An analytical model for GPU power identifies architecture- and workload-dependent transition frequencies beyond which energy efficiency degrades, based on benchmarks on A40/A100/H100/H200 GPUs.
In: ICC 2025 - IEEE International Conference on Communications
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The paper surveys energy efficiency strategies for Agentic AI inference by proposing a new accounting framework and taxonomy that spans model simplification, computation control, input optimization, and cross-layer co-design with wireless networks.
The report assembles abstracts of invited talks, presentations, and posters from the FFCS conference on foundational limits and emerging paradigms in communication.
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