A Holistic Model of the Performance and the Energy-Efficiency of Hypervisors in an HPC Environment

With a growing concern on the considerable energy consumed by HPC platforms and data centers, research efforts are targeting toward green approaches with higher energy efficiency. In particular, virtualization is emerging as the prominent approach to mutualize the energy consumed by a single server running multiple Virtual Machines (VMs) instances. However, little understanding has been obtained about the potential overhead in energy consumption and the throughput reduction for virtualized servers and/or computing resources, nor if it simply suits an environment as high-demanding as a High Performance Computing (HPC) platform. In this paper, a novel holistic model for the power of HPC node and its eventual virtualization layer is proposed. More importantly, we create and validate an instance of the proposed model using concrete measures taken on the Grid5000 platform. In particular, we use three widespread virtualization frameworks, namely Xen, KVM, and VMware ESXi and compare them with a baseline environment running in native mode. The conducted experiments were performed on top of benchmarking tools that reflect an HPC usage, i.e. HPCC, IOZone and Bonnie++. To abstract from the specifics of a single architecture, the benchmarks were run using two different hardware configurations, based on Intel and AMD processors. The benchmark scores are presented for all configurations to highlight their varying performance. The measured data is used to create a statistical holistic model of power of a machine that takes into account impacts of its components utilization metrics, as well as used application, virtualization, and hardware. The purpose of the model is to enable estimation of energy consumption of HPC platforms in areas such as simulation, scheduling or accounting.