diff --git a/mindspore/ccsrc/fl/CMakeLists.txt b/mindspore/ccsrc/fl/CMakeLists.txt
index dbd8621642f..bab81a91bb4 100644
--- a/mindspore/ccsrc/fl/CMakeLists.txt
+++ b/mindspore/ccsrc/fl/CMakeLists.txt
@@ -5,6 +5,7 @@ if(NOT ENABLE_CPU OR WIN32)
     list(REMOVE_ITEM _FL_SRC_FILES "server/kernel/aggregation_kernel_factory.cc")
     list(REMOVE_ITEM _FL_SRC_FILES "server/kernel/dense_grad_accum_kernel.cc")
     list(REMOVE_ITEM _FL_SRC_FILES "server/kernel/fed_avg_kernel.cc")
+    list(REMOVE_ITEM _FL_SRC_FILES "server/kernel/sgd_kernel.cc")
     list(REMOVE_ITEM _FL_SRC_FILES "server/kernel/optimizer_kernel_factory.cc")
     list(REMOVE_ITEM _FL_SRC_FILES "server/kernel/round/round_kernel_factory.cc")
     list(REMOVE_ITEM _FL_SRC_FILES "server/kernel/round/round_kernel.cc")
diff --git a/mindspore/ccsrc/fl/server/common.h b/mindspore/ccsrc/fl/server/common.h
index 775e624d41b..87dae8a1207 100644
--- a/mindspore/ccsrc/fl/server/common.h
+++ b/mindspore/ccsrc/fl/server/common.h
@@ -111,6 +111,7 @@ constexpr auto kAdamEps = "eps";
 constexpr auto kFtrlLinear = "linear";
 constexpr auto kDataSize = "data_size";
 constexpr auto kNewDataSize = "new_data_size";
+constexpr auto kStat = "stat";
 
 // OptimParamNameToIndex represents every inputs/workspace/outputs parameter's offset when an optimizer kernel is
 // launched.
@@ -155,11 +156,14 @@ const OptimParamNameToIndex kAdamWeightDecayNameToIdx = {{"inputs",
                                                            {"weight_decay", 7},
                                                            {"grad", 8}}},
                                                          {"outputs", {}}};
-const std::map<std::string, OptimParamNameToIndex> kNameToIdxMap = {{kApplyMomentumOpName, kMomentumNameToIdx},
-                                                                    {kFusedSparseAdamName, kSparseAdamNameToIdx},
-                                                                    {kSparseApplyFtrlOpName, kSparseFtrlNameToIdx},
-                                                                    {kApplyAdamOpName, kAdamNameToIdx},
-                                                                    {"AdamWeightDecay", kAdamWeightDecayNameToIdx}};
+const OptimParamNameToIndex kSGDNameToIdx = {
+  {"inputs", {{kWeight, 0}, {kGradient, 1}, {kLearningRate, 2}, {kAccumulation, 3}, {kMomentum, 4}, {kStat, 5}}},
+  {"outputs", {}}};
+
+const std::map<std::string, OptimParamNameToIndex> kNameToIdxMap = {
+  {kApplyMomentumOpName, kMomentumNameToIdx},     {kFusedSparseAdamName, kSparseAdamNameToIdx},
+  {kSparseApplyFtrlOpName, kSparseFtrlNameToIdx}, {kApplyAdamOpName, kAdamNameToIdx},
+  {"AdamWeightDecay", kAdamWeightDecayNameToIdx}, {kSGDName, kSGDNameToIdx}};
 
 constexpr uint32_t kLeaderServerRank = 0;
 constexpr size_t kWorkerMgrThreadPoolSize = 32;
diff --git a/mindspore/ccsrc/fl/server/kernel/sgd_kernel.cc b/mindspore/ccsrc/fl/server/kernel/sgd_kernel.cc
new file mode 100644
index 00000000000..0b1d13673c0
--- /dev/null
+++ b/mindspore/ccsrc/fl/server/kernel/sgd_kernel.cc
@@ -0,0 +1,35 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ *
+ * Licensed 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.
