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Project Summary

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.

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artificial_neural_networks cluster CNN CUDA cudnn deep_learning distributed gpu large_datasets large_scale machine_learning multiple_gpu opencl partitioning RBM RNN scalable

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In a Nutshell, incubator-singa...

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Project Security

Vulnerabilities per Version ( last 10 releases )

There are no reported vulnerabilities

Project Vulnerability Report

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About Project Security

Languages

C++
50%
Python
43%
10 Other
7%

30 Day Summary

Jan 1 2025 — Jan 31 2025

12 Month Summary

Jan 31 2024 — Jan 31 2025
  • 208 Commits
    Up + 62 (42%) from previous 12 months
  • 33 Contributors
    Up + 17 (106%) from previous 12 months

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