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.

TensorFlow

Type: Framework

Google framework with optimized 32-bit and 8-bit NEON routines for Arm CPUs.
Includes an OpenCL backend supporting Arm Mali GPU via SYCL.

TensorFlow Arm setup guide

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PyTorch

Type: Framework

Facebook framework with optimized routines for Arm CPUs with Neon.



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MxNet

Type: Framework

Apache framework with optimized routines for Arm CPUs.
Open AI version optimized with the Arm Compute Library for CPUs and GPUs.

MxNet GitHub

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Microsoft Cognitive Toolkit

Type: Framework

Microsoft framework with optimized routines for Arm CPUs with Neon.



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Caffe

Type: Framework

Berkley Vision and Learning Centre framework with several options for running on Arm.
CaffeOnACL is a version optimized with the Arm Compute Library for CPUs and GPUs.

CaffeOnACL GitHub

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Keras

Type: API

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).

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PlaidML

Type: Keras backend

Vertex.ai OpenCL framework compatible with Keras API with support for Arm Mali GPU.

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Arm SDKs

Arm software products maximize the performance of your machine learning applications.

Keil MDK

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.

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Application development software

Arm NN

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.

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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.

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Embedded development software

CMSIS-NN

CMSIS-NN is the Arm library of efficient neural network kernels for Arm Cortex-M CPUs.

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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.

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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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Community Forums

Suggested answer Pytorch framework for Arm NN (CMSIS)
  • Arm NN
  • CMSIS-NN
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
  • CMSIS
  • 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