ThirstyFLOPS: Water Footprint Modeling and Analysis Toward Sustainable HPC Systems

2025-09-30

AI Summary

While high-performance computing (HPC) systems increasingly rely on water-intensive cooling and electricity generation—exacerbating regional water stress—their water footprint remains understudied compared to carbon emissions. Method: This paper introduces the first regionally resolved water footprint framework for HPC, integrating local electricity generation mix and watershed-level water scarcity to quantify total water consumption across both cooling and power generation. It proposes novel metrics—including Water Usage Effectiveness (WUE)—and establishes the first systematic linkage among energy efficiency (PUE), energy–water factor (EWF), and total water footprint. Contribution/Results: Empirical modeling across four representative systems (Marconi, Fugaku, and two others) reveals that nuclear energy share and geographic location critically govern water sustainability. The framework provides a practical, quantifiable tool for planning, evaluating, and governing green HPC infrastructure, offering actionable insights for policymakers and facility operators.

Technology Category

• Machine Learning: Hardware-aware ML
• Data Mining & Knowledge Management: Scalability, Parallel & Distributed Systems
• Humans and AI: Other Foundations of Human Computation & AI

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Sustainability and carbon-aware systems for Web, mobile, and WoT
• Responsible Web: Sustainability and climate impact of web technologies
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics

Abstract

High-performance computing (HPC) systems are becoming increasingly water-intensive due to their reliance on water-based cooling and the energy used in power generation. However, the water footprint of HPC remains relatively underexplored-especially in contrast to the growing focus on carbon emissions. In this paper, we present ThirstyFLOPS - a comprehensive water footprint analysis framework for HPC systems. Our approach incorporates region-specific metrics, including Water Usage Effectiveness, Power Usage Effectiveness, and Energy Water Factor, to quantify water consumption using real-world data. Using four representative HPC systems - Marconi, Fugaku, Polaris, and Frontier - as examples, we provide implications for HPC system planning and management. We explore the impact of regional water scarcity and nuclear-based energy strategies on HPC sustainability. Our findings aim to advance the development of water-aware, environmentally responsible computing infrastructures.

Problem

• Modeling water footprint of water-intensive HPC systems
• Analyzing regional water scarcity impact on computing sustainability
• Developing water-aware metrics for HPC planning and management

Innovation

• Framework models water footprint for HPC systems
• Uses region-specific metrics to quantify water consumption
• Analyzes impact of water scarcity and energy strategies