SINGA is an Apache incubating project for developing an open source machine learning library. It provides a flexible architecture for scalable distributed training, is extensible to run a wide range of hardware, and has a focus on health-care applications.
The SINGA project was initiated by the DB System Group at the National University of Singapore in 2014. It focuses on distributed learning by partitioning the model and data onto nodes in a cluster and parallelize the training.   The prototype was accepted by Apache Incubator in March 2015. Five versions have been released as shown in the following table. Since V1.0, SINGA is general to support traditional machine learning models such as logistic regression. Companies like NetEase  and Shentilium are using SINGA for their applications.
|Version||Original release date||Latest version||Release date|
Older version, still supported
SINGA’s software stack includes three major components, namely, core, IO and model. The following figure illustrates these components together with the hardware. The core component provides memory management and tensor operations; IO has classes for reading (and writing) data from (to) disk and network; The modeling of the modeling model is based on the modeling of the model.
- List of Apache Software Foundation projects
- Comparison of deep learning software
- Jump up^ Ooi, Beng Chin; Tan, Kian-Lee; Sheng, Wang; Wang, Wei; Cai, Qingchao; Chen, Gang; Gao, Jinyang; Luo, Zhaojing; Tung, Anthony KH; Wang, Yuan; Xie, Zhongle; Zhang, Meihui; Zheng, Kaiping (2015). “SINGA: A distributed deep learning platform” (PDF) . ACM Multimedia . Doi : 10.1145 / 2733373.2807410 . Retrieved 8 September 2016 .
- Jump up^ Wei, Wang; Chen, Gang; Anh Dinh, Tien Tuan; Gao, Jinyang; Ooi, Beng Chin; Tan, Kian-Lee; Sheng, Wang (2015). “SINGA: putting deep learning in the hands of multimedia users” (PDF) . ACM Multimedia . Doi :10.1145 / 2733373.2806232 . Retrieved 8 September 2016 .
- Jump up^ </s> . “网易 携手 Apache SINGA 角逐 人工智能 新 战场 网易 科技” . Tech.163.com . Retrieved 2017-06-03 .