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# Download SINGA

* To verify the downloaded tar.gz file, download the [KEYS](https://www.apache.org/dist/incubator/singa/KEYS) and ASC files and then execute the following commands

        % gpg --import KEYS
        % gpg --verify downloaded_file.asc downloaded_file
  
  You can also check the SHA512 or MD5 values to see if the download is completed.


* Incubating v2.0.0 (20 April 2019):
    * [Apache SINGA 2.0.0 (incubating)](http://www.apache.org/dyn/closer.cgi/incubator/singa/2.0.0/apache-singa-incubating-2.0.0.tar.gz)
      [\[SHA512\]](https://www.apache.org/dist/incubator/singa/2.0.0/apache-singa-incubating-2.0.0.tar.gz.sha512)
      [\[ASC\]](https://www.apache.org/dist/incubator/singa/2.0.0/apache-singa-incubating-2.0.0.tar.gz.asc)
    * [Release Notes 2.0.0 (incubating)](releases/RELEASE_NOTES_2.0.0.html)
    * New features and major updates,
        * Enhance autograd (for Convolution networks and recurrent networks)
        * Support ONNX
        * Improve the CPP operations via Intel MKL DNN lib
        * Implement tensor broadcasting
        * Move Docker images under Apache user name
        * Update depdent lib versions in conda-build config
       

* Incubating v1.2.0 (6 June 2018):
    * [Apache SINGA 1.2.0 (incubating)](https://archive.apache.org/dist/incubator/singa/1.2.0/apache-singa-incubating-1.2.0.tar.gz)
      [\[SHA512\]](https://archive.apache.org/dist/incubator/singa/1.2.0/apache-singa-incubating-1.2.0.tar.gz.sha512)
      [\[ASC\]](https://archive.apache.org/dist/incubator/singa/1.2.0/apache-singa-incubating-1.2.0.tar.gz.asc)
    * [Release Notes 1.2.0 (incubating)](releases/RELEASE_NOTES_1.2.0.html)
    * New features and major updates,
        * Implement autograd (currently support MLP model)
        * Upgrade PySinga to support Python 3
        * Improve the Tensor class with the stride field
        * Upgrade cuDNN from V5 to V7
        * Add VGG, Inception V4, ResNet, and DenseNet for ImageNet classification
        * Create alias for conda packages
        * Complete documentation in Chinese
        * Add instructions for running Singa on Windows
        * Update the compilation, CI
        * Fix some bugs


* Incubating v1.1.0 (12 February 2017):
    * [Apache SINGA 1.1.0 (incubating)](https://archive.apache.org/dist/incubator/singa/1.1.0/apache-singa-incubating-1.1.0.tar.gz)
      [\[MD5\]](https://archive.apache.org/dist/incubator/singa/1.1.0/apache-singa-incubating-1.1.0.tar.gz.md5)
      [\[ASC\]](https://archive.apache.org/dist/incubator/singa/1.1.0/apache-singa-incubating-1.1.0.tar.gz.asc)
    * [Release Notes 1.1.0 (incubating)](releases/RELEASE_NOTES_1.1.0.html)
    * New features and major updates,
        * Create Docker images (CPU and GPU versions)
        * Create Amazon AMI for SINGA (CPU version)
        * Integrate with Jenkins for automatically generating Wheel and Debian packages (for installation), and updating the website.
        * Enhance the FeedFowardNet, e.g., multiple inputs and verbose mode for debugging
        * Add Concat and Slice layers
        * Extend CrossEntropyLoss to accept instance with multiple labels
        * Add image_tool.py with image augmentation methods
        * Support model loading and saving via the Snapshot API
        * Compile SINGA source on Windows
        * Compile mandatory dependent libraries together with SINGA code
        * Enable Java binding (basic) for SINGA
        * Add version ID in checkpointing files
        * Add Rafiki toolkit for providing RESTFul APIs
        * Add examples pretrained from Caffe, including GoogleNet


* Incubating v1.0.0 (8 September 2016):
    * [Apache SINGA 1.0.0 (incubating)](https://archive.apache.org/dist/incubator/singa/1.0.0/apache-singa-incubating-1.0.0.tar.gz)
      [\[MD5\]](https://archive.apache.org/dist/incubator/singa/1.0.0/apache-singa-incubating-1.0.0.tar.gz.md5)
      [\[ASC\]](https://archive.apache.org/dist/incubator/singa/1.0.0/apache-singa-incubating-1.0.0.tar.gz.asc)
    * [Release Notes 1.0.0 (incubating)](releases/RELEASE_NOTES_1.0.0.html)
    * New features and major updates,
        * Tensor abstraction for supporting more machine learning models.
        * Device abstraction for running on different hardware devices, including CPU, (Nvidia/AMD) GPU and FPGA (to be tested in later versions).
        * Replace GNU autotool with cmake for compilation.
        * Support Mac OS
        * Improve Python binding, including installation and programming
        * More deep learning models, including VGG and ResNet
        * More IO classes for reading/writing files and encoding/decoding data
        * New network communication components directly based on Socket.
        * Cudnn V5 with Dropout and RNN layers.
        * Replace website building tool from maven to Sphinx
        * Integrate Travis-CI


