If you are new to developing on Arm, read our getting started guides for application developer software and embedded software development. Jump to section:
Frameworks supported by Arm
Arm supports a wide array of machine learning frameworks. If you have requirements that are not yet supported by our fully optimized stack, you can choose from a range of frameworks and libraries.
Facebook framework with optimized routines for Arm CPUs with Neon.
Microsoft Cognitive Toolkit
Microsoft framework with optimized routines for Arm CPUs with Neon.
A high-level neural networks API, written in Python and capable of running on top of several framework backends including TensorFlow and Microsoft Cognitive Toolkit (CNTK).Learn more
Type: Keras backend
Vertex.ai OpenCL framework compatible with Keras API with support for Arm Mali GPU.
Arm software products maximize the performance of your machine learning applications.
Arm Keil MDK is the most comprehensive software development solution for Arm-based microcontrollers and includes all components that you need to create, build, and debug embedded applications.Learn more
Application development software
Arm NN is the Arm inference engine. Arm NN is designed to optimally run networks that are trained on popular frameworks, like TensorFlow and Caffe, on Arm IP.Learn more
Arm Compute Library
Arm Compute Library optimizes low-level functions for computer vision and machine learning. Arm Compute Library focuses on Convolutional Neural Networks for 32-bit float and 9-bit integers across an array of Arm CPUs and GPUs.Learn more
Embedded development software
CMSIS-NN is the Arm library of efficient neural network kernels for Arm Cortex-M CPUs.Learn more
DSP extensions for Arm
DSP extensions for Cortex-M
Cortex-M processors with DSP provide a high level of signal processing and integer performance, while maintaining the energy-efficiency and ease-of-use hallmarks of the Cortex-M family.Learn more
DSP extensions for Cortex-R
This instruction set for Cortex-R processors includes enhanced DSP instructions that improve execution performance for arithmetic operations.
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|Suggested answer||Pytorch framework for Arm NN (CMSIS)||0 votes||2528 views||3 replies||Latest 17 days ago by Karl Fezer||Answer this|
|Suggested answer||A good ML Conference||0 votes||2492 views||4 replies||Latest 18 days ago by asksolutions01||Answer this|
|Not answered||Example cpp running onnx on arm NN||0 votes||957 views||0 replies||Started 1 months ago by Gushgush||Answer this|
|Not answered||Which CMSIS-DSP parts are used by CMSIS-NN||0 votes||530 views||0 replies||Started 2 months ago by trembel||Answer this|
|Suggested answer||Pytorch framework for Arm NN (CMSIS) Latest 17 days ago by Karl Fezer||3 replies 2528 views|
|Suggested answer||A good ML Conference Latest 18 days ago by asksolutions01||4 replies 2492 views|
|Not answered||Example cpp running onnx on arm NN Started 1 months ago by Gushgush||0 replies 957 views|
|Not answered||Which CMSIS-DSP parts are used by CMSIS-NN Started 2 months ago by trembel||0 replies 530 views|