OAC Core: Small: Next-Generation Communication and I/O Middleware for HPC and Deep Learning with Smart NICs

网内计算技术，或将大部分计算、通信和I/O任务卸载到网络的能力，已经成为在高性能计算（HPC）和深度学习（DL）领域实现终端应用程序的极端规模性能的基本要求。不幸的是，目前的通信中间件和应用程序不能充分利用这些进步，由于缺乏适当的设计，在中间件级。这导致了以下广泛的挑战：1）能够“意识到”这些新兴的网内计算技术的计算能力的中间件是否能够以最优化的方式为HPC和DL应用程序设计？以及2）这样的中间件是否可以用于HPC和DL中的终端应用程序，以实现更好的性能和可移植性？提出了一个协同和全面的研究计划，以应对上述广泛的挑战与创新的解决方案。拟议的框架将提供给合作者和更广泛的科学界，以了解拟议的创新对下一代HPC和DL中间件和应用程序的影响。 一些研究生和本科生将在这个项目下培养未来的科学家和工程师在HPC。拟议的工作将通过俄亥俄州州立大学重点课程的教学法研究来促进课程的进步。此外，我们亦会在不同的会议上举办讲座及工作坊，与社会人士分享研究成果及经验。该项目与国家战略计算计划（NSCI）保持一致，以推动美国在HPC领域的领导地位，以及美国政府最近提出的保持人工智能（AI）领导地位的倡议。拟议的创新包括：1）设计可扩展的通信原语（点对点和集体）使用新兴的基于交换机和NIC的网络内计算功能，2）利用网络内计算功能来加载复杂和用户定义的功能，3）使用NVMe over Fabrics设计高性能I/O和存储子系统，4）为MPI库设计增强的网络内数据类型处理方案，5）为新兴的云环境设计和优化基于网内计算的解决方案，以及6）使用一组具有代表性的HPC和DL应用程序对所提出的设计进行集成开发和评估。拟议的设计将被集成到广泛使用的MVAPICH 2库中，并向公众提供。项目小组成员将与合作者密切合作，以促进广泛部署和采用已发布的软件。拟议研究的变革性影响是通过利用新兴的网络计算技术实现HPC和DL框架/应用程序的可扩展性、性能和可移植性。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响评审标准进行评估，被认为值得支持。

In-network computing technologies, or the ability to offload significant portions of compute, communication, and I/O tasks to the network, have emerged as fundamental requirements to achieve extreme scale performance for end applications in the areas of High-Performance Computing (HPC) and Deep Learning (DL). Unfortunately, current generation communication middleware and applications cannot fully take advantage of these advances due to the lack of appropriate designs in the middleware-level. This leads to the following broad challenges: 1) Can middleware that are “aware” of the computing capabilities of these emerging in-network computing technologies be designed in the most optimized manner possible for HPC and DL applications?, and 2) Can such a middleware be used to benefit end applications in HPC and DL to achieve better performance and portability? A synergistic and comprehensive research plan is proposed to address the above broad challenges with innovative solutions. The proposed framework will be made available to collaborators and the broader scientific community to understand the impact of the proposed innovations on next-generation HPC and DL middleware and applications. Several graduate and undergraduate students will be trained under this project as future scientists and engineers in HPC. The proposed work will enable curriculum advancements via research in pedagogy for key courses at The Ohio State University. Tutorials and workshops will be organized at various conferences to share the research results and experience with the community. The project is aligned with the National Strategic Computing Initiative (NSCI) to advance US leadership in HPC and the recent initiative of the US Government to maintain leadership in Artificial Intelligence (AI.)The proposed innovations include: 1) Designing scalable communication primitives (point-to-point and collectives) for using emerging switch and NIC based in-network computing features, 2) Exploiting in-network computing features to offload complex and user defined functions, 3) Designing high-performance I/O and storage subsystems using NVMe over Fabrics, 4) Designing enhanced in-network datatype processing schemes for MPI library, 5) Designing and optimizing in-network computing-based solutions for emerging cloud environment, and 6) Carrying out integrated development and evaluation of the proposed designs with a set of representative HPC and DL applications. The proposed designs will be integrated into the widely-used MVAPICH2 library and made available to the public. The project team members will work closely with collaborators to facilitate wide deployment and adoption of released software. The transformative impact of the proposed research is to achieve scalability, performance, and portability for HPC and DL frameworks/applications by leveraging emerging in-network computing technologies.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.