M3SA: Exploring Datacenter Performance and Climate-Impact with Multi- and Meta-Model Simulation and Analysis

Datacenters are vital for the digital society but represent a considerable fraction of global energy consumption. To improve their sustainability and performance when demand is foreseen to increase, we envision simulators will become primary decision-making tools. However, unlike other fields focusing on key societal infrastructure such as waterworks and mass transit, datacenter simulators cannot yet combine multiple, independent models into their operation. Addressing this challenge, in this work we propose M3SA, a datacenter simulation and analysis framework that uses discrete-event simulation to predict, per model and then combined into a meta-model, the impact on climate and performance of various realistic datacenter conditions. We design an architecture for simulating multiple concurrent models, a technique to integrate the results of multiple models into a meta-model, and a procedure to evaluate the accuracy of the meta-model. Through experiments with a prototype, we show that (i) M3SA can be used to reproduce peer-reviewed experiments, and enhance their output with more diverse metrics and more detailed analysis; (ii) M3SA can be configured with a variety of realistic parameters, such as diverse workload traces (using Grid Workloads Archive data in our experiments), and energy production data such as carbon intensity over time and location (gCO2/kWh data across all EU regions, from ENTSO-E); (iii) M3SA enables various types of what-if and how-to analysis, such as how to configure CO2-aware migration over yearly energy-production patterns. M3SA has been integrated into the open-source software simulator OpenDC and is available on https://github.com/atlarge-research/opendc-m3sa.