DeepMind releases book on scaling LLMs on TPUs, demystifying performance optimization
TheZachMueller · x · 2026-08-24
Google DeepMind has released a new online book titled "How To Scale Your Model," which provides a systems-level view of running Large Language Models on TPUs. The text aims to demystify the science behind scaling models, covering hardware operations, inter-device communication, and parallelization strategies.
Key topics include:
- Performance Analysis: Using Roofline models to gauge how close model components are to theoretical optima.
- Parallelism Schemes: Guidance on choosing between data, tensor, and pipeline parallelism at different scales.
- Cost Estimation: Methods to estimate the memory, time, and financial costs of training and serving models.
- Co-design: Designing algorithms for specific hardware constraints and vice versa.
The book assumes a basic understanding of LLMs and JAX, targeting engineers looking to optimize performance at massive scale.
More from Infra
- How Microsoft optimized Windows for Nvidia's Arm-based RTX Spark AI laptops — tomwarren · 2026-10-15
- How Microsoft optimized Windows for Nvidia's Arm-based RTX Spark laptops — The Verge AI · 2026-10-15
- Global smartphone shipments plunge 22% in worst quarterly decline on record as AI demand fuels memory costs — Polymarket · 2026-10-15
- SK Hynix drops 11% again, now below 3x FY2027 earnings as AI memory selloff deepens — JOBhakdi · 2026-10-15
- ASML Sells Zero Lithography Machines into Europe as US Hosts 75%+ of AI Compute — NinaDSchick · 2026-10-15
- Nvidia quietly reclassified SPCX as 'Hyperscale', signaling deeper neocloud reliance — RihardJarc · 2026-10-15