April updates
Beta API for model pipelining with multiple Edge TPUs
The Coral Team
April 1, 2020
We've just released an updated Edge TPU Compiler and a new C++ API to enable pipelining a single model across multiple Edge TPUs. This can improve throughput for high-speed applications and can reduce total latency for large models that cannot fit into the cache of a single Edge TPU. To use this API, you need to recompile your model to create separate .tflite files for each segment that runs on a different Edge TPU.
Here are all the changes included with this release:
- The Edge TPU Compiler is now version 2.1.
You can update by runningsudo apt-get update && sudo apt-get install edgetpu
, or follow the instructions here. - The model pipelining API is available as source in GitHub. (Currently in beta and available in C++ only.) For details, read our guide about how to pipeline a model with multiple Edge TPUs.
- New embedding extractor models for EfficientNet, for use with on-device backpropagation.
- Minor update to the Edge TPU Python library (now version 2.14) to add
new size parameter for
run_inference()
. - New Colab notebooks to build C++ examples.
Send us any questions or feedback at coral-support@google.com