mirror of https://github.com/hpcaitech/ColossalAI
[readme] sync CN readme (#766)
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Colossal-AI 为您提供了一系列并行训练组件。我们的目标是让您的分布式 AI 模型训练像普通的单 GPU 模型一样简单。我们提供的友好工具可以让您在几行代码内快速开始分布式训练。
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- 数据并行
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- 流水线并行
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- 1维, 2维, 2.5维, 3维张量并行
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- 序列并行
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- 友好的 trainer 和 engine
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- 可扩展新的并行方式
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- 混合精度
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- 零冗余优化器 (ZeRO)
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- 并行化策略
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- 数据并行
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- 流水线并行
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- 1维, [2维](https://arxiv.org/abs/2104.05343), [2.5维](https://arxiv.org/abs/2105.14500), [3维](https://arxiv.org/abs/2105.14450) 张量并行
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- [序列并行](https://arxiv.org/abs/2105.13120)
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- [零冗余优化器 (ZeRO)](https://arxiv.org/abs/2108.05818)
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- 异构内存管理
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- [PatrickStar](https://arxiv.org/abs/2108.05818)
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- 使用友好
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- 基于参数文件的并行化
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<p align="right">(<a href="#top">返回顶端</a>)</p>
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## 展示样例
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### ViT
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<p align="center">
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<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/ViT.png" width="450" />
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</p>
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- 14倍批大小和5倍训练速度(张量并行=64)
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### GPT-3
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<p align="center">
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<img src="https://raw.githubusercontent.com/hpcaitech/public_assets/main/colossalai/img/GPT3.png" width=700/>
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</p>
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- 释放 50% GPU 资源占用, 或 10.7% 加速
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@ -76,15 +76,15 @@ distributed training in a few lines.
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- Parallelism strategies
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- Data Parallelism
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- Pipeline Parallelism
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- 1D, [2D](https://arxiv.org/abs/2104.05343), [2.5D](https://arxiv.org/abs/2105.14500), 3D Tensor parallelism
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- [Sequence parallelism](https://arxiv.org/abs/2105.13120)
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- 1D, [2D](https://arxiv.org/abs/2104.05343), [2.5D](https://arxiv.org/abs/2105.14500), [3D](https://arxiv.org/abs/2105.14450) Tensor Parallelism
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- [Sequence Parallelism](https://arxiv.org/abs/2105.13120)
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- [Zero Redundancy Optimizer (ZeRO)](https://arxiv.org/abs/2108.05818)
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- Heterogeneous Memory Menagement
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- [PatrickStar](https://arxiv.org/abs/2108.05818)
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- Friendly Usage
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- Configuration file based
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- Parallelism based on configuration file
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<p align="right">(<a href="#top">back to top</a>)</p>
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