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| to you under the Apache License, Version 2.0 (the |
| "License"); you may not use this file except in compliance |
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| http://www.apache.org/licenses/LICENSE-2.0 |
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| software distributed under the License is distributed on an |
| "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY |
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| |
| Development Schedule |
| ==================== |
| |
| .. csv-table:: |
| :header: "Release","Module","Feature" |
| |
| "v0.1 Sep 2015 ","Neural Network ","Feed forward neural network, including CNN, MLP " |
| " "," ","RBM-like model, including RBM " |
| " "," ","Recurrent neural network, including standard RNN " |
| " ","Architecture ","One worker group on single node (with data partition) " |
| " "," ","Multi worker groups on single node using `Hogwild <http://www.eecs.berkeley.edu/~brecht/papers/hogwildTR.pdf>`_ " |
| " "," ","Distributed Hogwild" |
| " "," ","Multi groups across nodes, like `Downpour <http://papers.nips.cc/paper/4687-large-scale-distributed-deep-networks>`_" |
| " "," ","All-Reduce training architecture like `DeepImage <http://arxiv.org/abs/1501.02876>`_ " |
| " "," ","Load-balance among servers " |
| " ","Failure recovery ","Checkpoint and restore " |
| " ","Tools ","Installation with GNU auto Tools " |
| "v0.2 Jan 2016 ","Neural Network ","Feed forward neural network, including AlexNet, cuDNN layers,Tools " |
| " "," ","Recurrent neural network, including GRULayer and BPTT " |
| " "," ","Model partition and hybrid partition " |
| " ","Tools ","Integration with Mesos for resource management " |
| " "," ","Prepare Docker images for deployment" |
| " "," ","Visualization of neural net and debug information " |
| " ","Binding ","Python binding for major components " |
| " ","GPU ","Single node with multiple GPUs " |
| "v0.3 April 2016 ","GPU ","Multiple nodes, each with multiple GPUs" |
| " "," ","Heterogeneous training using both GPU and CPU `CcT <http://arxiv.org/abs/1504.04343>`_" |
| " "," ","Support cuDNN v4 " |
| " ","Installation ","Remove dependency on ZeroMQ, CZMQ, Zookeeper for single node training" |
| " ","Updater ","Add new SGD updaters including Adam, AdamMax and AdaDelta" |
| " ","Binding ","Enhance Python binding for training" |
| "v1.0 Sep 2016 ","Programming abstraction ","Tensor with linear algebra, neural net and random operations " |
| " "," ","Updater for distributed parameter updating " |
| " ","Hardware ","Use Cuda and Cudnn for Nvidia GPU" |
| " "," ","Use OpenCL for AMD GPU or other devices" |
| " ","Cross-platform ","To extend from Linux to MacOS" |
| " "," ","Large image models, e.g., `VGG <https://arxiv.org/pdf/1409.1556.pdf>`_ and `Residual Net <http://arxiv.org/abs/1512.03385>`_" |
| "v1.1 Jan 2017 ","Model Zoo ","GoogleNet; Health-care models" |
| " ","Caffe converter ","Use SINGA to train models configured in caffe proto files" |
| " ","Model components ","Add concat and slice layers; accept multiple inputs to the net" |
| " ","Compilation and installation ","Windows suppport" |
| " "," ","Simplify the installation by compiling protobuf and openblas together with SINGA" |
| " "," ","Build python wheel automatically using Jenkins" |
| " "," ","Install SINGA from Debian packages" |
| "v1.2 June 2018 ","AutoGrad ","AutoGrad for BP" |
| " ","Python 3 ","Support Python 3 for PySinga" |
| " ","Models ","Add popular models, including VGG, ResNet, DenseNet, InceptionNet" |
