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.
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
Apache SINGA Supported Solutions
Exxact offers Apache SINGA pre-installed optionally in our line of Deep Learning Solutions. Each Exxact Deep Learning Solution is powered by leading hardware, software, and systems engineering. All Exxact Deep Learning Solutions are turn-key and designed for rapid development and deployment of deep neural networks.