APACHE SINGA

Apache SINGA Overview

Apache SINGA is a general distributed deep learning platform for training big deep learning models over large datasets. It is designed with an intuitive programming model based on the layer abstraction. A variety of popular deep learning models are supported, namely feed-forward models including convolutional neural networks (CNN), energy models like restricted Boltzmann machine (RBM), and recurrent neural networks (RNN). Many built-in layers are provided for users.

SINGA architecture is sufficiently flexible to run synchronous, asynchronous and hybrid training frameworks. SINGA also supports different neural net partitioning schemes to parallelize the training of large models, namely partitioning on batch dimension, feature dimension or hybrid partitioning.

SINGA Highlights

As flexible and scalable deep learning platform, SINGA serves as an incredibly valuable tool for big data analytics by providing the following features:

  • Supports various deep learning models and has the flexibility to allow users to customize the models that fit their business requirements
  • Provides a scalable architecture to train deep learning models from huge volumes of data
  • Serves a simple programming model for making the distributed training process transparent to users

Exxact Deep Learning GPU Solutions


Our deep learning GPU solutions are powered by the leading hardware, software, and systems engineering. Each system comes with our pre-installed deep learning software stack and are fully turnkey to run right out of the box.



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