* Incubating v0.3.0 (20 April 2016):
    * [Apache SINGA 0.3.0 (incubating)](https://archive.apache.org/dist/incubator/singa/0.3.0/apache-singa-incubating-0.3.0.tar.gz)
      [\[MD5\]](https://archive.apache.org/dist/incubator/singa/0.3.0/apache-singa-incubating-0.3.0.tar.gz.md5)
      [\[ASC\]](https://archive.apache.org/dist/incubator/singa/0.3.0/apache-singa-incubating-0.3.0.tar.gz.asc)
    * [Release Notes 0.3.0 (incubating)](releases/RELEASE_NOTES_0.3.0.html)
    * New features and major updates,
        * [Training on GPU cluster](v0.3.0/gpu.html) enables training of deep learning models over a GPU cluster.
        * [Python wrapper improvement](v0.3.0/python.html) makes it easy to configure the job, including neural net and SGD algorithm.
        * [New SGD updaters](v0.3.0/updater.html) are added, including Adam, AdaDelta and AdaMax.
        * [Installation](v0.3.0/installation.html) has fewer dependent libraries for single node training.
        * Heterogeneous training with CPU and GPU.
        * Support cuDNN V4.
        * Data prefetching.
        * Fix some bugs.


* Incubating v0.2.0 (14 January 2016):
    * [Apache SINGA 0.2.0 (incubating)](https://archive.apache.org/dist/incubator/singa/0.2.0/apache-singa-incubating-0.2.0.tar.gz)
      [\[MD5\]](https://archive.apache.org/dist/incubator/singa/0.2.0/apache-singa-incubating-0.2.0.tar.gz.md5)
      [\[ASC\]](https://archive.apache.org/dist/incubator/singa/0.2.0/apache-singa-incubating-0.2.0.tar.gz.asc)
    * [Release Notes 0.2.0 (incubating)](releases/RELEASE_NOTES_0.2.0.html)
    * New features and major updates,
        * [Training on GPU](v0.2.0/gpu.html) enables training of complex models on a single node with multiple GPU cards.
        * [Hybrid neural net partitioning](v0.2.0/hybrid.html) supports data and model parallelism at the same time.
        * [Python wrapper](v0.2.0/python.html) makes it easy to configure the job, including neural net and SGD algorithm.
        * [RNN model and BPTT algorithm](v0.2.0/general-rnn.html) are implemented to support applications based on RNN models, e.g., GRU.
        * [Cloud software integration](v0.2.0/distributed-training.html) includes Mesos, Docker and HDFS.
        * Visualization of neural net structure and layer information, which is helpful for debugging.
        * Linear algebra functions and random functions against Blobs and raw data pointers.
        * New layers, including SoftmaxLayer, ArgSortLayer, DummyLayer, RNN layers and cuDNN layers.
        * Update Layer class to carry multiple data/grad Blobs.
        * Extract features and test performance for new data by loading previously trained model parameters.
        * Add Store class for IO operations.


* Incubating v0.1.0 (8 October 2015):
    * [Apache SINGA 0.1.0 (incubating)](https://archive.apache.org/dist/incubator/singa/apache-singa-incubating-0.1.0.tar.gz)
      [\[MD5\]](https://archive.apache.org/dist/incubator/singa/apache-singa-incubating-0.1.0.tar.gz.md5)
      [\[ASC\]](https://archive.apache.org/dist/incubator/singa/apache-singa-incubating-0.1.0.tar.gz.asc)
    * [Amazon EC2 image](https://console.aws.amazon.com/ec2/v2/home?region=ap-southeast-1#LaunchInstanceWizard:ami=ami-b41001e6)
    * [Release Notes 0.1.0 (incubating)](releases/RELEASE_NOTES_0.1.0.html)
    * Major features include,
        * Installation using GNU build utility
        * Scripts for job management with zookeeper
        * Programming model based on NeuralNet and Layer abstractions.
        * System architecture based on Worker, Server and Stub.
        * Training models from three different model categories, namely, feed-forward models, energy models and RNN models.
        * Synchronous and asynchronous distributed training frameworks using CPU
        * Checkpoint and restore
        * Unit test using gtest

**Disclaimer**

Apache SINGA is an effort undergoing incubation at The Apache Software
Foundation (ASF), sponsored by the name of Apache Incubator PMC. Incubation is
required of all newly accepted projects until a further review indicates that
the infrastructure, communications, and decision making process have stabilized
in a manner consistent with other successful ASF projects. While incubation
status is not necessarily a reflection of the completeness or stability of the
code, it does indicate that the project has yet to be fully endorsed by the
ASF.