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新POLCA系统将LLM服务效率提升20% · 跟踪2个来源

作者 PulseAugur 编辑部 · [2 个来源] ·

研究人员开发了一种新的分布式LLM服务电源控制系统，可优化GPU能效。该系统名为POLCA，将预填充和解码阶段的电源管理解耦，这与应用单一设置的NVIDIA Max-Q配置文件不同。POLCA的基于模型的校准方法在每焦耳的令牌数和降低延迟方面取得了显著改进，在Qwen3-Coder-480B和Qwen3-235B-A22B等特定模型上超越了供应商配置文件。 AI

影响 优化LLM服务基础设施，可能降低运营成本并增加容量。

排序理由 学术论文，详细介绍了一种LLM服务基础设施的新技术方法。

在 Hugging Face Daily Papers 阅读 →

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新POLCA系统将LLM服务效率提升20% · 跟踪2个来源

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学术论文，详细介绍了一种LLM服务基础设施的新技术方法。
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报道来源 [2]

  1. arXiv cs.LG TIER_1 English(EN) · Jae Gon Kim, Donghoon Yoo, Hanyul Ryu, Sungho Ha, Juyeon Lee, Soojung Ryu ·

    解耦相位、模型校准的分布式大模型服务功率控制

    arXiv:2609.11133v1 Announce Type: new Abstract: Datacenter GPU power is the binding constraint on LLM serving capacity, and production serving has shifted to prefill/decode (PD) disaggregation. Deploying NVIDIA's Max-Q inference profile on a disaggregated B200 system, we found it…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    解耦相位、模型校准的分布式大模型服务功率控制

    Datacenter GPU power is the binding constraint on LLM serving capacity, and production serving has shifted to prefill/decode (PD) disaggregation. Deploying NVIDIA's Max-Q inference profile on a disaggregated B200 system, we found its realized gain modest (+8.6% tokens/J), model-d…

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