+ */
+
+#include "fl/server/kernel/sgd_kernel.h"
+
+namespace mindspore {
+namespace fl {
+namespace server {
+namespace kernel {
+REG_OPTIMIZER_KERNEL(SGD,
+                     ParamsInfo()
+                       .AddInputNameType(kWeight, kNumberTypeFloat32)
+                       .AddInputNameType(kGradient, kNumberTypeFloat32)
+                       .AddInputNameType(kLearningRate, kNumberTypeFloat32)
+                       .AddInputNameType(kAccumulation, kNumberTypeFloat32)
+                       .AddInputNameType(kMomentum, kNumberTypeFloat32)
+                       .AddInputNameType(kStat, kNumberTypeFloat32),
+                     SGDKernel, float)
+}  // namespace kernel
+}  // namespace server
+}  // namespace fl
+}  // namespace mindspore
diff --git a/mindspore/ccsrc/fl/server/kernel/sgd_kernel.h b/mindspore/ccsrc/fl/server/kernel/sgd_kernel.h
new file mode 100644
index 00000000000..233f9c0d8df
--- /dev/null
+++ b/mindspore/ccsrc/fl/server/kernel/sgd_kernel.h
@@ -0,0 +1,63 @@
+/**
+ * Copyright 2021 Huawei Technologies Co., Ltd
+ *
+ * Licensed 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.
+ */
+
+#ifndef MINDSPORE_CCSRC_FL_SERVER_KERNEL_SGD_KERNEL_H_
+#define MINDSPORE_CCSRC_FL_SERVER_KERNEL_SGD_KERNEL_H_
+
+#include <vector>
+#include <memory>
+#include <utility>
+#include "backend/kernel_compiler/cpu/sgd_cpu_kernel.h"
+#include "fl/server/kernel/optimizer_kernel.h"
+#include "fl/server/kernel/optimizer_kernel_factory.h"
+
+namespace mindspore {
+namespace fl {
+namespace server {
+namespace kernel {
+using mindspore::kernel::SGDCPUKernel;
+template <typename T>
+class SGDKernel : public SGDCPUKernel<T>, public OptimizerKernel {
+ public:
+  SGDKernel() = default;
+  ~SGDKernel() override = default;
+
+  void InitKernel(const CNodePtr &cnode) override {
+    SGDCPUKernel<T>::InitKernel(cnode);
+    InitServerKernelInputOutputSize(cnode);
+    GenerateReuseKernelNodeInfo();
+  }
+
+  bool Launch(const std::vector<AddressPtr> &inputs, const std::vector<AddressPtr> &workspace,
+              const std::vector<AddressPtr> &outputs) override {
+    return SGDCPUKernel<T>::Launch(inputs, workspace, outputs);
+  }
+
+  void GenerateReuseKernelNodeInfo() override {
+    MS_LOG(INFO) << "SGD reuse 'weight', 'learning rate', 'accumulation', 'momentum' and 'stat' of the kernel node.";
+    reuse_kernel_node_inputs_info_.insert(std::make_pair(kWeight, 0));
+    reuse_kernel_node_inputs_info_.insert(std::make_pair(kLearningRate, 2));
+    reuse_kernel_node_inputs_info_.insert(std::make_pair(kAccumulation, 3));
+    reuse_kernel_node_inputs_info_.insert(std::make_pair(kMomentum, 4));
+    reuse_kernel_node_inputs_info_.insert(std::make_pair(kStat, 5));
+    return;
+  }
+};
+}  // namespace kernel
+}  // namespace server
+}  // namespace fl
+}  // namespace mindspore
+#endif  // MINDSPORE_CCSRC_FL_SERVER_KERNEL_SGD_KERNEL_H_
diff --git a/tests/st/fl/cross_silo_femnist/config.json b/tests/st/fl/cross_silo_femnist/config.json
new file mode 100644
index 00000000000..37ac6edfb25
--- /dev/null
+++ b/tests/st/fl/cross_silo_femnist/config.json
@@ -0,0 +1,6 @@
+{
+    "recovery": {
+        "storge_type": 1,
+        "storage_file_path": "recovery.json"
+    }
+}
\ No newline at end of file
diff --git a/tests/st/fl/cross_silo_femnist/finish_cross_silo_femnist.py b/tests/st/fl/cross_silo_femnist/finish_cross_silo_femnist.py
new file mode 100644
index 00000000000..2f48947835a
--- /dev/null
+++ b/tests/st/fl/cross_silo_femnist/finish_cross_silo_femnist.py
@@ -0,0 +1,29 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# Licensed 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.
