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None ModeSwitch-LLM: A Lightweight Phase-Aware Controller for Cross-Mode LLM Inference on a Single GPU

ModeSwitch-LLM 提升单GPU LLM推理效率

作者 PulseAugur 编辑部 · [2 sources] ·

研究人员开发了ModeSwitch-LLM，这是一种轻量级的控制器，旨在提高单个GPU上大型语言模型推理的效率。该系统根据工作负载特征，动态地将请求路由到各种推理模式，包括量化、推测和混合配置。在Meta-Llama-3.1-8B-Instruct上的评估表明，与标准的FP16相比，延迟速度提高了2.10倍，每token的能耗降低了51.7%，同时保持了近乎等效的准确性。 AI

影响 提高了单GPU上LLM的推理效率，可能降低运营成本并增加可访问性。

排序理由 发表了一篇学术论文，详细介绍了一种提高LLM推理效率的新方法。

在 arXiv cs.CL 阅读 →

AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →

报道来源 [2]

  1. arXiv cs.CL TIER_1 · Aman Sunesh, Ali Alshehhi, Hivansh Dhakne ·

    ModeSwitch-LLM: A Lightweight Phase-Aware Controller for Cross-Mode LLM Inference on a Single GPU

    arXiv:2605.23057v1 Announce Type: cross Abstract: ModeSwitch-LLM is a lightweight request-boundary controller for improving single-GPU large language model inference efficiency by routing each request to an appropriate fixed inference mode. Instead of relying on one static servin…

  2. arXiv cs.CL TIER_1 · Hivansh Dhakne ·

    ModeSwitch-LLM: A Lightweight Phase-Aware Controller for Cross-Mode LLM Inference on a Single GPU

    ModeSwitch-LLM is a lightweight request-boundary controller for improving single-GPU large language model inference efficiency by routing each request to an appropriate fixed inference mode. Instead of relying on one static serving configuration, the system selects among FP16, qu…

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