Rich user interfaces like Jupyter have the potential to make interacting with a supercomputer easier and more productive, consequently attracting new kinds of users and helping to expand the application of supercomputing to new science domains. For the scientist user, the ideal rich user interface delivers a familiar, responsive, introspective, modular, and customizable platform upon which to build, run, capture, document, re-run, and share analysis workflows. From the provider or system administrator perspective, such a platform would also be easy to configure, deploy securely, update, customize, and support. Jupyter checks most if not all of these boxes. But from the perspective of leadership computing organizations that provide supercomputing power to users, such a platform should also make the unique features of a supercomputer center more accessible to users and more composable with high-performance computing (HPC) workflows. Project Jupyter’s ( https://jupyter.org/about ) core design philosophy of extensibility, abstraction, and agnostic deployment has allowed HPC centers like National Energy Research Scientific Computing Center to bring in advanced supercomputing capabilities that can extend the interactive notebook environment. This has enabled a rich scientific discovery platform, particularly for experimental facility data analysis and machine learning problems.

中文翻译：

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使用 Jupyter 进行交互式超级计算


Jupyter 等丰富的用户界面有可能使与超级计算机的交互变得更容易、更高效，从而吸引新类型的用户，并有助于将超级计算的应用扩展到新的科学领域。对于科学家用户来说，理想的丰富用户界面提供了一个熟悉的、响应式的、内省式的、模块化的和可定制的平台，可以在该平台上构建、运行、捕获、记录、重新运行和共享分析工作流程。从提供商或系统管理员的角度来看，这样的平台也易于配置、安全部署、更新、定制和支持。 Jupyter 检查大部分（如果不是全部）这些框。但从向用户提供超级计算能力的领先计算组织的角度来看，这样的平台还应该使超级计算中心的独特功能更易于用户使用，并且更易于与高性能计算（HPC）工作流程进行组合。 Jupyter 项目 ( https://jupyter.org/about ) 的可扩展性、抽象性和不可知部署的核心设计理念使国家能源研究科学计算中心等 HPC 中心能够引入先进的超级计算功能，从而扩展交互式笔记本环境。这使得丰富的科学发现平台成为可能，特别是对于实验设施数据分析和机器学习问题。