Deep learning has shown outstanding performance in various machine learning tasks. However, the deep complex model structure and massive training data make it expensive to train.
We present a distributed deep learning system, called SINGA, for training big models over large datasets. An intuitive programming model based on the layer abstraction is provided, which supports a variety of popular deep learning models. SINGA architecture supports both synchronous and asynchronous training frameworks. Hybrid training frameworks can also be customized to achieve good scalability. SINGA provides different neural net partitioning schemes for training large models.
SINGA is an Apache Incubator project released under the Apache License version 2.0. The latest release of the framework can be accessed here.
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