Efinix offers a TinyML platform based on an open-source TensorFlow Lite for Microcontrollers (TFLite Micro) C++ library running on the Sapphire RISC-V SoC with the Efinix TinyML Accelerator.
Open Source
Field Reconfigurable
Free AI Framework
High Performance and Low Power
There is a drive to push Artificial Intelligence (AI) closer to the network edge where it can operate on data with lower latency and increased context. Power and compute resources are at a premium at the edge however and compute hungry AI algorithms find it hard to deliver the performance required. The open source community has developed TensorFlow lite that creates a quantized version of standard TensorFlow models and, using a library of functions, enables them to run on microcontrollers at the far edge. The Efinix TinyML platform takes these TensorFlow Lite models and, using the custom instruction capabilities of the Sapphire core, accelerates them in the FPGA hardware to dramatically improve their performance while retaining a low power and small footprint .
TensorFlow, the TensorFlow logo and any related marks are trademarks of Google Inc.
Efinix presents a flexible and scalable RISC-V based TinyML platform with various acceleration strategies:
Efinix provides an end-to-end design flow that facilitates the deployment of TinyML applications on Efinix FPGAs.The design flow encompasses all aspects of the flow from AI model training, post-training quantization, all the way to running inference on RISC-V with a custom TinyML accelerator. In addition, we are also showing the steps to deploy TinyML on Efinix highly flexible domain-specific framework.
To further explore Efinix TinyML Platform: