TPU Architecture: How Google’s AI Chip Revolutionizes Machine Learning
Tensor Processing Units (TPUs) represent a revolutionary leap in AI hardware architecture, fundamentally transforming how we process machine learning workloads. Unlike traditional CPUs and GPUs, these custom-designed chips optimize matrix multiplication operations—the cornerstone of deep learning calculations—delivering up to 50x better performance and energy efficiency in AI tasks.
Developed by Google in 2016, TPUs execute complex neural network computations through a systolic array architecture, where data flows through thousands of arithmetic logic units (ALUs) in a choreographed pattern. This unique …










