Release Notes - SINGA - Version singa-incubating-0.3.0

SINGA is a general distributed deep learning platform for training big deep learning models over large datasets.

This release includes following features:

  * GPU Support
    * [SINGA-131] Implement and optimize hybrid training using both CPU and GPU
    * [SINGA-136] Support cuDNN v4
    * [SINGA-134] Extend SINGA to run over a GPU cluster
    * [Singa-157] Change the priority of cudnn library and install libsingagpu.so

  * Remove Dependencies
    * [SINGA-156] Remove the dependency on ZMQ for single process training
    * [SINGA-155] Remove zookeeper for single-process training

  * Python Binding
    * [SINGA-126] Python Binding for Interactive Training

  * Other Improvements
    * [SINGA-80] New Blob Level and Address Level Math Operation Interface
    * [SINGA-130] Data Prefetching
    * [SINGA-145] New SGD based optimization Updaters: AdaDelta, Adam, AdamMax

  * Bugs Fixed
    * [SINGA-148] Race condition between Worker threads and Driver
    * [SINGA-150] Mesos Docker container failed
    * [SIGNA-141] Undesired Hash collision when locating process id to worker…
    * [SINGA-149] Docker build fail
    * [Singa-143] The compilation cannot detect libsingagpu.so file


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Release Notes - SINGA - Version singa-incubating-0.2.0

SINGA is a general distributed deep learning platform for training big deep learning models over large datasets. It is
designed with an intuitive programming model based on the layer abstraction. SINGA supports a wide variety of popular
deep learning models.

This release includes following features:

  * Programming model
    * [SINGA-80] New Blob Level and Address Level Math Operation Interface
    * [SINGA-82] Refactor input layers using data store abstraction
    * [SINGA-87] Replace exclude field to include field for layer configuration
    * [SINGA-110] Add Layer member datavec_ and gradvec_
    * [SINGA-120] Implemented GRU and BPTT (BPTTWorker)

  * Neuralnet layers
    * [SINGA-91] Add SoftmaxLayer and ArgSortLayer
    * [SINGA-106] Add dummy layer for test purpose
    * [SINGA-120] Implemented GRU and BPTT (GRULayer and OneHotLayer)

  * GPU training support
    * [SINGA-100] Implement layers using CUDNN for GPU training
    * [SINGA-104] Add Context Class
    * [SINGA-105] Update GUN make files for compiling cuda related code
    * [SINGA-98] Add Support for AlexNet ImageNet Classification Model


  * Model/Hybrid partition
    * [SINGA-109] Refine bridge layers
    * [SINGA-111] Add slice, concate and split layers
    * [SINGA-113] Model/Hybrid Partition Support

  * Python binding
    * [SINGA-108] Add Python wrapper to singa

  * Predict-only mode
    * [SINGA-85] Add functions for extracting features and test new data

  * Integrate with third-party tools
    * [SINGA-11] Start SINGA on Apache Mesos
    * [SINGA-78] Use Doxygen to generate documentation
    * [SINGA-89] Add Docker support

  * Unit test
    * [SINGA-95] Add make test after building

  * Other improvment
    * [SINGA-84] Header Files Rearrange
    * [SINGA-93] Remove the asterisk in the log tcp://169.254.12.152:*:49152
    * [SINGA-94] Move call to google::InitGoogleLogging() from Driver::Init() to main()
    * [SINGA-96] Add Momentum to Cifar10 Example
    * [SINGA-101] Add ll (ls -l) command in .bashrc file when using docker
    * [SINGA-114] Remove short logs in tmp directory
    * [SINGA-115] Print layer debug information in the neural net graph file
    * [SINGA-118] Make protobuf LayerType field id easy to assign
    * [SIGNA-97] Add HDFS Store

  * Bugs fixed
    * [SINGA-85] Fix compilation errors in examples
    * [SINGA-90] Miscellaneous trivial bug fixes
    * [SINGA-107] Error from loading pre-trained params for training stacked RBMs
    * [SINGA-116] Fix a bug in InnerProductLayer caused by weight matrix sharing

