Artificial intelligence (AI), and particularly large language models, are rapidly advancing capabilities within a range of fields, from personal assistants to medical diagnosis to weather forecasting. This growth is supported by high-performance compute (HPC) datacenters, whose performance has been doubling every 2.5 years [1] and is likely to accelerate over time based on demands of future AI applications. These server-class systems consume energy equivalent to a medium-sized city, where significant power is used for data movement between the various modules, boards, racks, and clients throughout the datacenter. The rapidly growing needs of AI-driven compute require increasing communication bandwidth with the highest degree of energy efficiency across all levels of system integration.
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Turner et al. (2024) studied this question.
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