diff --git a/go/pserver/client/c/test/test_train.py b/go/pserver/client/c/test/test_train.py
index 68e1d9b269209b695e27f91a656dc2d8e527b4cd..d6922672f4c1253e62cfe54965f6c2f3b5e6c7bf 100644
--- a/go/pserver/client/c/test/test_train.py
+++ b/go/pserver/client/c/test/test_train.py
@@ -19,7 +19,7 @@ def main():
     # create parameters
     parameters = paddle.parameters.create(cost)
 
-    # create optimizer
+    # create optimizer of new remote updater to pserver
     optimizer = paddle.optimizer.Momentum(momentum=0)
 
     #TODO(zhihong) : replace optimizer with new OptimizerConfig
diff --git a/go/pserver/optimizer.go b/go/pserver/optimizer.go
index 54d108209402c27e79a9948f60ecbdadeffc7d9b..ee5fe6205b670920b0ce13dd678901e5154c0e7e 100644
--- a/go/pserver/optimizer.go
+++ b/go/pserver/optimizer.go
@@ -42,12 +42,12 @@ func newOptimizer(paramWithConfigs ParameterWithConfig) *optimizer {
 	c := paramWithConfigs.Config
 	log.WithFields(log.Fields{
 		"ElementType": p.ElementType,
-		"ParamSize":   len(p.Content),
+		"ParamSize":   len(p.Content) / C.sizeof_float,
 		"ConfigSize":  len(c),
 	}).Info("New Optimizer Created with config:")
 	var cbuffer unsafe.Pointer
 	cbuffer = C.malloc(C.size_t(len(p.Content)))
-	C.memcpy(cbuffer, unsafe.Pointer(&p.Content[0]), C.size_t(len(p.Content)))
+	C.memcpy(cbuffer, unsafe.Pointer(&p.Content[0]), C.size_t(len(p.Content)/C.sizeof_float))
 	o.opt = C.paddle_create_optimizer((*C.uchar)(&c[0]), C.int(len(c)),
 		C.paddle_element_type(p.ElementType), cbuffer, C.int(len(p.Content)/C.sizeof_float),
 		(*C.char)(nullPtr), 0)
diff --git a/paddle/trainer/NewRemoteParameterUpdater.cpp b/paddle/trainer/NewRemoteParameterUpdater.cpp
index f25ce2f7f06f6da0feab27da61b8e49689cbe213..b359d9da2167bf459504e15c3140b3d956f417f3 100644
--- a/paddle/trainer/NewRemoteParameterUpdater.cpp
+++ b/paddle/trainer/NewRemoteParameterUpdater.cpp
@@ -22,7 +22,8 @@ DECLARE_string(save_dir);
 namespace paddle {
 NewRemoteParameterUpdater::NewRemoteParameterUpdater(
     const OptimizationConfig &config, const std::string pserverSpec)
-    : parameterClient_(-1),
+    : trainerConfig_(config),
+      parameterClient_(-1),
       newParameters_(nullptr),
       newGradients_(nullptr),
       pserverSpec_(pserverSpec) {}
@@ -51,7 +52,22 @@ void NewRemoteParameterUpdater::init(
     LOG(INFO) << "paddle_begin_init_params start";
     for (int i = 0; i < parameterSize(); ++i) {
       auto paramConfig = parameters_[i]->getConfig();
-      std::string bytes = paramConfig.SerializeAsString();
+      LOG(INFO) << "old param config: " << paramConfig.DebugString();
+      // FIXME(typhoonzero): convert old paramConfig to optimizerConfig
+      OptimizerConfig optimizeConfigV2;
+      auto sgdConfigV2 = optimizeConfigV2.mutable_sgd();
+      sgdConfigV2->set_momentum(paramConfig.momentum());
+      sgdConfigV2->set_decay(paramConfig.decay_rate());
+      optimizeConfigV2.set_lr_policy(paddle::OptimizerConfig::Const);
+      auto constlr = optimizeConfigV2.mutable_const_lr();
+      constlr->set_learning_rate(paramConfig.learning_rate());
+      if (trainerConfig_.algorithm() == "sgd") {
+        optimizeConfigV2.set_optimizer(paddle::OptimizerConfig::SGD);
+        // FIXME: config all algorithms
+      } else {
+        optimizeConfigV2.set_optimizer(paddle::OptimizerConfig::SGD);
+      }
+      std::string bytes = optimizeConfigV2.SerializeAsString();
       const char *array = bytes.data();
       int size = (int)bytes.size();
       paddle_init_param(
@@ -83,4 +99,4 @@ void NewRemoteParameterUpdater::finishBatch(real cost) {
 void NewRemoteParameterUpdater::startPass() {}
 
 bool NewRemoteParameterUpdater::finishPass() { return true; }
-}
+}  // namespace paddle
diff --git a/paddle/trainer/NewRemoteParameterUpdater.h b/paddle/trainer/NewRemoteParameterUpdater.h
index f735185f62b3491a63e34cfc4a2ef73dae12243e..dfed00bc216b1d41bb7520619b76702f9fe650f2 100644
--- a/paddle/trainer/NewRemoteParameterUpdater.h
+++ b/paddle/trainer/NewRemoteParameterUpdater.h
@@ -16,6 +16,7 @@ limitations under the License. */
 
 #include <functional>
 #include <thread>
+#include "OptimizerConfig.pb.h"
 #include "ParameterUpdater.h"
 #include "libpaddle_pserver_cclient.h"
 #include "paddle/pserver/ParameterClient2.h"
@@ -101,6 +102,7 @@ private:
   }
 
 protected:
+  const OptimizationConfig& trainerConfig_;
   /// internal parameter client object for exchanging data with pserver
   paddle_pserver_client parameterClient_;
   /// the parameters for new pserver client
diff --git a/python/paddle/v2/optimizer.py b/python/paddle/v2/optimizer.py
index 8124e219ba499333ecdf4b34ff5352e281aaa016..390c22ee552c506fde1567efba1326a6d735ad2e 100644
--- a/python/paddle/v2/optimizer.py
+++ b/python/paddle/v2/optimizer.py
@@ -66,6 +66,8 @@ class Optimizer(object):
             if use_sparse_remote_updater:
                         gradient_machine.prefetch(in_args)
                         parameter_updater.getParametersRemote()
+
+        :param pserver_spec: pserver location, eg: localhost:3000
         :return: parameter_updater
         """
         if is_local:
diff --git a/python/paddle/v2/trainer.py b/python/paddle/v2/trainer.py
index f9658a8c5df9562073c8a187074a6cb3459ac5d9..96c6c4b89a2f2e2c3ecb95213e0e0191b1998f50 100644
--- a/python/paddle/v2/trainer.py
+++ b/python/paddle/v2/trainer.py
@@ -41,6 +41,7 @@ class SGD(object):
     :type parameters: paddle.v2.parameters.Parameters
     :param extra_layers: Some layers in the neural network graph are not
                          in the path of cost layer.
+    :param pserver_spec: pserver location, eg: localhost:3000
     :type extra_layers: paddle.v2.config_base.Layer
     """