+# ============================================================================
+
+import argparse
+import subprocess
+
+parser = argparse.ArgumentParser(description="Finish test_cross_silo_femnist.py case")
+parser.add_argument("--scheduler_port", type=int, default=8113)
+
+args, _ = parser.parse_known_args()
+scheduler_port = args.scheduler_port
+
+cmd = "pid=`ps -ef|grep \"scheduler_port=" + str(scheduler_port) + "\" "
+cmd += " | grep -v \"grep\" | grep -v \"finish\" |awk '{print $2}'` && "
+cmd += "for id in $pid; do kill -9 $id && echo \"killed $id\"; done"
+
+subprocess.call(['bash', '-c', cmd])
diff --git a/tests/st/fl/cross_silo_femnist/run_cross_silo_femnist_sched.py b/tests/st/fl/cross_silo_femnist/run_cross_silo_femnist_sched.py
new file mode 100644
index 00000000000..477e72a4124
--- /dev/null
+++ b/tests/st/fl/cross_silo_femnist/run_cross_silo_femnist_sched.py
@@ -0,0 +1,58 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# Licensed 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.
+# ============================================================================
+
+import argparse
+import subprocess
+
+parser = argparse.ArgumentParser(description="Run test_cross_silo_femnist.py case")
+parser.add_argument("--device_target", type=str, default="CPU")
+parser.add_argument("--server_mode", type=str, default="FEDERATED_LEARNING")
+parser.add_argument("--worker_num", type=int, default=1)
+parser.add_argument("--server_num", type=int, default=2)
+parser.add_argument("--scheduler_ip", type=str, default="127.0.0.1")
+parser.add_argument("--scheduler_port", type=int, default=8113)
+parser.add_argument("--scheduler_manage_port", type=int, default=11202)
+parser.add_argument("--config_file_path", type=str, default="")
+parser.add_argument("--dataset_path", type=str, default="")
+
+args, _ = parser.parse_known_args()
+device_target = args.device_target
+server_mode = args.server_mode
+worker_num = args.worker_num
+server_num = args.server_num
+scheduler_ip = args.scheduler_ip
+scheduler_port = args.scheduler_port
+scheduler_manage_port = args.scheduler_manage_port
+config_file_path = args.config_file_path
+dataset_path = args.dataset_path
+
+cmd_sched = "execute_path=$(pwd) && self_path=$(dirname \"${script_self}\") && rm -rf ${execute_path}/scheduler/ &&"
+cmd_sched += "mkdir ${execute_path}/scheduler/ &&"
+cmd_sched += "cd ${execute_path}/scheduler/ || exit && export GLOG_v=1 &&"
+cmd_sched += "python ${self_path}/../test_cross_silo_femnist.py"
+cmd_sched += " --device_target=" + device_target
+cmd_sched += " --server_mode=" + server_mode
+cmd_sched += " --ms_role=MS_SCHED"
+cmd_sched += " --worker_num=" + str(worker_num)
+cmd_sched += " --server_num=" + str(server_num)
+cmd_sched += " --config_file_path=" + str(config_file_path)
+cmd_sched += " --scheduler_ip=" + scheduler_ip
+cmd_sched += " --scheduler_port=" + str(scheduler_port)
+cmd_sched += " --scheduler_manage_port=" + str(scheduler_manage_port)
+cmd_sched += " --dataset_path=" + str(dataset_path)
+cmd_sched += " --user_id=" + str(0)
+cmd_sched += " > scheduler.log 2>&1 &"
+
+subprocess.call(['bash', '-c', cmd_sched])
diff --git a/tests/st/fl/cross_silo_femnist/run_cross_silo_femnist_server.py b/tests/st/fl/cross_silo_femnist/run_cross_silo_femnist_server.py
new file mode 100644
index 00000000000..9869b4df4dd
--- /dev/null
+++ b/tests/st/fl/cross_silo_femnist/run_cross_silo_femnist_server.py
@@ -0,0 +1,119 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# Licensed 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.
