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Align tpu_codesign README introduction with the GfD launch blog post. #1

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gagika merged 1 commit into from
Nov 9, 2026
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Align tpu_codesign README introduction with the GfD launch blog post. #1

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2 changes: 1 addition & 1 deletion README.md
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[![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](LICENSE)

Practical, hardware-grounded architectural design principles, Mixture-of-Experts (MoE) co-design patterns, low-precision numerics rules, and distributed systems mappings for training and serving foundation models on Google Cloud TPUs (Ironwood / TPU v7x and future TPU generations).
Google designed TPUs from the ground up for machine learning efficiency and performance per total cost of ownership (TCO), trading general-purpose hardware scheduling for wide systolic arrays, dedicated SparseCore engines, and custom interconnect fabrics. This living guide provides practical, hardware-grounded architectural design principles, Mixture-of-Experts (MoE) co-design patterns, low-precision numerics rules, and distributed systems mappings for training and serving LLMs, MoEs, and other hardware-intensive workloads on Google Cloud TPUs (Ironwood / TPU v7x and future TPU generations).

* **Online Book & Blog:** <https://ai-hypercomputer.github.io/tpu-codesign/>
* **Single-Page Guide:** [`docs/guide.md`](docs/guide.md)
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