Edge TPU
Google’s purpose-built ASIC designed to run inference at the edge.
AI at the edge
AI is pervasive today, from consumer to enterprise applications. With the explosive growth
of connected devices, combined with a demand for privacy/confidentiality, low latency and
bandwidth constraints, AI models trained in the cloud increasingly need to be run at the
edge. Edge TPU is Google’s purpose-built ASIC designed to run AI at the edge. It delivers
high performance in a small physical and power footprint, enabling the deployment of
high-accuracy AI at the edge.
End-to-end AI infrastructure
Edge TPU complements Cloud TPU and Google Cloud services to provide an end-to-end,
cloud-to-edge, hardware + software infrastructure for facilitating the deployment of
customers' AI-based solutions.
High performance in a small physical and power footprint
Thanks to its performance, small footprint, and low power, Edge TPU enables the broad
deployment of high-quality AI at the edge.
Co-design of AI hardware, software and algorithms
Edge TPU isn't just a hardware solution, it combines custom hardware, open software,
and state-of-the-art AI algorithms to provide high-quality, easy to deploy AI solutions
for the edge.
A broad range of applications
Edge TPU can be used for a growing number of industrial use-cases such as predictive
maintenance, anomaly detection, machine vision, robotics, voice recognition, and many more.
It can be used in manufacturing, on-premise, healthcare, retail, smart spaces,
transportation, etc.
An open, end-to-end infrastructure for deploying AI solutions
The Edge TPU allows you to deploy high-quality ML inferencing at the edge, using various
prototyping and production products from Coral.
The Coral platform for ML at the edge augments Google's
Cloud TPU and Cloud IoT to provide an end-to-end (cloud-to-edge, hardware + software)
infrastructure to facilitate the deployment of customers' AI-based solutions. In addition to its
open-source TensorFlow Lite programming environment, the Coral platform provides a complete
developer toolkit so you can compile your own models or retrain several Google AI models for the
Edge TPU, combining Google's expertise in both AI and hardware.
Edge TPU complements CPUs, GPUs, FPGAs, and other ASIC solutions for running AI at the edge.
|
Edge
(Devices/nodes, Gateways, Servers)
|
Google Cloud | |
|---|---|---|
| Tasks | ML inference | ML training and inference |
| Software, services | Linux, Windows |
AI Platform, Kubernetes Engine,
Compute Engine, Cloud IoT Core
|
| ML frameworks | TensorFlow Lite, NN API |
TensorFlow, scikit-learn,
XGBoost, Keras
|
| Hardware accelerators | Edge TPU, GPU, CPU | Cloud TPU, GPU, and CPU |
Edge TPU features
This ASIC is the first step in a roadmap that will leverage Google's AI expertise to follow and reflect in hardware the rapid evolution of AI.
| Type | Inference Accelerator |
| Performance Example | Edge TPU enables users to execute state-of-the-art mobile vision models such as MobileNet v2 at nearly 400 FPS, in a power efficient manner. See model benchmarks. |
| Numerics | Int8 |
| IO Interface | PCIe, USB |
Get started
Build with Edge TPU using the development board, which includes an Edge TPU SoM and a
carrier board.
Learn about Edge TPU products from Coral
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Products listed on this page are in beta. For more information on our product
launch stages, see
here.