English(EN) Sharding vs replicas across multiple GPUs, just trying to plan this right [R]

AI 从业者争论多 GPU 设置中的分片与副本

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-12 13:01

一位 r/MachineLearning 上的用户正在寻求关于优化多 GPU 设置以适应 AI 工作负载的建议。他们正在争论是将大型模型分片到多个 GPU 上，还是在负载均衡器后运行更小的独立实例。核心问题围绕着在考虑模型大小、VRAM 以及权重和 KV 缓存的实际内存需求等因素的情况下，平衡单请求延迟与并发性。 AI

影响提供了关于在多 GPU 系统上优化 AI 模型部署的实际考虑因素的见解。

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r/MachineLearning TIER_1 English(EN) · /u/hulakrtahukhula · 2026-11-12 13:01

跨多GPU分片与副本，只是想正确规划一下[R]

<div class="md"><p>Hey all, I’m planning a small multi-GPU setup across two boxes, with a mix of long-context and short-chat workloads. Should a bigger model be sharded across all the cards, or is it better to run smaller independent instances per card and load-bal…

本文如何被排名

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跨多GPU分片与副本，只是想正确规划一下[R]

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