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Sustainable Data Centres

Track Description

Data centers are at the core of modern digital infrastructure, powering an array of critical applications from cloud computing and high-performance simulations to artificial intelligence and emerging quantum computing technologies. Despite their critical importance, the rapid expansion and increasingly intensive computational demands of these facilities contribute significantly to global environmental challenges, particularly through substantial energy consumption, resource depletion, and electronic waste generation. To address these pressing concerns, environmental computing seeks innovative approaches to minimize the ecological footprint of data centers by integrating state-of-the-art computational methods and sustainable operational strategies.
This special track invites comprehensive discussions on reducing environmental impacts through enhanced efficiency in data centers, focusing also on cutting-edge computing paradigms. By exploring the intersection of environmental informatics, computational efficiency, and future-oriented technologies, the track aims to foster interdisciplinary collaboration and promote sustainable computational practices that are economically feasible and ecologically responsible.

Objectives

  • Explore advanced computational methods to optimize energy efficiency and reduce resource use in data centers.
  • Investigate the environmental impacts associated with emerging computational technologies.
  • Encourage research on sustainable software development practices and energy-efficient system architectures.
  • Facilitate interdisciplinary dialogue among computer scientists, environmental experts, and industry professionals to address environmental computing challenges.
  • Promote the development and dissemination of methodologies for assessing and mitigating the ecological impact of computational infrastructure.

Topics of Interest

  • Sustainable data center operations and green IT solutions.
  • AI-driven techniques for optimizing computational resource utilization.
  • Energy-aware acceleration integration into sustainable infrastructures.
  • Environmental impact assessment and lifecycle management for computing hardware.
  • Machine learning algorithms for real-time resource monitoring and optimization.
  • Data-driven strategies for predicting and minimizing the ecological footprint of data centers.
  • Novel cooling and resource management technologies tailored for advanced computing environments.

Special Track Chair

  • Maximilian Höb, Leibniz Supercomputing Centre LRZ, maximilian.hoeb@lrz.de
  • Dieter Kranzlmüller, Leibniz Supercomputing Centre LRZ