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| <div class="section" id="development-schedule"> |
| <h1>Development Schedule<a class="headerlink" href="#development-schedule" title="Permalink to this headline">¶</a></h1> |
| <table border="1" class="docutils"> |
| <colgroup> |
| <col width="25%" /> |
| <col width="25%" /> |
| <col width="25%" /> |
| <col width="25%" /> |
| </colgroup> |
| <thead valign="bottom"> |
| <tr class="row-odd"><th class="head">Release</th> |
| <th class="head">Module</th> |
| <th class="head">Feature</th> |
| <th class="head">Status</th> |
| </tr> |
| </thead> |
| <tbody valign="top"> |
| <tr class="row-even"><td><blockquote class="first last"> |
| <div>0.1 Sep 2015</div></blockquote> |
| </td> |
| <td><blockquote class="first last"> |
| <div>Neural Network</div></blockquote> |
| </td> |
| <td><blockquote class="first last"> |
| <div>Feed forward neural network, including CNN, MLP</div></blockquote> |
| </td> |
| <td><blockquote class="first last"> |
| <div>done</div></blockquote> |
| </td> |
| </tr> |
| <tr class="row-odd"><td> </td> |
| <td> </td> |
| <td><blockquote class="first last"> |
| <div>RBM-like model, including RBM</div></blockquote> |
| </td> |
| <td><blockquote class="first last"> |
| <div>done</div></blockquote> |
| </td> |
| </tr> |
| <tr class="row-even"><td> </td> |
| <td> </td> |
| <td><blockquote class="first last"> |
| <div>Recurrent neural network, including standard RNN</div></blockquote> |
| </td> |
| <td><blockquote class="first last"> |
| <div>done</div></blockquote> |
| </td> |
| </tr> |
| <tr class="row-odd"><td> </td> |
| <td><blockquote class="first last"> |
| <div>Architecture</div></blockquote> |
| </td> |
| <td><blockquote class="first last"> |
| <div>One worker group on single node (with data partition)</div></blockquote> |
| </td> |
| <td><blockquote class="first last"> |
| <div>done</div></blockquote> |
| </td> |
| </tr> |
| <tr class="row-even"><td> </td> |
| <td> </td> |
| <td><blockquote class="first last"> |
| <div>Multi worker groups on single node using [Hogwild](<a class="reference external" href="http://www.eecs.berkeley.edu/~brecht/papers/hogwildTR.pdf">http://www.eecs.berkeley.edu/~brecht/papers/hogwildTR.pdf</a>)</div></blockquote> |
| </td> |
| <td>done</td> |
| </tr> |
| <tr class="row-odd"><td> </td> |
| <td> </td> |
| <td><blockquote class="first last"> |
| <div>Distributed Hogwild</div></blockquote> |
| </td> |
| <td>done</td> |
| </tr> |
| <tr class="row-even"><td> </td> |
| <td> </td> |
| <td><blockquote class="first last"> |
| <div>Multi groups across nodes, like [Downpour](<a class="reference external" href="http://papers.nips.cc/paper/4687-large-scale-distributed-deep-networks">http://papers.nips.cc/paper/4687-large-scale-distributed-deep-networks</a>)</div></blockquote> |
| </td> |
| <td>done</td> |
| </tr> |
| <tr class="row-odd"><td> </td> |
| <td> </td> |
| <td><blockquote class="first last"> |
| <div>All-Reduce training architecture like [DeepImage](<a class="reference external" href="http://arxiv.org/abs/1501.02876">http://arxiv.org/abs/1501.02876</a>)</div></blockquote> |
| </td> |
| <td>done</td> |
| </tr> |
| <tr class="row-even"><td> </td> |
| <td> </td> |
| <td><blockquote class="first last"> |
| <div>Load-balance among servers</div></blockquote> |
| </td> |
| <td><blockquote class="first last"> |
| <div>done</div></blockquote> |
| </td> |
| </tr> |
| <tr class="row-odd"><td> </td> |
| <td><blockquote class="first last"> |
| <div>Failure recovery</div></blockquote> |
| </td> |
| <td><blockquote class="first last"> |
| <div>Checkpoint and restore</div></blockquote> |
| </td> |
| <td>done</td> |
| </tr> |
| <tr class="row-even"><td> </td> |
| <td><blockquote class="first last"> |
| <div>Tools</div></blockquote> |
| </td> |
| <td><blockquote class="first last"> |
| <div>Installation with GNU auto tools</div></blockquote> |
| </td> |
| <td><blockquote class="first last"> |
| <div>done</div></blockquote> |
| </td> |
| </tr> |
| <tr class="row-odd"><td>0.2 Jan 2016</td> |
| <td><blockquote class="first last"> |
| <div>Neural Network</div></blockquote> |
| </td> |
| <td><blockquote class="first last"> |
| <div>Feed forward neural network, including AlexNet, cuDNN layers, etc.</div></blockquote> |
| </td> |
| <td><blockquote class="first last"> |
| <div>done</div></blockquote> |
| </td> |
| </tr> |
| <tr class="row-even"><td> </td> |
| <td> </td> |
| <td><blockquote class="first last"> |
| <div>Recurrent neural network, including GRULayer and BPTT</div></blockquote> |
| </td> |
| <td>done</td> |
| </tr> |
| <tr class="row-odd"><td> </td> |
| <td> </td> |
| <td><blockquote class="first last"> |
| <div>Model partition and hybrid partition</div></blockquote> |
| </td> |
| <td>done</td> |
| </tr> |
| <tr class="row-even"><td> </td> |
| <td><blockquote class="first last"> |
