE 类似，基于 NVIDIA 的 DGX 平台。 JADE 由 22 个 DGX1V 节点组成。 JADE2 的尺寸将是 JADE 的两倍以上，并采用更具成本效益的 DGX1 Max Q 平台。 Max Q 与高级 DGX1V 之间的差异集中在 GPU 内存带宽略有减少以及峰值计算性能较低。在这些平台上对相关代码的测试表明，对于 AI/ML 和分子动力学，Max Q 至少实现了 3/ 4.性能，用2/3的功率，1/2的价格。该系统将作为国家设施运行，通过轻量级资源分配面板（RAP）向所有学术用户提供免费访问。 HECBioSim将为MD用户运行RAP，ATI将为AI/ML用户运行相应的RAP。