Google DeepMind Releases 'How To Scale Your Model' Systems Guide
tetsuoai · x · 2026-08-10
Google DeepMind released an open-source guide titled How to Scale Your Model, aiming to demystify the "alchemy" of scaling LLM training and inference from a systems perspective.
The tutorial explores how TPUs and GPUs work and communicate, covering core topics including:
- Parallelism Schemes: Making informed choices about splitting computation across multiple devices at different scales.
- Cost Estimation: Estimating the time and memory required to train and serve large Transformer models.
- Hardware-Software Co-design: Designing algorithms that leverage specific hardware affordances and understanding hardware driven by algorithm bottlenecks.
Assuming a basic understanding of Transformers, this guide is ideal for engineers and researchers looking to grasp the underlying logic of massive distributed training.
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