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papersSEP 10 04:00 UTC

PELM paper proposes speculative decoding and DVFS for power-efficient on-device LLM inference

A new arXiv paper introduces PELM, a system aimed at making large language model inference more power-efficient on mobile devices. The approach combines speculative decoding with dynamic voltage and frequency scaling to reduce the energy demands of running LLMs at the edge, where privacy, personalization, and lower latency are key motivations.

PELMdvfsedge AIon-device-llm-inferencepower-efficient-aispeculative-decoding

COVERAGE · 2 REPORTS · LINKS GO TO THE ORIGINAL OUTLETS

arXiv cs.CLPELM: Power Efficient On-Device LLM Inference with Speculative Decoding and Dynamic Voltage Frequency Scaling ↗SEP 10 04:00 UTC
arXiv cs.LGPELM: Power Efficient On-Device LLM Inference with Speculative Decoding and Dynamic Voltage Frequency Scaling ↗SEP 10 04:00 UTC

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