SINGA-100 Implement layers using CUDNN for GPU training

cudnn for cifar10 reaches accuracy 0.814


Project: http://git-wip-us.apache.org/repos/asf/incubator-singa/repo
Commit: http://git-wip-us.apache.org/repos/asf/incubator-singa/commit/5728c248
Tree: http://git-wip-us.apache.org/repos/asf/incubator-singa/tree/5728c248
Diff: http://git-wip-us.apache.org/repos/asf/incubator-singa/diff/5728c248

Branch: refs/heads/master
Commit: 5728c24832f8ce542325410c033d9c59dadab712
Parents: 8174760
Author: Wei Wang <[email protected]>
Authored: Thu Dec 10 21:37:43 2015 +0800
Committer: Wei Wang <[email protected]>
Committed: Fri Dec 11 11:48:24 2015 +0800

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 examples/cifar10/cudnn.conf | 18 ++++--------------
 1 file changed, 4 insertions(+), 14 deletions(-)
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http://git-wip-us.apache.org/repos/asf/incubator-singa/blob/5728c248/examples/cifar10/cudnn.conf
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diff --git a/examples/cifar10/cudnn.conf b/examples/cifar10/cudnn.conf
index 6a5e15f..49132d8 100644
--- a/examples/cifar10/cudnn.conf
+++ b/examples/cifar10/cudnn.conf
@@ -1,21 +1,11 @@
 name: "cifar10-convnet"
-<<<<<<< HEAD
-train_steps: 1000
-test_steps: 0
-test_freq: 0
-#validate_steps: 100
-#validate_freq: 300
-disp_freq: 30
-gpu: 0
-=======
-train_steps: 13000
+train_steps: 70000
 test_steps: 100
 test_freq: 1000
 #validate_steps: 100
 #validate_freq: 300
 disp_freq: 200
->>>>>>> bfb913f... fix bug from cudnnsoftmax and cudnnsoftmaxloss; todo debug 
accuracy problem. the accuracy improves slower than that from caffe and cannot 
reach 0.8 finally.
-gpu: 1
+gpu: 0
 #checkpoint_path: "examples/cifar10/checkpoint/step1000-worker0"
 train_one_batch {
   alg: kBP
@@ -298,7 +288,7 @@ neuralnet {
 cluster {
   nworker_groups: 1
   nserver_groups: 1
-  nworkers_per_group: 2
-  nworkers_per_procs: 2
+  nworkers_per_group: 1
+  nworkers_per_procs: 1
   workspace: "examples/cifar10"
 }

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