| Release Notes - SINGA - Version singa-incubating-0.3.0 |
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| SINGA is a general distributed deep learning platform for training big deep learning models over large datasets. |
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| This release includes following features: |
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| * 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 |
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| * Remove Dependencies |
| * [SINGA-156] Remove the dependency on ZMQ for single process training |
| * [SINGA-155] Remove zookeeper for single-process training |
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| * Python Binding |
| * [SINGA-126] Python Binding for Interactive Training |
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| * 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 |
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| * 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 |
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| 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) |
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| * 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 |
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| * Model/Hybrid partition |
| * [SINGA-109] Refine bridge layers |
| * [SINGA-111] Add slice, concate and split layers |
| * [SINGA-113] Model/Hybrid Partition Support |
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| * Python binding |
| * [SINGA-108] Add Python wrapper to singa |
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| * Predict-only mode |
| * [SINGA-85] Add functions for extracting features and test new data |
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| * Integrate with third-party tools |
| * [SINGA-11] Start SINGA on Apache Mesos |
| * [SINGA-78] Use Doxygen to generate documentation |
| * [SINGA-89] Add Docker support |
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| * Unit test |
| * [SINGA-95] Add make test after building |
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| * 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 |
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| * 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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| ----------------------------------------- |
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| Features included in singa-incubating-0.1.0: |
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| * 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 |
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| * 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 |
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| * 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) |
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| * Checkpoint and restore |
| * [SINGA-12] Support Checkpoint and Restore |
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| * Unit test |
| * [SINGA-64] Add the test module for utils/common |
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| * 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 |
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| * Other features |
| * [SINGA-6] Implement thread-safe singleton |
| * [SINGA-18] Update API for displaying performance metric |
| * [SINGA-77] Integrate with Apache RAT |
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| 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 |
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| 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 |
