How to Fine‑Tune Large Models on Multiple Nodes and GPUs – A Must‑Know Interview Answer

This article explains how to fine‑tune large models across multiple machines and GPUs by covering data, model, tensor, and pipeline parallelism, hybrid 3D parallel strategies, engineering details such as NCCL, PyTorch Distributed, DeepSpeed, fault‑tolerance, checkpointing, and the ZeRO optimizer stages that dramatically reduce memory usage.

Data ParallelDeepSpeedDistributed Training

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How to Fine‑Tune Large Models on Multiple Nodes and GPUs – A Must‑Know Interview Answer

Alibaba Cloud Infrastructure

Apr 16, 2025 · Artificial Intelligence

Optimizing Multi‑Node Distributed LLM Inference with ACK Gateway and vLLM

This article presents a step‑by‑step guide for deploying and optimizing large‑language‑model inference across multiple GPU‑enabled nodes using ACK Gateway with Inference Extension, vLLM’s tensor‑ and pipeline‑parallel techniques, and Kubernetes resources such as LeaderWorkerSet, PVCs, and custom routing policies, followed by performance benchmarking and analysis.

ACK GatewayDistributed inferenceKubernetes

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Optimizing Multi‑Node Distributed LLM Inference with ACK Gateway and vLLM