Life Cycle Analysis for Emissions of Scientific Computing Centres
Wim Vanderbauwhede, Mattias Wadenstein
TL;DR
This work develops a time-dependent life cycle analysis (LCA) framework for scientific computing centres that jointly tracks embodied hardware emissions and runtime electricity emissions. It normalizes HPC capability using the HS23 benchmark, models expansion, replacement cycles, and heat reuse, and implements the model in Haskell for transparency and reproducibility, including a detailed embodied-carbon model for CPUs, memory, SSDs, GPUs, and infrastructure. Key findings show that cluster expansion and replacement cycles largely drive total emissions, with heat reuse offering substantial reductions, particularly in low-carbon electricity regions; the relative importance of embodied versus runtime emissions shifts with electricity carbon intensity. The framework provides a practical tool for HPC operators to optimise lifecycle emissions through hardware strategies and grid decarbonization, while highlighting that ever-growing capacity can defeat efficiency gains unless coupled with effective heat reuse and lower-carbon electricity.
Abstract
We propose a dedicated model to assist with the life cycle analysis of emissions of scientific computing centres. The model takes into account both the embodied carbon and emissions from use, as well as other factors such as data centre power usage efficiency, data centre expansion, hardware replacement, increase in energy efficiency of next-generation hardware, reduction in carbon intensity of the electricity supply and potential for heat reuse. If differs from existing models in its detailed handling of hardware embodied carbon and time dependency of various factors affecting the emissions. We present a number of scenarios where we apply the model to real-life HPC centres in different countries to illustrate how the trade-offs depend on the various factors and validate our model against the literature.