Collaborative Research: Frameworks: Diamond: Democratizing Large Neural Network Model Training for Science

合作研究：框架：钻石：科学大型神经网络模型训练的民主化

• 批准号: 2311766
• 负责人: Zhao Zhang
• 金额: $ 94.95万
• 依托单位: University of Texas at Austin
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2023-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2311766&HistoricalAwards=false
• 关键词: Collaborative; Research; Frameworks; Diamond; Democratizing

Diamond is a service designed to democratize access to cutting-edge DL methods by abstracting the use of HPC resources. Diamond combines novel computer science research with translational computer science to reduce the significant barriers that impede adoption of DL methods in science. With Diamond, domain scientists can focus on the neural network architecture design to solve their domain-specific challenges without worrying about Cyberinfrastructure management. Diamond also contributes to key educational outcomes. PhD students work directly on project goals, and tools developed in the project will be used in undergraduate and graduate-level courses. The tools will also be used in summer schools and programs at TACC, UChicago, and NCSA. Targeted recruitment of students from underserved communities at the graduate, undergraduate, and high-school levels will address diversity and outreach goals.Diamond builds upon prior work in software ecosystem management, parallel computing, deep learning, and data management, combining disparate capabilities into a cohesive and user-friendly framework. It provides a web service-enabled programming interface supporting the DL lifecycle from development to deployment and dissemination. It offers container configuration, automatic scaling for distributed training, hyper-parameter tuning, and model sharing. It also applies crucial performance optimizations, including planning for long training jobs, performance-aware model placement, cross-cluster training, and data management. Diamond results are made available to domain scientists, computer scientists, and engineers supporting DL applications in HPC centers.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.

Diamond是一项旨在通过抽象使用HPC资源来使对尖端DL方法访问的访问的服务。 Diamond将新颖的计算机科学研究与转化计算机科学结合在一起，以减少阻碍科学中DL方法采用的重大障碍。借助Diamond，领域科学家可以专注于神经网络架构设计，以解决其特定领域的挑战，而不必担心网络基础设施管理。钻石还为关键的教育成果做出了贡献。博士生直接实现项目目标的工作，项目中开发的工具将用于本科和研究生级课程。这些工具还将在TACC，Uchicago和NCSA的暑期学校和计划中使用。来自研究生，本科和高中级别的服务不足社区的学生有针对性地招募学生，将解决多样性和外展目标。Diamond基于软件生态系统管理，并行计算，深度学习和数据管理的先前工作，并将不同的功能结合到凝聚力和用户友好的框架中。它提供了一个支持Web服务的编程接口，该界面支持DL生命周期从开发到部署和传播。它提供容器配置，用于分布式培训的自动缩放，超参数调整和模型共享。它还应用了至关重要的绩效优化，包括计划长期培训工作，表现吸引模型的位置，跨集群培训和数据管理。钻石结果可用于支持HPC中心中DL应用的领域科学家，计算机科学家和工程师。该奖项反映了NSF的法定任务，并且使用基金会的知识分子优点和更广泛的影响评估审查标准，认为值得通过评估值得支持。