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Energy-Aware Application-Centric VM Allocation for HPC Workloads

机译:用于HPC工作负载的能量感知应用中心VM分配

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Virtualized datacenters and clouds are being increasingly considered for traditional High-Performance Computing (HPC) workloads that have typically targeted Grids and conventional HPC platforms. However, maximizing energy efficiency, cost-effectiveness, and utilization of datacenter resources while ensuring performance and other Quality of Service (QoS) guarantees for HPC applications requires careful consideration of important and extremely challenging tradeoffs. An innovative application-centric energy-aware strategy for Virtual Machine (VM) allocation is presented. The proposed strategy ensures high resource utilization and energy efficiency through VM consolidation while satisfying application QoS. While existing VM allocation solutions are aimed at satisfying only the resource utilization requirements of applications along only one dimension (CPU utilization), the proposed approach is more generic as it employs knowledge obtained through application profiling along multiple dimensions. The results of our evaluation show that the proposed VM allocation strategy enables significant reduction either in energy consumption or in execution time, depending on the optimization goals.
机译:对于具有通常有针对性网格和传统HPC平台的传统高性能计算(HPC)工作负载,越来越多地考虑虚拟化数据中心和云。然而,最大限度地提高了数据中心资源的能源效率,成本效益和利用,同时确保HPC应用程序的性能和其他服务质量(QoS)保证需要仔细考虑重要且极具挑战性的权衡。提出了一种用于虚拟机(VM)分配的创新的应用中规范的能量感知策略。拟议的策略通过VM Consolidation确保了高资源利用率和能源效率,同时满足应用QoS。虽然现有的VM分配解决方案旨在仅符合一个维度(CPU利用率)的应用程序的资源利用率要求,但是所提出的方法是更通用的,因为它采用通过沿多个维度的应用程序分析获得的知识。我们的评价结果​​表明,取决于优化目标,所提出的VM分配策略能够显着降低能耗或执行时间。

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