CSR: Small: Collaborative Research: Enabling Cost-Effective Cloud HPC

该项目研究构建在公共云基础设施之上的新颖服务，以实现经济高效的高性能计算。PI 将探索云计算的按需、弹性和可配置功能，以补充传统的超级计算机/集群平台。更具体地说，本研究旨在评估利用云实例的可配置性和分层定价模型构建基于云的动态集群的有效性。该提案的科学价值在于对 HPC 云计算未开发功能的新颖使用，以及战略性采用小型基于云的集群，以开发/调整大型超级计算机的应用程序。通过这项研究，PI 期望回答以下关键研究问题：(1) 自动工作负载特定的云集群配置，(2) 成本感知和争用感知数据和任务协同调度，以及 (3) 自适应、集成云实例配置和作业调度，以及用于降低云实例租赁成本的工作负载聚合。如果成功，这项研究将产生针对不同 HPC 需求自适应聚合、配置和重新配置云资源的工具，目的是为可扩展的并行应用程序提供低成本的研发环境。

The project examines novel services built on top of public cloudinfrastructure to enable cost-effective high-performance computing.The PIs will explore the on-demand, elastic, and configurable features ofcloud computing to complement the traditional supercomputer/clusterplatforms. More specifically, this research aims to assess the efficacyof building dynamic cloud-based clusters leveraging the configurabilityand tiered pricing model of cloud instances. The scientific value of thisproposal lies in the novel use of untapped features of cloud computingfor HPC and the strategic adoption of small, cloud-based clusters forthe purpose of developing/tuning applications for large supercomputers.Through this research, the PIs expect to answer key research questionsregarding: (1) automatic workload-specific cloud cluster configuration,(2) cost-aware and contention-aware data and task co-scheduling,and (3) adaptive, integrated cloud instance provisioning and jobscheduling, plus workload aggregation for cloud instance rental costreduction. If successful, this research will result in tools thatadaptively aggregate, configure, and re-configure cloud resources fordifferent HPC needs, with the purpose of offering low-cost R&Denvironments for scalable parallel applications.