| #singa-incubating-0.2.0 Release Notes |
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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. |
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| This release includes the following **major features**: |
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| * [Training on GPU](../docs/gpu.html) enables training of complex models on a single node with multiple GPU cards. |
| * [Hybrid neural net partitioning](../docs/hybrid.html) supports data and model parallelism at the same time. |
| * [Python wrapper](../docs/python.html) makes it easy to configure the job, including neural net and SGD algorithm. |
| * [RNN model and BPTT algorithm](../docs/general-rnn.html) are implemented to support applications based on RNN models, e.g., GRU. |
| * [Cloud software integration](../docs/distributed-training.md) includes Mesos, Docker and HDFS. |
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| **More details** are listed as follows, |
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| * 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) |
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| * 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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