Software for Machine Learning on Arm

There are many ways to deploy neural networks on mobile and embedded platforms, from a full framework to low-level primitives that enable you to implement your architecture directly. Get started quickly and easily on Arm hardware.

  • Arm NN

    Arm's inference engine, designed to run networks trained on popular frameworks – such as TensorFlow and Caffe – optimally on Arm IP.

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  • Compute Library

    Arm's optimized low-level functions for computer vision and machine learning, focusing on CNNs for 32-bit float and 8-bit integer across a wide array of Arm CPUs and GPUs.

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  • CMSIS-NN

    Arm's library of efficient neural network kernels for Arm Cortex-M CPUs.

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Frameworks supported by Arm

Arm supports a wide array of machine learning frameworks. If you have requirements that aren't 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 (CNTK)

    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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  • Caffe2

    Type: Framework

    Facebook framework with optimized routines for Arm CPUs with NEON.

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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 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 libraries and SDKs

Arm provides software products to maximize your Machine Learning applications' performance and minimize time-to-market:

  • DSP extensions for Arm

    The Arm DSP instruction set extensions increase the DSP processing capability of Arm solutions in high-performance applications.

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  • Keil MDK

    Arm Development Studio gives you a core set of tools for efficient and reliable application development.

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Architecture

  • DynamIQ

    DynamIQ technology redefines the multi-core microarchitecture for the industry and is the foundation for future Arm Cortex-A processors.

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  • Neon

    Arm Neontechnology is an advanced SIMD architecture that is great for many applications such as image processing, computer vision, and machine learning.

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  • Scalable Vector Extension (SVE)

    SVE is the next-generation SIMD instruction set for the Arm architecture.

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Tools

Is your preferred framework or library missing from this list? Email ml@arm.com and let us know!

How-to guides

Learn to develop machine learning applications using Arm-based products and tools with our how-to guides. 

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Webinars

Discover tips and techniques for your Arm-based machine learning projects with our growing bank of webinars.

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White papers

To learn more about machine learning on Arm, see our range of available white papers and research papers.

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