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<p>#singa-incubating-0.2.0 Release Notes</p>
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<p>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.</p>
<p>This release includes the following <strong>major features</strong>:</p>
<ul class="simple">
<li><a class="reference external" href="../docs/gpu.html">Training on GPU</a> enables training of complex models on a single node with multiple GPU cards.</li>
<li><a class="reference external" href="../docs/hybrid.html">Hybrid neural net partitioning</a> supports data and model parallelism at the same time.</li>
<li><a class="reference external" href="../docs/python.html">Python wrapper</a> makes it easy to configure the job, including neural net and SGD algorithm.</li>
<li><a class="reference external" href="../docs/general-rnn.html">RNN model and BPTT algorithm</a> are implemented to support applications based on RNN models, e.g., GRU.</li>
<li><a class="reference external" href="../docs/distributed-training.md">Cloud software integration</a> includes Mesos, Docker and HDFS.</li>
</ul>
<p><strong>More details</strong> are listed as follows,</p>
<ul class="simple">
<li>Programming model<ul>
<li>[SINGA-80] New Blob Level and Address Level Math Operation Interface</li>
<li>[SINGA-82] Refactor input layers using data store abstraction</li>
<li>[SINGA-87] Replace exclude field to include field for layer configuration</li>
<li>[SINGA-110] Add Layer member datavec_ and gradvec_</li>
<li>[SINGA-120] Implemented GRU and BPTT (BPTTWorker)</li>
</ul>
</li>
</ul>
<ul class="simple">
<li>Neuralnet layers<ul>
<li>[SINGA-91] Add SoftmaxLayer and ArgSortLayer</li>
<li>[SINGA-106] Add dummy layer for test purpose</li>
<li>[SINGA-120] Implemented GRU and BPTT (GRULayer and OneHotLayer)</li>
</ul>
</li>
</ul>
<ul class="simple">
<li>GPU training support<ul>
<li>[SINGA-100] Implement layers using CUDNN for GPU training</li>
<li>[SINGA-104] Add Context Class</li>
<li>[SINGA-105] Update GUN make files for compiling cuda related code</li>
<li>[SINGA-98] Add Support for AlexNet ImageNet Classification Model</li>
</ul>
</li>
</ul>
<ul class="simple">
<li>Model/Hybrid partition<ul>
<li>[SINGA-109] Refine bridge layers</li>
<li>[SINGA-111] Add slice, concate and split layers</li>
<li>[SINGA-113] Model/Hybrid Partition Support</li>
</ul>
</li>
</ul>
<ul class="simple">
<li>Python binding<ul>
<li>[SINGA-108] Add Python wrapper to singa</li>
</ul>
</li>
</ul>
<ul class="simple">
<li>Predict-only mode<ul>
<li>[SINGA-85] Add functions for extracting features and test new data</li>
</ul>
</li>
</ul>
<ul class="simple">
<li>Integrate with third-party tools<ul>
<li>[SINGA-11] Start SINGA on Apache Mesos</li>
<li>[SINGA-78] Use Doxygen to generate documentation</li>
<li>[SINGA-89] Add Docker support</li>
</ul>
</li>
</ul>
<ul class="simple">
<li>Unit test<ul>
<li>[SINGA-95] Add make test after building</li>
</ul>
</li>
</ul>
<ul class="simple">
<li>Other improvment<ul>
<li>[SINGA-84] Header Files Rearrange</li>
<li>[SINGA-93] Remove the asterisk in the log tcp://169.254.12.152:*:49152</li>
<li>[SINGA-94] Move call to google::InitGoogleLogging() from Driver::Init() to main()</li>
<li>[SINGA-96] Add Momentum to Cifar10 Example</li>
<li>[SINGA-101] Add ll (ls -l) command in .bashrc file when using docker</li>
<li>[SINGA-114] Remove short logs in tmp directory</li>
<li>[SINGA-115] Print layer debug information in the neural net graph file</li>
<li>[SINGA-118] Make protobuf LayerType field id easy to assign</li>
<li>[SIGNA-97] Add HDFS Store</li>
</ul>
</li>
</ul>
<ul class="simple">
<li>Bugs fixed<ul>
<li>[SINGA-85] Fix compilation errors in examples</li>
<li>[SINGA-90] Miscellaneous trivial bug fixes</li>
<li>[SINGA-107] Error from loading pre-trained params for training stacked RBMs</li>
<li>[SINGA-116] Fix a bug in InnerProductLayer caused by weight matrix sharing</li>
</ul>
</li>
</ul>
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