Development Schedule

Release	Module	Feature
v0.1 Sep 2015	Neural Network	Feed forward neural network, including CNN, MLP
		RBM-like model, including RBM
		Recurrent neural network, including standard RNN
	Architecture	One worker group on single node (with data partition)
		Multi worker groups on single node using Hogwild
		Distributed Hogwild
		Multi groups across nodes, like Downpour
		All-Reduce training architecture like DeepImage
		Load-balance among servers
	Failure recovery	Checkpoint and restore
	Tools	Installation with GNU auto Tools
v0.2 Jan 2016	Neural Network	Feed forward neural network, including AlexNet, cuDNN layers,Tools
		Recurrent neural network, including GRULayer and BPTT
		Model partition and hybrid partition
	Tools	Integration with Mesos for resource management
		Prepare Docker images for deployment
		Visualization of neural net and debug information
	Binding	Python binding for major components
	GPU	Single node with multiple GPUs
v0.3 April 2016	GPU	Multiple nodes, each with multiple GPUs
		Heterogeneous training using both GPU and CPU CcT
		Support cuDNN v4
	Installation	Remove dependency on ZeroMQ, CZMQ, Zookeeper for single node training
	Updater	Add new SGD updaters including Adam, AdamMax and AdaDelta
	Binding	Enhance Python binding for training
v1.0 Sep 2016	Programming abstraction	Tensor with linear algebra, neural net and random operations
		Updater for distributed parameter updating
	Hardware	Use Cuda and Cudnn for Nvidia GPU
		Use OpenCL for AMD GPU or other devices
	Cross-platform	To extend from Linux to MacOS
		Large image models, e.g., VGG and Residual Net
v1.1 Jan 2017	Model Zoo	GoogleNet; Health-care models
	Caffe converter	Use SINGA to train models configured in caffe proto files
	Model components	Add concat and slice layers; accept multiple inputs to the net
	Compilation and installation	Windows suppport
		Simplify the installation by compiling protobuf and openblas together with SINGA
		Build python wheel automatically using Jenkins
		Install SINGA from Debian packages
v1.2 June 2018	AutoGrad	AutoGrad for BP
	Python 3	Support Python 3 for PySinga
	Models	Add popular models, including VGG, ResNet, DenseNet, InceptionNet