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Features included in singa-incubating-0.1.0:

  * Job management
    * [SINGA-3] Use Zookeeper to check stopping (finish) time of the system
    * [SINGA-16] Runtime Process id Management
    * [SINGA-25] Setup glog output path
    * [SINGA-26] Run distributed training in a single command
    * [SINGA-30] Enhance easy-to-use feature and support concurrent jobs
    * [SINGA-33] Automatically launch a number of processes in the cluster
    * [SINGA-34] Support external zookeeper service
    * [SINGA-38] Support concurrent jobs
    * [SINGA-39] Avoid ssh in scripts for single node environment
    * [SINGA-43] Remove Job-related output from workspace
    * [SINGA-56] No automatic launching of zookeeper service
    * [SINGA-73] Refine the selection of available hosts from host list

  * Installation with GNU Auto tool
    * [SINGA-4] Refine thirdparty-dependency installation
    * [SINGA-13] Separate intermediate files of compilation from source files
    * [SINGA-17] Add root permission within thirdparty/install.
    * [SINGA-27] Generate python modules for proto objects
    * [SINGA-53] Add lmdb compiling options
    * [SINGA-62] Remove building scrips and auxiliary files
    * [SINGA-67] Add singatest into build targets

  * Distributed training
    * [SINGA-7] Implement shared memory Hogwild algorithm
    * [SINGA-8] Implement distributed Hogwild
    * [SINGA-19] Slice large Param objects for load-balance
    * [SINGA-29] Update NeuralNet class to enable layer partition type customization
    * [SINGA-24] Implement Downpour training framework
    * [SINGA-32] Implement AllReduce training framework
    * [SINGA-57] Improve Distributed Hogwild

  * Training algorithms for different model categories
    * [SINGA-9] Add Support for Restricted Boltzman Machine (RBM) model
    * [SINGA-10] Add Support for Recurrent Neural Networks (RNN)

  * Checkpoint and restore
    * [SINGA-12] Support Checkpoint and Restore

  * Unit test
    * [SINGA-64] Add the test module for utils/common

  * Programming model
    * [SINGA-36] Refactor job configuration, driver program and scripts
    * [SINGA-37] Enable users to set parameter sharing in model configuration
    * [SINGA-54] Refactor job configuration to move fields in ModelProto out
    * [SINGA-55] Refactor main.cc and singa.h
    * [SINGA-61] Support user defined classes
    * [SINGA-65] Add an example of writing user-defined layers

  * Other features
    * [SINGA-6] Implement thread-safe singleton
    * [SINGA-18] Update API for displaying performance metric
    * [SINGA-77] Integrate with Apache RAT

Some bugs are fixed during the development of this release
  * [SINGA-2] Check failed: zsock_connect
  * [SINGA-5] Server early terminate when zookeeper singa folder is not initially empty
  * [SINGA-15] Fixg a bug from ConnectStub function which gets stuck for connecting layer_dealer_
  * [SINGA-22] Cannot find openblas library when it is installed in default path
  * [SINGA-23] Libtool version mismatch error.
  * [SINGA-28] Fix a bug from topology sort of Graph
  * [SINGA-42] Issue when loading checkpoints
  * [SINGA-44] A bug when reseting metric values
  * [SINGA-46] Fix a bug in updater.cc to scale the gradients
  * [SINGA-47] Fix a bug in data layers that leads to out-of-memory when group size is too large
  * [SINGA-48] Fix a bug in trainer.cc that assigns the same NeuralNet instance to workers from diff groups
  * [SINGA-49] Fix a bug in HandlePutMsg func that sets param fields to invalid values
  * [SINGA-66] Fix bugs in Worker::RunOneBatch function and ClusterProto
  * [SINGA-79] Fix bug in singatool that can not parse -conf flag

Features planned for the next release
  * [SINGA-11] Start SINGA using Mesos
  * [SINGA-31] Extend Blob to support xpu (cpu or gpu)
  * [SINGA-35] Add random number generators
  * [SINGA-40] Support sparse Param update
  * [SINGA-41] Support single node single GPU training