OpenDC-STEAM: Realistic Modeling and Systematic Exploration of Composable Techniques for Sustainable Datacenters

Fuente: arXiv
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Autori principali: Niewenhuis, Dante, Talluri, Sacheendra, Iosup, Alexandru, de Matteis, Tiziano
Natura: Preprint
Pubblicazione: 2026
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author Niewenhuis, Dante
Talluri, Sacheendra
Iosup, Alexandru
de Matteis, Tiziano
author_facet Niewenhuis, Dante
Talluri, Sacheendra
Iosup, Alexandru
de Matteis, Tiziano
contents The need to reduce datacenter carbon footprint is urgent. While many sustainability techniques have been proposed, they are often evaluated in isolation, using limited setups or analytical models that overlook real-world dynamics and interactions between methods. This makes it challenging for researchers and operators to understand the effectiveness and trade-offs of combining such techniques. We design OpenDC-STEAM, an open-source customizable datacenter simulator, to investigate the individual and combined impact of sustainability techniques on datacenter operational and embodied carbon emissions, and their trade-off with performance. Using STEAM, we systematically explore three representative techniques - horizontal scaling, leveraging batteries, and temporal shifting - with diverse representative workloads, datacenter configurations, and carbon-intensity traces. Our analysis highlights that datacenter dynamics can influence their effectiveness and that combining strategies can significantly lower emissions, but introduces complex cost-emissions-performance trade-offs that STEAM can help navigate. STEAM supports the integration of new models and techniques, making it a foundation framework for holistic, quantitative, and reproducible research in sustainable computing. Following open-science principles, STEAM is available as FOSS: https://github.com/atlarge-research/OpenDC-STEAM.
format Preprint
id arxiv_https___arxiv_org_abs_2603_12381
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle OpenDC-STEAM: Realistic Modeling and Systematic Exploration of Composable Techniques for Sustainable Datacenters
Niewenhuis, Dante
Talluri, Sacheendra
Iosup, Alexandru
de Matteis, Tiziano
Distributed, Parallel, and Cluster Computing
The need to reduce datacenter carbon footprint is urgent. While many sustainability techniques have been proposed, they are often evaluated in isolation, using limited setups or analytical models that overlook real-world dynamics and interactions between methods. This makes it challenging for researchers and operators to understand the effectiveness and trade-offs of combining such techniques. We design OpenDC-STEAM, an open-source customizable datacenter simulator, to investigate the individual and combined impact of sustainability techniques on datacenter operational and embodied carbon emissions, and their trade-off with performance. Using STEAM, we systematically explore three representative techniques - horizontal scaling, leveraging batteries, and temporal shifting - with diverse representative workloads, datacenter configurations, and carbon-intensity traces. Our analysis highlights that datacenter dynamics can influence their effectiveness and that combining strategies can significantly lower emissions, but introduces complex cost-emissions-performance trade-offs that STEAM can help navigate. STEAM supports the integration of new models and techniques, making it a foundation framework for holistic, quantitative, and reproducible research in sustainable computing. Following open-science principles, STEAM is available as FOSS: https://github.com/atlarge-research/OpenDC-STEAM.
title OpenDC-STEAM: Realistic Modeling and Systematic Exploration of Composable Techniques for Sustainable Datacenters
topic Distributed, Parallel, and Cluster Computing
url https://arxiv.org/abs/2603.12381