✳flâneur — a map of the web's best reading

Introduction to Cloud TPU  |  Google Cloud

cloud.google.com · 1,011 words · saved by 1 readers

Tensor Processing Units (TPUs) are Google's custom-developed application-specific integrated circuits (ASICs) used to accelerate machine learning workloads. For more detailed information about TPU hardware, see System Architecture. Cloud TPU is a web service that makes TPUs available as scalable computing resources on Google Cloud. TPUs train your models more efficiently using hardware designed for performing large matrix operations often found in machine learning algorithms. TPUs have on-chip high-bandwidth memory (HBM) letting you use larger models and batch sizes. TPUs can be connected in groups called Pods that scale up your workloads with little to no code changes. We recommend starting your machine learning project with a single TPU and scale out to a TPU Pod slice for production. To get you started, you can use open source reference models that Google's research and engineering teams optimize for use with TPUs. For more information, see Reference models. To understand how TPUs w

Home Documentation AI and ML Cloud TPU Guides Send feedback Stay organized with collections Save and categorize content based on your preferences. Introduction to Cloud TPU Tensor Processing Units (TPUs) are Google's custom-developed, application-specific integrated circuits (ASICs) used to accelerate machine learning workloads. For more information about TPU hardware, see TPU architecture . TPUs efficiently train your models by using hardware designed for performing large matrix operations often found in machine learning algorithms. TPUs have on-chip high-bandwidth memory (HBM) letting you us

Explore this link on the map →

saved by

related reading