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About

Deep learning frameworks such as TensorFlow, PyTorch, Caffe, Torch, Theano, and MXNet have contributed to the popularity of deep learning by reducing the effort and skills needed to design, train, and use deep learning models. Fabric for Deep Learning (FfDL, pronounced “fiddle”) provides a consistent way to run these deep-learning frameworks as a service on Kubernetes. The FfDL platform uses a microservices architecture to reduce coupling between components, keep each component simple and as stateless as possible, isolate component failures, and allow each component to be developed, tested, deployed, scaled, and upgraded independently. Leveraging the power of Kubernetes, FfDL provides a scalable, resilient, and fault-tolerant deep-learning framework. The platform uses a distribution and orchestration layer that facilitates learning from a large amount of data in a reasonable amount of time across compute nodes.

About

Transition seamlessly between eager and graph modes with TorchScript, and accelerate the path to production with TorchServe. Scalable distributed training and performance optimization in research and production is enabled by the torch-distributed backend. A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more. PyTorch is well supported on major cloud platforms, providing frictionless development and easy scaling. Select your preferences and run the install command. Stable represents the most currently tested and supported version of PyTorch. This should be suitable for many users. Preview is available if you want the latest, not fully tested and supported, 1.10 builds that are generated nightly. Please ensure that you have met the prerequisites (e.g., numpy), depending on your package manager. Anaconda is our recommended package manager since it installs all dependencies.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Neural networks experts looking for a solution to run deep-learning frameworks as a service on Kubernetes

Audience

Researchers in need of an open source machine learning solution to accelerate research prototyping and production deployment

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

IBM
Founded: 1911
United States
developer.ibm.com/open/projects/fabric-for-deep-learning-ffdl/

Company Information

PyTorch
Founded: 2016
pytorch.org

Alternatives

Alternatives

Core ML

Core ML

Apple
Create ML

Create ML

Apple
DeepSpeed

DeepSpeed

Microsoft
AWS Neuron

AWS Neuron

Amazon Web Services

Categories

Categories

Integrations

Amazon Elastic Inference
Amazon SageMaker Studio Lab
Flyte
GPUEater
Gemma 3
HPC-AI
HStreamDB
HunyuanWorld
IREN Cloud
Kubernetes
MLReef
MegaETH
NVIDIA DeepStream SDK
NeevCloud
SynapseAI
Torch
Unremot
Yandex DataSphere
Zilliz Cloud

Integrations

Amazon Elastic Inference
Amazon SageMaker Studio Lab
Flyte
GPUEater
Gemma 3
HPC-AI
HStreamDB
HunyuanWorld
IREN Cloud
Kubernetes
MLReef
MegaETH
NVIDIA DeepStream SDK
NeevCloud
SynapseAI
Torch
Unremot
Yandex DataSphere
Zilliz Cloud
Claim Fabric for Deep Learning (FfDL) and update features and information
Claim Fabric for Deep Learning (FfDL) and update features and information
Claim PyTorch and update features and information
Claim PyTorch and update features and information