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From wang...@apache.org
Subject svn commit: r1679948 - /incubator/singa/site/trunk/content/markdown/community/schedule.md
Date Mon, 18 May 2015 06:41:55 GMT
Author: wangwei
Date: Mon May 18 06:41:55 2015
New Revision: 1679948

URL: http://svn.apache.org/r1679948
Log:
add development schedule page

Added:
    incubator/singa/site/trunk/content/markdown/community/schedule.md

Added: incubator/singa/site/trunk/content/markdown/community/schedule.md
URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/content/markdown/community/schedule.md?rev=1679948&view=auto
==============================================================================
--- incubator/singa/site/trunk/content/markdown/community/schedule.md (added)
+++ incubator/singa/site/trunk/content/markdown/community/schedule.md Mon May 18 06:41:55
2015
@@ -0,0 +1,42 @@
+Title: Development Schedule
+Notice:    Licensed to the Apache Software Foundation (ASF) under one
+           or more contributor license agreements.  See the NOTICE file
+           distributed with this work for additional information
+           regarding copyright ownership.  The ASF licenses this file
+           to you under the Apache License, Version 2.0 (the
+           "License"); you may not use this file except in compliance
+           with the License.  You may obtain a copy of the License at
+           .
+             http://www.apache.org/licenses/LICENSE-2.0
+           .
+           Unless required by applicable law or agreed to in writing,
+           software distributed under the License is distributed on an
+           "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+           KIND, either express or implied.  See the License for the
+           specific language governing permissions and limitations
+           under the License.
+
+## Development Schedule
+
+| Release | Module| Feature | Status |
+|---------|---------|-------------|--------|
+| 0.1     | Neural Network |1.1. Feed forward neural network, including CNN, MLP | done|
+|         |                |1.2. RBM-like model, including RBM | working|
+|         |                |1.3. Recurrent neural network, including standard RNN | working|
+|         | Architecture   |1.4. One worker group on single node (with data partition)| done|
+|         |                |1.5. Multi worker groups on single node using [Hogwild](http://www.eecs.berkeley.edu/~brecht/papers/hogwildTR.pdf)|working|
+|         |                |1.6. Multi groups across nodes, like [Downpour](http://papers.nips.cc/paper/4687-large-scale-distributed-deep-networks)|working|
+|         | Resource Management |1.7. Integration with Mesos | working|
+|         | Failure recovery|1.8. Checkpoint and restore |working|
+|         | Tools|1.9. Installation with GNU auto tools| done|
+|0.2      | Neural Network |2.1. Feed forward neural network, including auto-encoders, hinge
loss layers, HDFS data layers||
+|         |                |2.2. RBM-like model, including DBM | |
+|         |                |2.3. Recurrent neural network, including LSTM| |
+|         |                |2.4. Model partition ||
+|         | Communication  |2.5. MPI||
+|         | GPU            |2.6. Single GPU ||
+|         |                |2.7. Multiple GPUs on single node||
+|         | Architecture   |2.8. All-Reduce training architecture like [DeepImage](http://arxiv.org/abs/1501.02876)||
+|         | Fault Tolerance|2.9. Node failure detection and recovery||
+|         | Binding        |2.9. Python binding ||
+|         | User Interface |2.10. Web front-end for job submission and performance visualization||



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