diff --git a/benchmark/paddle/image/alexnet.py b/benchmark/paddle/image/alexnet.py
index 3358d43a4b08c6a9b89d59e1a8be53ee1f12bbe0..77d130ae34059d1e87040d00346ac1dadd86b0d8 100644
--- a/benchmark/paddle/image/alexnet.py
+++ b/benchmark/paddle/image/alexnet.py
@@ -6,8 +6,18 @@ height = 227
 width = 227
 num_class = 1000
 batch_size = get_config_arg('batch_size', int, 128)
+gp = get_config_arg('layer_num', int, 1)
+is_infer = get_config_arg("is_infer", bool, False)
+num_samples = get_config_arg('num_samples', int, 2560)
 
-args = {'height': height, 'width': width, 'color': True, 'num_class': num_class}
+args = {
+    'height': height,
+    'width': width,
+    'color': True,
+    'num_class': num_class,
+    'is_infer': is_infer,
+    'num_samples': num_samples
+}
 define_py_data_sources2(
     "train.list", None, module="provider", obj="process", args=args)
 
@@ -31,7 +41,7 @@ net = img_pool_layer(input=net, pool_size=3, stride=2)
 
 # conv2
 net = img_conv_layer(
-    input=net, filter_size=5, num_filters=256, stride=1, padding=2, groups=1)
+    input=net, filter_size=5, num_filters=256, stride=1, padding=2, groups=gp)
 net = img_cmrnorm_layer(input=net, size=5, scale=0.0001, power=0.75)
 net = img_pool_layer(input=net, pool_size=3, stride=2)
 
@@ -40,11 +50,11 @@ net = img_conv_layer(
     input=net, filter_size=3, num_filters=384, stride=1, padding=1)
 # conv4
 net = img_conv_layer(
-    input=net, filter_size=3, num_filters=384, stride=1, padding=1, groups=1)
+    input=net, filter_size=3, num_filters=384, stride=1, padding=1, groups=gp)
 
 # conv5
 net = img_conv_layer(
-    input=net, filter_size=3, num_filters=256, stride=1, padding=1, groups=1)
+    input=net, filter_size=3, num_filters=256, stride=1, padding=1, groups=gp)
 net = img_pool_layer(input=net, pool_size=3, stride=2)
 
 net = fc_layer(
@@ -59,6 +69,9 @@ net = fc_layer(
     layer_attr=ExtraAttr(drop_rate=0.5))
 net = fc_layer(input=net, size=1000, act=SoftmaxActivation())
 
-lab = data_layer('label', num_class)
-loss = cross_entropy(input=net, label=lab)
-outputs(loss)
+if is_infer:
+    outputs(net)
+else:
+    lab = data_layer('label', num_class)
+    loss = cross_entropy(input=net, label=lab)
+    outputs(loss)
diff --git a/benchmark/paddle/image/run_mkl_infer.sh b/benchmark/paddle/image/run_mkl_infer.sh
index 9eea21793ba9816e83a5311cb6f05cf535ed1a60..62c9bf6efd3810f506fd4592b2ba3a21b1b7f0e7 100755
--- a/benchmark/paddle/image/run_mkl_infer.sh
+++ b/benchmark/paddle/image/run_mkl_infer.sh
@@ -79,8 +79,9 @@ fi
 # inference benchmark
 for use_mkldnn in True False; do
   for batchsize in 1 2 4 8 16; do
-    infer googlenet v1 $batchsize $use_mkldnn
-    infer resnet 50 $batchsize $use_mkldnn
     infer vgg 19 $batchsize $use_mkldnn
+    infer resnet 50 $batchsize $use_mkldnn
+    infer googlenet v1 $batchsize $use_mkldnn
+    infer alexnet 2 $batchsize $use_mkldnn
   done
 done
diff --git a/benchmark/paddle/image/run_mkl_train.sh b/benchmark/paddle/image/run_mkl_train.sh
index 5335af5ac1b9a4a48ec107b8b6386b50ead8284c..03d2d378fb72e36f765d89af788f6ee96fe21d4e 100755
--- a/benchmark/paddle/image/run_mkl_train.sh
+++ b/benchmark/paddle/image/run_mkl_train.sh
@@ -47,5 +47,6 @@ for use_mkldnn in True False; do
     train vgg 19 $batchsize $use_mkldnn
     train resnet 50 $batchsize $use_mkldnn
     train googlenet v1 $batchsize $use_mkldnn
+    train alexnet 2 $batchsize $use_mkldnn
   done
 done
diff --git a/benchmark/paddle/image/run_openblas_infer.sh b/benchmark/paddle/image/run_openblas_infer.sh
index 83b603c170346f5a4550c0bdad49d7ad1bff976e..da034f3b9dff794e22086a5295ad2b0c2361c356 100755
--- a/benchmark/paddle/image/run_openblas_infer.sh
+++ b/benchmark/paddle/image/run_openblas_infer.sh
@@ -57,7 +57,8 @@ fi
 
 # inference benchmark
 for batchsize in 1 2 4 8 16; do
-  infer googlenet v1 $batchsize
-  infer resnet 50 $batchsize
   infer vgg 19 $batchsize
+  infer resnet 50 $batchsize 
+  infer googlenet v1 $batchsize
+  infer alexnet 2 $batchsize
 done
diff --git a/benchmark/paddle/image/run_openblas_train.sh b/benchmark/paddle/image/run_openblas_train.sh
index e751cd6939ee54721ac8c22ef86911b4e9aeb29d..e9df83fee2a3f796b7234b39619364f6ee4d5dc9 100755
--- a/benchmark/paddle/image/run_openblas_train.sh
+++ b/benchmark/paddle/image/run_openblas_train.sh
@@ -37,4 +37,5 @@ for batchsize in 64 128 256; do
   train vgg 19 $batchsize
   train resnet 50 $batchsize
   train googlenet v1 $batchsize
+  train alexnet 2 $batchsize
 done