+# ============================================================================
+
+import argparse
+import subprocess
+
+parser = argparse.ArgumentParser(description="Run test_cross_silo_femnist.py case")
+parser.add_argument("--device_target", type=str, default="CPU")
+parser.add_argument("--server_mode", type=str, default="FEDERATED_LEARNING")
+parser.add_argument("--worker_num", type=int, default=1)
+parser.add_argument("--server_num", type=int, default=2)
+parser.add_argument("--scheduler_ip", type=str, default="127.0.0.1")
+parser.add_argument("--scheduler_port", type=int, default=8113)
+parser.add_argument("--fl_server_port", type=int, default=6666)
+parser.add_argument("--start_fl_job_threshold", type=int, default=1)
+parser.add_argument("--start_fl_job_time_window", type=int, default=3000)
+parser.add_argument("--update_model_ratio", type=float, default=1.0)
+parser.add_argument("--update_model_time_window", type=int, default=3000)
+parser.add_argument("--fl_name", type=str, default="Lenet")
+parser.add_argument("--fl_iteration_num", type=int, default=25)
+parser.add_argument("--client_epoch_num", type=int, default=20)
+parser.add_argument("--client_batch_size", type=int, default=32)
+parser.add_argument("--client_learning_rate", type=float, default=0.1)
+parser.add_argument("--local_server_num", type=int, default=-1)
+parser.add_argument("--config_file_path", type=str, default="")
+parser.add_argument("--encrypt_type", type=str, default="NOT_ENCRYPT")
+# parameters for encrypt_type='DP_ENCRYPT'
+parser.add_argument("--dp_eps", type=float, default=50.0)
+parser.add_argument("--dp_delta", type=float, default=0.01)  # 1/worker_num
+parser.add_argument("--dp_norm_clip", type=float, default=1.0)
+# parameters for encrypt_type='PW_ENCRYPT'
+parser.add_argument("--share_secrets_ratio", type=float, default=1.0)
+parser.add_argument("--cipher_time_window", type=int, default=300000)
+parser.add_argument("--reconstruct_secrets_threshold", type=int, default=3)
+parser.add_argument("--dataset_path", type=str, default="")
+
+args, _ = parser.parse_known_args()
+device_target = args.device_target
+server_mode = args.server_mode
+worker_num = args.worker_num
+server_num = args.server_num
+scheduler_ip = args.scheduler_ip
+scheduler_port = args.scheduler_port
+fl_server_port = args.fl_server_port
+start_fl_job_threshold = args.start_fl_job_threshold
+start_fl_job_time_window = args.start_fl_job_time_window
+update_model_ratio = args.update_model_ratio
+update_model_time_window = args.update_model_time_window
+fl_name = args.fl_name
+fl_iteration_num = args.fl_iteration_num
+client_epoch_num = args.client_epoch_num
+client_batch_size = args.client_batch_size
+client_learning_rate = args.client_learning_rate
+local_server_num = args.local_server_num
+config_file_path = args.config_file_path
+encrypt_type = args.encrypt_type
+share_secrets_ratio = args.share_secrets_ratio
+cipher_time_window = args.cipher_time_window
+reconstruct_secrets_threshold = args.reconstruct_secrets_threshold
+dp_eps = args.dp_eps
+dp_delta = args.dp_delta
+dp_norm_clip = args.dp_norm_clip
+dataset_path = args.dataset_path
+
+if local_server_num == -1:
+    local_server_num = server_num
+
+assert local_server_num <= server_num, "The local server number should not be bigger than total server number."
