Summary
Tensor Processing Units (TPUs) are application-specific integrated circuits (ASICs) developed by Google to accelerate machine learning workloads.
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TPUs offer over 100 petaflops of performance in a single pod
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, enough computational power to transform businesses or create research breakthroughs. TPUs are designed with Google's deep experience and leadership in machine learning.
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Summary
Cloud TPU is designed to run cutting-edge machine learning models with AI services on Google Cloud. And its custom high-speed network offers over 100 petaflops of performance in a single pod—enough computational power to transform your business or create the next research breakthrough.
Train and run machine learning models faster | Cloud TPU | Google Cloud
google.com
Summary
Tensor Processing Unit ( TPU ) is an AI accelerator application-specific integrated circuit (ASIC) developed by Google for neural network machine learning , using Google's own TensorFlow software
Tensor Processing Unit - Wikipedia
wikipedia.org
Summary
Tensor Processing Units (TPUs) are Google’s custom-developed application-specific integrated circuits (ASICs) used to accelerate machine learning workloads. TPUs are designed from the ground up with the benefit of Google’s deep experience and leadership in machine learning.
Cloud Tensor Processing Units (TPUs) | Google Cloud
google.com
Coral devices harness the power of Google's Edge TPU machine-learning coprocessor. This is a small ASIC built by Google that's specially-designed to execute ...
Edge TPU Devices
aiyprojects.withgoogle.com
Google CEO Sundar Pichai spoke for only one minute and 42 seconds about the company’s latest TPU v4 Tensor Processing Units during his keynote at the Google ...
Google Launches TPU v4 AI Chips
hpcwire.com
A single-board computer with a removable system-on-module (SoM) featuring the Edge TPU. Supported OS: Mendel Linux (derivative of Debian)
Products | Coral
coral.ai
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TPU Research Cloud
research.google
How Google TPUs work, how they provide exceptional performance for TensorFlow workloads, and how to make the most of TPU resources.
Google TPU
run.ai