| <div>Tools</div></blockquote> |
| </td> |
| <td><blockquote class="first last"> |
| <div>Integration with Mesos for resource management</div></blockquote> |
| </td> |
| <td>done</td> |
| </tr> |
| <tr class="row-odd"><td> </td> |
| <td> </td> |
| <td><blockquote class="first last"> |
| <div>Prepare Docker images for deployment</div></blockquote> |
| </td> |
| <td>done</td> |
| </tr> |
| <tr class="row-even"><td> </td> |
| <td> </td> |
| <td><blockquote class="first last"> |
| <div>Visualization of neural net and debug information</div></blockquote> |
| </td> |
| <td>done</td> |
| </tr> |
| <tr class="row-odd"><td> </td> |
| <td><blockquote class="first last"> |
| <div>Binding</div></blockquote> |
| </td> |
| <td><blockquote class="first last"> |
| <div>Python binding for major components</div></blockquote> |
| </td> |
| <td>done</td> |
| </tr> |
| <tr class="row-even"><td> </td> |
| <td><blockquote class="first last"> |
| <div>GPU</div></blockquote> |
| </td> |
| <td><blockquote class="first last"> |
| <div>Single node with multiple GPUs</div></blockquote> |
| </td> |
| <td>done</td> |
| </tr> |
| <tr class="row-odd"><td>0.3 April 2016</td> |
| <td><blockquote class="first last"> |
| <div>GPU</div></blockquote> |
| </td> |
| <td><blockquote class="first last"> |
| <div>Multiple nodes, each with multiple GPUs</div></blockquote> |
| </td> |
| <td>done</td> |
| </tr> |
| <tr class="row-even"><td> </td> |
| <td> </td> |
| <td><blockquote class="first last"> |
| <div>Heterogeneous training using both GPU and CPU [CcT](<a class="reference external" href="http://arxiv.org/abs/1504.04343">http://arxiv.org/abs/1504.04343</a>)</div></blockquote> |
| </td> |
| <td>done</td> |
| </tr> |
| <tr class="row-odd"><td> </td> |
| <td> </td> |
| <td><blockquote class="first last"> |
| <div>Support cuDNN v4</div></blockquote> |
| </td> |
| <td><blockquote class="first last"> |
| <div>done</div></blockquote> |
| </td> |
| </tr> |
| <tr class="row-even"><td> </td> |
| <td><blockquote class="first last"> |
| <div>Installation</div></blockquote> |
| </td> |
| <td><blockquote class="first last"> |
| <div>Remove dependency on ZeroMQ, CZMQ, Zookeeper for single node training</div></blockquote> |
| </td> |
| <td>done</td> |
| </tr> |
| <tr class="row-odd"><td> </td> |
| <td><blockquote class="first last"> |
| <div>Updater</div></blockquote> |
| </td> |
| <td><blockquote class="first last"> |
| <div>Add new SGD updaters including Adam, AdamMax and AdaDelta</div></blockquote> |
| </td> |
| <td>done</td> |
| </tr> |
| <tr class="row-even"><td> </td> |
| <td><blockquote class="first last"> |
| <div>Binding</div></blockquote> |
| </td> |
| <td><blockquote class="first last"> |
| <div>Enhance Python binding for training</div></blockquote> |
| </td> |
| <td>done</td> |
| </tr> |
| <tr class="row-odd"><td>1.0 Aug 2016</td> |
| <td><blockquote class="first last"> |
| <div>Programming abstraction</div></blockquote> |
| </td> |
| <td>Tensor with linear algebra, neural net and random operations</td> |
| <td> </td> |
| </tr> |
| <tr class="row-even"><td> </td> |
| <td> </td> |
| <td>Updater for distributed parameter updating</td> |
| <td> </td> |
| </tr> |
| <tr class="row-odd"><td> </td> |
| <td><blockquote class="first last"> |
| <div>Optimization</div></blockquote> |
| </td> |
| <td><blockquote class="first last"> |
| <div>Execution and memory optimization</div></blockquote> |
| </td> |
| <td> </td> |
| </tr> |
| <tr class="row-even"><td> </td> |
| <td><blockquote class="first last"> |
| <div>Hardware</div></blockquote> |
| </td> |
| <td><blockquote class="first last"> |
| <div>Use Cuda and Cudnn for Nvidia GPU</div></blockquote> |
| </td> |
| <td> </td> |
| </tr> |
| <tr class="row-odd"><td> </td> |
| <td> </td> |
| <td><blockquote class="first last"> |
| <div>Use OpenCL for AMD GPU or other devices</div></blockquote> |
| </td> |
| <td> </td> |
| </tr> |
| <tr class="row-even"><td> </td> |
| <td><blockquote class="first last"> |
| <div>Cross-platform</div></blockquote> |
| </td> |
| <td><blockquote class="first last"> |
| <div>To extend from Linux to MacOS and Windows</div></blockquote> |
| </td> |
| <td> </td> |
| </tr> |
| <tr class="row-odd"><td> </td> |
| <td><blockquote class="first last"> |
| <div>Examples</div></blockquote> |
| </td> |
| <td><blockquote class="first last"> |
| <div>Speech recognition example</div></blockquote> |
| </td> |
| <td> </td> |
| </tr> |
| <tr class="row-even"><td> </td> |
| <td> </td> |
| <td>Large image models, e.g., [VGG](<a class="reference external" href="https://arxiv.org/pdf/1409.1556.pdf">https://arxiv.org/pdf/1409.1556.pdf</a>) and [Residual Net](<a class="reference external" href="http://arxiv.org/abs/1512.03385">http://arxiv.org/abs/1512.03385</a>)</td> |
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| </tr> |
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