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EnerInfer Optimizes Energy Use for On-Device LLM Inference
EnerInfer addresses the energy and thermal costs of on-device LLM inference by exploiting configuration slack to reduce NPU and memory usage without sacrificing performance. This challenges the common assumption that faster decoding speed is always preferable.
Reducing energy consumption and thermal output is crucial for practical, privacy-preserving on-device LLM deployment. EnerInfer's approach enables more cost-effective and reliable inference on edge devices.
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Score 70
Source Type arxiv
Reposts 0
Topic Quality 59
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