MXNetThe Apache Software Foundation
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Related Products
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About
A hybrid front-end seamlessly transitions between Gluon eager imperative mode and symbolic mode to provide both flexibility and speed. Scalable distributed training and performance optimization in research and production is enabled by the dual parameter server and Horovod support. Deep integration into Python and support for Scala, Julia, Clojure, Java, C++, R and Perl. A thriving ecosystem of tools and libraries extends MXNet and enables use-cases in computer vision, NLP, time series and more. Apache MXNet is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision-making process have stabilized in a manner consistent with other successful ASF projects. Join the MXNet scientific community to contribute, learn, and get answers to your questions.
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About
GPUs bring data in and out quickly, but have little locality of reference because of their small caches. They are geared towards applying a lot of compute to little data, not little compute to a lot of data. The networks designed to run on them therefore execute full layer after full layer in order to saturate their computational pipeline (see Figure 1 below). In order to deal with large models, given their small memory size (tens of gigabytes), GPUs are grouped together and models are distributed across them, creating a complex and painful software stack, complicated by the need to deal with many levels of communication and synchronization among separate machines. CPUs, on the other hand, have large, much faster caches than GPUs, and have an abundance of memory (terabytes). A typical CPU server can have memory equivalent to tens or even hundreds of GPUs. CPUs are perfect for a brain-like ML world in which parts of an extremely large network are executed piecemeal, as needed.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Developers and researchers requiring an open-source deep learning framework for research prototyping and production
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Audience
Companies doing AI and ML development
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
No information available.
Free Version
Free Trial
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Pricing
No information available.
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationThe Apache Software Foundation
Founded: 1999
United States
mxnet.apache.org
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Company InformationNeural Magic
Founded: 2018
United States
neuralmagic.com
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Alternatives |
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Categories |
Categories |
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Integrations
AWS Elastic Fabric Adapter (EFA)
AWS Marketplace
Amazon EC2 Inf1 Instances
Amazon EC2 P4 Instances
Amazon Elastic Inference
Amazon SageMaker Debugger
Amazon SageMaker Model Building
Cameralyze
Flower
GPUonCLOUD
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Integrations
AWS Elastic Fabric Adapter (EFA)
AWS Marketplace
Amazon EC2 Inf1 Instances
Amazon EC2 P4 Instances
Amazon Elastic Inference
Amazon SageMaker Debugger
Amazon SageMaker Model Building
Cameralyze
Flower
GPUonCLOUD
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