Apache MXNet

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Apache MXNet
Developer(s)Apache Software Foundation
Stable release
1.9.1[1] / 10 May 2022; 8 months ago (10 May 2022)
Repository
Written inC++, Python, R, Java, Julia, JavaScript, Scala, Go, Perl
Operating systemWindows, macOS, Linux
TypeLibrary for machine learning and deep learning
LicenseApache License 2.0
Websitemxnet.apache.org

Apache MXNet is an open-source deep learning software framework, used to train and deploy deep neural networks. It is scalable, allowing for fast model training and supports a flexible programming model and multiple programming languages (including C++, Python, Java, Julia, MATLAB, JavaScript, Go, R, Scala, Perl, and Wolfram Language). The MXNet library is portable and can scale to multiple GPUs[2] as well as multiple machines. It was co-developed by Carlos Guestrin at University of Washington (along with GraphLab).[3]

Features[edit]

Apache MXNet is a scalable deep learning framework that supports deep learning models, such as; convolutional neural networks (CNNs) and long short-term memory networks (LSTMs).

Scalable[edit]

MXNet can be distributed on dynamic cloud infrastructure using a distributed parameter server (based on research at Carnegie Mellon University, Baidu, and Google[4]). With multiple GPUs or CPUs the framework approaches linear scale.

Flexible[edit]

MXNet supports both imperative and symbolic programming. The framework allows developers to track, debug, save checkpoints, modify hyperparameters, and perform early stopping.

Multiple languages[edit]

MXNet supports Python, R, Scala, Clojure, Julia, Perl, MATLAB and JavaScript for front-end development, and C++ for back-end optimization.

Portable[edit]

Supports an efficient deployment of a trained model to low-end devices for inference, such as mobile devices (using Amalgamation[5]), Internet of things devices (using AWS Greengrass), serverless computing (using AWS Lambda) or containers. These low-end environments can have only weaker CPU or limited memory (RAM), and should be able to use the models that were trained on a higher-level environment (GPU based cluster, for example).

Cloud Support[edit]

MXNet is supported by public cloud providers including Amazon Web Services (AWS)[6] and Microsoft Azure.[7] Amazon has chosen MXNet as its deep learning framework of choice at AWS.[8][9] Currently, MXNet is supported by Intel, Baidu, Microsoft, Wolfram Research, and research institutions such as Carnegie Mellon, MIT, the University of Washington, and the Hong Kong University of Science and Technology.[10]

See also[edit]

References[edit]

  1. ^ "Release 1.9.1". 10 May 2022. Retrieved 30 June 2022.
  2. ^ "Building Deep Neural Networks in the Cloud with Azure GPU VMs, MXNet and Microsoft R Server". Microsoft. Retrieved 13 May 2017.
  3. ^ https://homes.cs.washington.edu/~guestrin/open-source.html
  4. ^ "Scaling Distributed Machine Learning with the Parameter Server" (PDF). Retrieved 2014-10-08.
  5. ^ "Amalgamation". Archived from the original on 2018-08-08. Retrieved 2018-05-08.
  6. ^ "Apache MXNet on AWS - Deep Learning on the Cloud". Amazon Web Services, Inc. Retrieved 13 May 2017.
  7. ^ "Building Deep Neural Networks in the Cloud with Azure GPU VMs, MXNet and Microsoft R Server". Microsoft TechNet Blogs. Retrieved 6 September 2017.
  8. ^ "MXNet - Deep Learning Framework of Choice at AWS - All Things Distributed". www.allthingsdistributed.com. 22 November 2016. Retrieved 13 May 2017.
  9. ^ "Amazon Has Chosen This Framework to Guide Deep Learning Strategy". Fortune. Retrieved 13 May 2017.
  10. ^ "MXNet, Amazon's deep learning framework, gets accepted into Apache Incubator". Retrieved 2017-03-08.