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Mastering Tensor Processing Units: High-Performance Deep Learning with Google TPU Architecture, Training, and Inference
Paperback
Publisher: Independently Published
Published: Sep 20 2025
Pages: 218
Weight: 0.78
Height: 0.46 Width: 6.69 Depth: 9.61
Language: English
Mastering Tensor Processing Units: High-Performance Deep Learning with Google TPU Architecture, Training, and Inference
Artificial intelligence is evolving at breakneck speed, and the demand for specialized hardware to train and deploy massive models has never been higher. Google's Tensor Processing Units (TPUs) are at the forefront of this revolution, powering some of the most advanced AI systems in the world-from large language models and image recognition networks to recommendation engines and real-time inference pipelines.
This book is your definitive guide to understanding, programming, and optimizing TPUs for high-performance deep learning. Whether you are a researcher, engineer, or advanced practitioner, you'll gain the knowledge needed to harness TPUs for both experimentation and production.
Inside, you'll explore:
- TPU Architecture Demystified - Learn how the Matrix Multiply Unit (MXU), high-bandwidth memory (HBM), and TPU Pods work together to accelerate machine learning at scale.
- The TPU Software Ecosystem - Understand the role of the XLA compiler, TensorFlow integration, and support for JAX and PyTorch-XLA.
- Training and Inference on TPUs - Build, fine-tune, and deploy models efficiently using best practices for batch sizing, static shapes, and distributed strategies.
- Scaling Across TPU Pods - Unlock the power of thousands of interconnected TPU chips for large-scale model training and deployment.
- Optimization and Profiling - Learn how to maximize throughput, minimize bottlenecks, and design TPU-friendly pipelines.
- Real-World Applications and Case Studies - See how TPUs are used in products like Google Search, Translate, and YouTube recommendations, and how enterprises and researchers apply them in finance, healthcare, and beyond.
- The Future of AI Hardware - Explore emerging trends such as sparsity, quantization, energy-efficient design, and inference-specialized TPUs like Ironwood.
With step-by-step tutorials, real-world examples, and practical coding demonstrations, this book equips you with the tools to make TPUs a powerful part of your machine learning workflow. If you're serious about scaling deep learning models and want to stay ahead in the age of AI acceleration, this book is an essential resource.
Unlock the full potential of Google TPUs, get your copy today and start building high-performance AI systems that push the boundaries of what's possible.
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