I found an example using ARM-NN with Cortex-A board. The output of ARM-NN is a .so file and can load easily to Cortex-A board. However, Cortex-M board doesn't support any system to load .so file. So, I would like to know is it possible to use ARM-NN for converting a Tensorflow model to a CMSIS-NN model and run on a Cortex-M board.
  • A Machine Learning Convolutional Neural Network operation has a proven 5x boost on the Cortex-M platform using the CMSIS-NN software framework. Please refer to Arm Developer link below for more information on Arm ML solutions and don't hesitate to comment below if you have any further questions. Read about Arm ML solutions
  • This user manual describes the CMSIS NN software library, a collection of efficient neural network kernels developed to maximize the performance and minimize the memory footprint of neural networks on Cortex-M processor cores. The library is divided into a number of functions each covering a specific category: Neural Network Convolution Functions
  • This document is Non-Confidential. The right to use, copy and disclose this document may be subject to license restrictions in accordance with the terms of the agreement entered into by Arm and the party that Arm delivered this document to.
  • BOverview. CMSIS Packs are a Keil/ARM technology, intended to handle distribution of software and documentation in Keil MDK. The main difference from usual libraries or source archives is that the actual source/object files are accompanied by some form of metadata, defining, among other things, the registers and peripherals definitions.
  • C Arm Mbed OS is a free, open-source embedded operating system that includes all the necessary features to facilitate the development of IoT connected products, including standards-based security and connectivity stacks, an RTOS kernel, middleware for storage and networking, and remote device management.
  • This user manual describes the CMSIS NN software library, a collection of efficient neural network kernels developed to maximize the performance and minimize the memory footprint of neural networks on Cortex-M processor cores. The library is divided into a number of functions each covering a specific category: Neural Network Convolution Functions
  • Arm Education comprises of the Arm University Program, Arm Education Media and the Arm School Program. Books. Arm Education books appeal to students and learners as they progress from novices to experts in Arm-based system design. Research. Arm Research Program supports academic and industrial researchers across a wide range of disciplines.
  • Version Description ; V1.2.0 : Added depthwise convolution function with asymmetric quantization. arm_depthwise_conv_u8_basic_ver1 ; Added support functions for requantization.
  • Oct 11, 2018 · Finally, there was a bug in the CMSIS-NN code from ARM that has now been fixed which was previously causing issues with running your own CNN. It has now been fixed on the master of the OpenMV Cam GitHub. Anyway, we're going to try to get an IDE release out with all these fixes along with new CNN examples now that we've documented how to do things.
  • DCMSIS-NN. In order to fully take advantage of our microcontroller's capabilities let's use the CMSIS-NN optimized libraries, available open source on GitHub.You will make use of CMSIS-NN, a collection of efficient neural network kernels developed to maximize the performance and minimize the memory footprint of neural networks on Arm Cortex-M processor cores.
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