This analysis examines energy consumption and carbon emissions of HPC systems, suggesting pathways for sustainability.
High-Performance Computing (HPC) is increasingly pivotal for scientific discovery, technolog- ical innovation, and economic competitiveness. However, its rapidly escalating energy consumption and consequent carbon footprint present profound environmental challenges that demand rigorous assessment and proactive mitigation. This study develops and applies an integrated modeling framework to compre- hensively estimate and project the multifaceted environmental impact of global HPC operations. Employing Autoregressive Integrated Moving Average (ARIMA) models, meticulously selected based on the Corrected Akaike Information Criterion (AICc), we forecast future energy consumption trajectories for distinct data center archetypes: hyperscale, cloud, and legacy facilities. The intricate relationships between HPC energy utilization, key macroeconomic indicators (such as Gross Domestic Product, population growth, and rates of technological progress), and resultant CO2 emissions are systematically analyzed, with causal linkages explored through Granger causality tests. Our projections indicate a persistent upward trend in global HPC energy consumption, although the growing integration of renewable and nuclear energy sources into elec- tricity grids offers a partial, yet insufficient, mitigating effect. The research further extends the modeling to quantitatively assess the potential for carbon emission reductions attributable to accelerated renewable en- ergy deployment, revealing that while achieving a 100% renewable energy supply for HPC remains a distant, multi-decadal prospect, substantial and impactful emission reductions are attainable in the near to medium term through concerted policy and investment. The analysis also critically examines the substantial water footprint of HPC, particularly for cooling large-scale data centers, thereby highlighting significant resource allocation and sustainability concerns, especially in water-stressed regions. Based on these comprehensive empirical findings, a suite of actionable technical and policy recommendations is formulated to guide the transition towards more sustainable HPC development. These include advancements in hardware energy effi- ciency, strategic promotion of renewable energy procurement, enhanced software and workload optimization, and fostering international cooperation on green computing standards. This research underscores the exi- gent need for a holistic, system-level approach to managing the ecological footprint of HPC, ensuring that its profound benefits to society are realized in a manner consistent with global environmental sustainability imperatives and climate change mitigation goals.
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WANG et al. (2025) studied this question.
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