Increasing the Profit of Cloud Providers through DRAM Operation at Reduced Margins

2020 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID)(2020)

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Energy reduction is a key objective in cloud computing, and DRAM memories are responsible for an important amount of the energy consumption of data center nodes. Vendors adopt very conservative margins for DRAM operating parameters, such as the refresh rate and supply voltage, to guarantee correct operation even under the worst process variation and operating conditions. In this paper, we investigate the exploitation of DRAM margins to improve the energy efficiency of data center nodes, without triggering penalties due to service level agreement (SLA) violations. We introduce a model that captures the most important aspects of job management and system configuration. We also introduce RM-DRAM, a scheduling and node configuration policy that exploits the extended margins of DRAMs to reduce the operator’s cost, considering the tradeoff between the cost of energy consumption and potential SLA violations. RM-DRAM also employs cost-aware (rather than threshold-based) VM consolidation. We extract the parameters used in the simulation (particularly power consumption and error rates) by characterizing a commercial ARM-based server. We perform simulations to evaluate the effectiveness of our approach, showing that significant gains, up to 34.84% and 29.53% in energy and cost, respectively, can be achieved compared with a state-of-the-art policy.
DRAM reduced margins,energy efficiency,scheduling,cost effectiveness
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