ml-tpu-google-2016

IN premise — entries/2026/06/21/wiki-Machine_learning-chunk-6.md

Created 2026-06-21T09:55:51+00:00

Tensor Processing Units (TPUs) are Google-designed ASICs optimized for tensor/matrix computations using matrix multiplication units and high-bandwidth memory, introduced in 2016

Dependents

These beliefs depend on this one:

• IN ml-hardware-diversification-beyond-cpu — ML training hardware has diversified from general-purpose CPUs into at least three specialized architectures — GPUs (parallel matrix ops), TPUs (tensor-optimized ASICs), and neuromorphic chips (memristor-based) — each optimized for different computational patterns.