PPoSS: Planning: Cross-Layer Design for Cost-Effective HPC in the Cloud

PPoSS：规划：云中经济高效 HPC 的跨层设计

• 批准号: 2028929
• 负责人: Mahmut Kandemir
• 金额: $ 25万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2022-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2028929&HistoricalAwards=false
• 关键词: PPoSS; Planning; Cross; Layer; Design

Many high-performance computing (HPC) applications of national importance (e.g., nuclear simulations, climate modeling, drug discovery, epidemiology, and finance) process enormous datasets and have significant resource demands and strict performance/accuracy/power constraints. Ever-changing hardware elements (e.g., emerging new compute elements) and systems software (continuous fixes to operating systems, compilers and runtime systems) make hosting such HPC applications in locally-managed compute platforms increasingly less attractive. A promising alternate approach is to host these applications in the cloud. However, making legacy HPC applications cloud-ready and identifying the best blend of cloud services for a given application are significant challenges that need to be addressed. In this project, a holistic, cross-layer approach is taken to address the problem of securely mounting such HPC applications in the cloud with high efficiency, low cost, and good performance. A key distinguishing aspect of this project is that it combines both compile-time and run-time innovations and makes contributions to both client and cloud-provider sides. This project spans the following five complementary thrusts, all of which are made challenging by the increasing complexity and scale of the HPC applications of interest, and by the complexity of cloud service offerings and application service-level objectives: (i) characterizing HPC application behavior on myriad cloud infrastructural options; (ii) compiler support for HPC application cloudization; (iii) novel programming language support -- Object-as-a-Service (OaaS); (iv) workload placement and scheduling support; and (v) systems software support for PaaS/SaaS on heterogeneous hardware. The ultimate goal of this project is to devise systematic methodologies for mapping HPC applications to different types of services (spanning IaaS, SaaS, FaaS, OaaS) in multi/hybrid-cloud. This research facilitates improvements in the costs of running HPC applications. This project also enables easy transitioning of HPC applications from one cloud to another and provides data for cloud architecture designers to tune their systems better for current and future HPC workloads. In addition to its technical contributions, this project involves various educational and outreach activities as well. In particular, a new graduate curriculum for cloud computing focusing on HPC applications is created and freely disseminated. Finally, the code being developed and experimental results collected are documented and open-sourced.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.

国家重要性（例如核模拟，气候建模，药物发现，流行病学和金融）的许多高性能计算（HPC）应用程序的应用程序庞大的数据集，并且具有巨大的资源需求以及严格的性能/准确性/功率约束。不断变化的硬件元素（例如，新兴的新计算元素）和系统软件（连续修复操作系统，编译器和运行时系统）使在本地管理的计算平台中托管此类HPC应用程序的吸引力越来越小。 一种有希望的替代方法是将这些应用程序托管在云中。 但是，将旧版HPC应用程序云准备好并确定给定应用程序的云服务的最佳融合是需要解决的重大挑战。在这个项目中，采用了整体，跨层的方法来解决以高效率，低成本和良好的性能将此类HPC应用程序牢固地安装在云中的问题。该项目的一个关键区别是，它结合了编译时间和运行时创新，并为客户和云提供者提供贡献。该项目跨越了以下五个互补推力，所有这些项目都是由于感兴趣的HPC应用程序的复杂性和规模日益增加，以及云服务产品的复杂性和应用程序服务级别的目标的挑战。 （ii）编译器支持HPC应用程序云； （iii）新颖的编程语言支持-Abs-As-A-Service（OAAS）； （iv）工作负载安排和调度支持； （v）系统软件支持PAAS/SaaS在异质硬件上。 该项目的最终目的是将系统方法论映射到多类/混合云中的不同类型的服务（跨越IaaS，SaaS，FAAS，OAAS）。 这项研究促进了运行HPC应用程序成本的改善。该项目还可以轻松地将HPC应用程序从一个云转换为另一个云，并为云体系结构设计人员提供数据，以更好地调整其系统，以实现当前和将来的HPC工作负载。除了其技术贡献外，该项目还涉及各种教育和外展活动。特别是，创建并自由传播了针对HPC应用程序的云计算的新的研究生课程。 最后，正在制定的代码和收集的实验结果记录和开源。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响审查标准，被认为值得通过评估来获得支持。

项目成果

SHOWAR: Right-Sizing And Efficient Scheduling of Microservices

• DOI: 10.1145/3472883.3486999
• 发表时间: 2021-11
• 期刊: Proceedings of the ACM Symposium on Cloud Computing
• 作者: A. F. Baarzi;G. Kesidis

Splice: An Automated Framework for Cost-and Performance-Aware Blending of Cloud Services

• DOI: 10.1109/ccgrid54584.2022.00021
• 发表时间: 2022-05
• 期刊: 2022 22nd IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid)
• 作者: Myungjun Son;S. Mohanty;Jashwant Raj Gunasekaran;Aman Jain;M. Kandemir;G. Kesidis;B. Urgaonkar