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SINGA graduates to Top-Level Apache Project

We are excited and pleased to announce that Apache SINGA, a distributed machine and deep learning platform [1], is now an Apache Top-Level Project (TLP). The Apache Software Foundation (ASF) board has passed the resolution for SINGA to graduate from the Apache Incubator to become a top-level project on 16 Oct 2019, based on the evidence that SINGA’s community has grown, diversified and adapted to the Apache way.

The SINGA project was initiated by the DB System Group at the National University of Singapore (NUS) School of Computing in 2014, in collaboration with the database group of Zhejiang University and NetEase[4]. It focused on distributed deep learning by partitioning the model and data onto nodes in a cluster and parallelize the training. The prototype was submitted to Apache Incubator in March 2015 and in October 2015 [1].

About Apache SINGA

Apache SINGA is a usable, flexible, and scalable distributed deep learning platform for big data analytics. It provides optimization techniques, GPU support, and a simple, intuitive programming model that makes it accessible even to non-experts.

Apache SINGA is in use at organizations such as Carnegie Technologies, CBRE, Citigroup, JurongHealth Hospital, National University of Singapore, National University Hospital, NetEase, Noblis, Shentilium Technologies, Singapore General Hospital, Tan Tock Seng Hospital, YZBigData, and others. Apache SINGA is used across applications in banking, education, finance, healthcare, real estate, software development, and other categories

SINGA-auto, SINGA-easy and SINGA-lite

The SINGA team also developed SINGA-auto (a.k.a. RAFIKI) and SINGA-easy (a.k.a. PANDA) extensions. SINGA-auto provides AutoML services such as model construction, hyper-parameter tuning, model training and inference. Users can simply upload their datasets and configure the service to conduct training and then deploy the model for inference. As a cloud service system, SINGA manages the hardware resources and failure recovery. It speeds up hyper-parameter tuning by distributed tuning to achieve almost linear scalability. SINGA-easy allows people without much artificial intelligence (AI) knowledge to use AI technology with ease. SINGA-easy empowers a domain expert such as a doctor/clinician to fuse his domain knowledge into AI systems.  SINGA-lite is being developed for edge computing and the 5G environment.

Apache SINGA community will continue to develop and improve to broaden its use, usability, efficiency, and scalability. Should you wish to have more information, please contact Dr. Wang Wei (wangwei@comp.nus.edu.sg).  Downloads, documentation, and ways to be involved with the project can be found on the Apache SINGA Web site. http://singa.incubator.apache.org/

Apache Software Foundation

The Apache Software Foundation is the world’s largest open-source foundation and incubators of more than 350 Open Source projects and initiatives. After graduation, most top-level Apache projects become enterprise-grade software, benefiting millions of users worldwide. Graduation is a terrific milestone, but only the beginning for much wider adoption.


[1] https://en.wikipedia.org/wiki/Apache_SINGA

[2] https://www.opengovasia.com/apache-singa-flexible-and-scalable-deep-learning-platform-developed-by-nus-big-data-systems-team/



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