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From wang...@apache.org
Subject svn commit: r1724070 - /incubator/singa/site/trunk/content/markdown/develop/schedule.md
Date Mon, 11 Jan 2016 16:05:12 GMT
Author: wangwei
Date: Mon Jan 11 16:05:11 2016
New Revision: 1724070

URL: http://svn.apache.org/viewvc?rev=1724070&view=rev
Log:
Update schedule page for v0.2

Modified:
    incubator/singa/site/trunk/content/markdown/develop/schedule.md

Modified: incubator/singa/site/trunk/content/markdown/develop/schedule.md
URL: http://svn.apache.org/viewvc/incubator/singa/site/trunk/content/markdown/develop/schedule.md?rev=1724070&r1=1724069&r2=1724070&view=diff
==============================================================================
--- incubator/singa/site/trunk/content/markdown/develop/schedule.md (original)
+++ incubator/singa/site/trunk/content/markdown/develop/schedule.md Mon Jan 11 16:05:11 2016
@@ -3,7 +3,7 @@
 
 | Release | Module| Feature | Status |
 |---------|---------|-------------|--------|
-| 0.1 Sep     | Neural Network |1.1. Feed forward neural network, including CNN, MLP | done|
+| 0.1 Sep 2015     | Neural Network |1.1. Feed forward neural network, including CNN, MLP
| done|
 |         |          |1.2. RBM-like model, including RBM | done|
 |         |                |1.3. Recurrent neural network, including standard RNN | done|
 |         | Architecture   |1.4. One worker group on single node (with data partition)| done|
@@ -14,18 +14,17 @@
 |         |                |1.9. Load-balance among servers | done|
 |         | Failure recovery|1.10. Checkpoint and restore |done|
 |         | Tools|1.11. Installation with GNU auto tools| done|
-|0.2 Dec | Neural Network |2.1. Feed forward neural network, including VGG model, CSV input
layer, HDFS output layer, etc.||
-|         |                |2.2. Recurrent neural network, including GRU and LSTM| |
-|         | |2.3. Model partition and hybrid partition||
-|         | Configuration   |2.4. Configuration helpers for popular models, e.g., CNN, MLP,
Auto-encoders||
-|         | Tools |2.5. Integration with Mesos for resource management||
-|         |               |2.6. Prepare Docker images for deployment||
-|         | Binding        |2.7. Python binding for major components ||
-|         | GPU            |2.8. Single node with multiple GPUs ||
-|0.3 Mar | GPU | 3.1 Multiple nodes, each with multiple GPUs||
+|0.2 Jan 2016 | Neural Network |2.1. Feed forward neural network, including AlexNet, cuDNN
layers, etc.| done |
+|         |                |2.2. Recurrent neural network, including GRULayer and BPTT|done
|
+|         | |2.3. Model partition and hybrid partition|done|
+|         | Tools |2.4. Integration with Mesos for resource management|done|
+|         |               |2.5. Prepare Docker images for deployment|done|
+|         |               |2.6. Visualization of neural net and debug information |done|
+|         | Binding        |2.7. Python binding for major components |done|
+|         | GPU            |2.8. Single node with multiple GPUs |done|
+|0.3 Mar 2016 | GPU | 3.1 Multiple nodes, each with multiple GPUs||
 |        |     | 3.2 Heterogeneous training using both GPU and CPU [CcT](http://arxiv.org/abs/1504.04343)||
-|        | Phi | 3.3 Integration with Intel Phi co-processors (depending on the availability
of the hardware)||
-|         | Tools| 3.4 Deep learning as a service ||
-|         | Applications | 3.5 Image classification, product search, etc.||
-|         | Optimization | 3.6 ... ||
+|         | Tools| 3.3 Deep learning as a service ||
+|         | Applications | 3.4 Image classification, product search, etc.||
+|         | Optimization | 3.5 ... ||
 



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