Energy Proportionality in Near-Threshold Computing Servers and Cloud Data Centers: Consolidating or Not?
Ali Pahlevan1,a, Yasir Mahmood Qureshi1,b, Marina Zapater1,c, Andrea Bartolini2,e, Davide Rossi3, Luca Benini2,f and David Atienza1,d
1Embedded Systems Laboratory (ESL), Swiss Federal Institute of Technology Lausanne (EPFL), Switzerland
aali.pahlevan@epfl.ch
byasir.qureshi@epfl.ch
cmarina.zapater@epfl.ch
ddavid.atienza@epfl.ch
2Swiss Federal Institute of Technology Zurich (ETHZ), Switzerland
ebarandre@iis.ee.ethz.ch
flbenini@iis.ee.ethz.ch
3University of Bologna (Unibo), Italy
davide.rossig@unibo.it
ABSTRACT
Cloud Computing aims to efficiently tackle the increasing demand of computing resources, and its popularity has led to a dramatic increase in the number of computing servers and data centers worldwide. However, as effect of post‐Dennard scaling, computing servers have become power‐limited, and new system‐level approaches must be used to improve their energy efficiency. This paper first presents an accurate power modelling characterization for a new server architecture based on the FDSOI process technology for near‐threshold computing (NTC). Then, we explore the existing energy vs. performance trade‐offs when virtualized applications with different CPU utilization and memory footprint characteristics are executed. Finally, based on this analysis, we propose a novel dynamic virtual machine (VM) allocation method that exploits the knowledge of VMs characteristics together with our accurate server power model for next‐generation NTC‐based data centers, while guaranteeing quality of service (QoS) requirements. Our results demonstrate the inefficiency of current workload consolidation techniques for new NTC‐based data center designs, and how our proposed method provides up to 45% energy savings when compared to state‐of‐the‐art consolidation‐based approaches.
