Table of Contents
Fetching ...

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

Radu Nicolae, Dante Niewenhuis, Sacheendra Talluri, Alexandru Iosup

Abstract

Datacenters are vital to our digital society, but consume a considerable fraction of global electricity and demand is projected to increase. To improve their sustainability and performance, we envision that simulators will become primary decision-making tools. However, and unlike other fields focusing on key societal infrastructure such as waterworks and mass transit, datacenter simulators do not yet combine multiple independent models into their operation and thus suffer from issues associated with singular models, such as specialization, and lack of adaptability to operational phenomena. To address this challenge, we propose M3SA, a datacenter simulation and analysis framework that uses discrete-event simulation to predict, for each model, the impact on climate and performance under various realistic datacenter conditions, and then combines these predictions. We design an architecture for simulating multiple concurrent models (Multi-Model), a technique for integrating the results of multiple models into a Meta-Model, and a procedure for quantifying Meta-Model accuracy. Through experiments with an M3SA prototype, we show that (i) M3SA can reproduce and enhance peer-reviewed experiments; (ii) M3SA can predict operational phenomena (e.g., failures) of datacenters, running fundamentally different workload traces; (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 simulator OpenDC and is available at: https://github.com/atlarge-research/opendc-m3sa.

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

Abstract

Datacenters are vital to our digital society, but consume a considerable fraction of global electricity and demand is projected to increase. To improve their sustainability and performance, we envision that simulators will become primary decision-making tools. However, and unlike other fields focusing on key societal infrastructure such as waterworks and mass transit, datacenter simulators do not yet combine multiple independent models into their operation and thus suffer from issues associated with singular models, such as specialization, and lack of adaptability to operational phenomena. To address this challenge, we propose M3SA, a datacenter simulation and analysis framework that uses discrete-event simulation to predict, for each model, the impact on climate and performance under various realistic datacenter conditions, and then combines these predictions. We design an architecture for simulating multiple concurrent models (Multi-Model), a technique for integrating the results of multiple models into a Meta-Model, and a procedure for quantifying Meta-Model accuracy. Through experiments with an M3SA prototype, we show that (i) M3SA can reproduce and enhance peer-reviewed experiments; (ii) M3SA can predict operational phenomena (e.g., failures) of datacenters, running fundamentally different workload traces; (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 simulator OpenDC and is available at: https://github.com/atlarge-research/opendc-m3sa.

Paper Structure

This paper contains 19 sections, 1 equation, 31 figures, 8 tables.

Figures (31)

  • Figure 1: M3SA Multi-Model simulation uses multiple models simultaneously. M3SA Meta-Model integrates all results. \ref{['fig:exp1:A-B-C:results']} depicts a specific scenario.
  • Figure 2: System model for datacenter operation adapted from DBLP:journals/tpds/AndreadisMBI22. Simulation enables fine-grained datacenter operational monitoring used by stakeholders in decision-making processes.
  • Figure 3: Architecture of M3SA, a Multi- and Meta- Model Simulation Analyzer, integrated with a black-boxed simulator.
  • Figure 4: Sample M3SA plots. We represent singular models in gray and Meta-Models in green. In (A),(B): vertical axis depicts simulated metric, horizontal depicts time. In (C): vertical axis depicts model identifier, horizontal depicts cumulative totals.
  • Figure 5: Window size 5 applied on $n$ entries, using aggregation function $F$.
  • ...and 26 more figures