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Fun with Large Models
Fun with Large Models
Aug 30, 2025 · Artificial Intelligence

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
0 likes · 8 min read
How to Fine‑Tune Large Models on Multiple Nodes and GPUs – A Must‑Know Interview Answer
Huawei Cloud Developer Alliance
Huawei Cloud Developer Alliance
Jul 17, 2023 · Artificial Intelligence

How MindSpore’s Auto Parallel Tech Simplifies Large-Model Training

During a livestream titled “Solving the ‘Development Difficulty’ of Large Models with MindSpore Auto Parallel”, Huawei’s MindSpore experts explained how the framework’s distributed training techniques—including data, model, and pipeline parallelism as well as memory‑saving strategies—enable efficient pre‑training of trillion‑parameter models across diverse AI domains.

Data ParallelDistributed TrainingMindSpore
0 likes · 6 min read
How MindSpore’s Auto Parallel Tech Simplifies Large-Model Training