+
+for i in range(local_server_num):
+    cmd_server = "execute_path=$(pwd) && self_path=$(dirname \"${script_self}\") && "
+    cmd_server += "rm -rf ${execute_path}/server_" + str(i) + "/ &&"
+    cmd_server += "mkdir ${execute_path}/server_" + str(i) + "/ &&"
+    cmd_server += "cd ${execute_path}/server_" + str(i) + "/ || exit && export GLOG_v=1 &&"
+    cmd_server += "python ${self_path}/../test_cross_silo_femnist.py"
+    cmd_server += " --device_target=" + device_target
+    cmd_server += " --server_mode=" + server_mode
+    cmd_server += " --ms_role=MS_SERVER"
+    cmd_server += " --worker_num=" + str(worker_num)
+    cmd_server += " --server_num=" + str(server_num)
+    cmd_server += " --scheduler_ip=" + scheduler_ip
+    cmd_server += " --scheduler_port=" + str(scheduler_port)
+    cmd_server += " --fl_server_port=" + str(fl_server_port + i)
+    cmd_server += " --start_fl_job_threshold=" + str(start_fl_job_threshold)
+    cmd_server += " --start_fl_job_time_window=" + str(start_fl_job_time_window)
+    cmd_server += " --update_model_ratio=" + str(update_model_ratio)
+    cmd_server += " --update_model_time_window=" + str(update_model_time_window)
+    cmd_server += " --fl_name=" + fl_name
+    cmd_server += " --fl_iteration_num=" + str(fl_iteration_num)
+    cmd_server += " --config_file_path=" + str(config_file_path)
+    cmd_server += " --client_epoch_num=" + str(client_epoch_num)
+    cmd_server += " --client_batch_size=" + str(client_batch_size)
+    cmd_server += " --client_learning_rate=" + str(client_learning_rate)
+    cmd_server += " --encrypt_type=" + str(encrypt_type)
+    cmd_server += " --share_secrets_ratio=" + str(share_secrets_ratio)
+    cmd_server += " --cipher_time_window=" + str(cipher_time_window)
+    cmd_server += " --reconstruct_secrets_threshold=" + str(reconstruct_secrets_threshold)
+    cmd_server += " --dp_eps=" + str(dp_eps)
+    cmd_server += " --dp_delta=" + str(dp_delta)
+    cmd_server += " --dp_norm_clip=" + str(dp_norm_clip)
+    cmd_server += " --dataset_path=" + str(dataset_path)
+    cmd_server += " --user_id=" + str(0)
+    cmd_server += " > server.log 2>&1 &"
+
+    import time
+    time.sleep(0.3)
+    subprocess.call(['bash', '-c', cmd_server])
diff --git a/tests/st/fl/cross_silo_femnist/run_cross_silo_femnist_worker.py b/tests/st/fl/cross_silo_femnist/run_cross_silo_femnist_worker.py
new file mode 100644
index 00000000000..1be35aedb07
--- /dev/null
+++ b/tests/st/fl/cross_silo_femnist/run_cross_silo_femnist_worker.py
@@ -0,0 +1,73 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# Licensed 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.
+# ============================================================================
+
+import argparse
+import subprocess
+
+parser = argparse.ArgumentParser(description="Run test_cross_silo_femnist.py case")
+parser.add_argument("--device_target", type=str, default="GPU")
+parser.add_argument("--server_mode", type=str, default="FEDERATED_LEARNING")
+parser.add_argument("--worker_num", type=int, default=1)
+parser.add_argument("--server_num", type=int, default=2)
+parser.add_argument("--scheduler_ip", type=str, default="127.0.0.1")
+parser.add_argument("--scheduler_port", type=int, default=8113)
+parser.add_argument("--fl_iteration_num", type=int, default=25)
+parser.add_argument("--client_epoch_num", type=int, default=20)
+parser.add_argument("--worker_step_num_per_iteration", type=int, default=65)
+parser.add_argument("--local_worker_num", type=int, default=-1)
+parser.add_argument("--config_file_path", type=str, default="")
+parser.add_argument("--dataset_path", type=str, default="")
+
+args, _ = parser.parse_known_args()
+device_target = args.device_target
+server_mode = args.server_mode
+worker_num = args.worker_num
+server_num = args.server_num
+scheduler_ip = args.scheduler_ip
+scheduler_port = args.scheduler_port
+fl_iteration_num = args.fl_iteration_num
+client_epoch_num = args.client_epoch_num
+worker_step_num_per_iteration = args.worker_step_num_per_iteration
+local_worker_num = args.local_worker_num
+config_file_path = args.config_file_path
+dataset_path = args.dataset_path
+
+if local_worker_num == -1:
+    local_worker_num = worker_num
+
+assert local_worker_num <= worker_num, "The local worker number should not be bigger than total worker number."
+
+for i in range(local_worker_num):
+    cmd_worker = "execute_path=$(pwd) && self_path=$(dirname \"${script_self}\") && "
+    cmd_worker += "rm -rf ${execute_path}/worker_" + str(i) + "/ &&"
+    cmd_worker += "mkdir ${execute_path}/worker_" + str(i) + "/ &&"
+    cmd_worker += "cd ${execute_path}/worker_" + str(i) + "/ || exit && export GLOG_v=1 &&"
+    cmd_worker += "python ${self_path}/../test_cross_silo_femnist.py"
+    cmd_worker += " --device_target=" + device_target
+    cmd_worker += " --server_mode=" + server_mode
+    cmd_worker += " --ms_role=MS_WORKER"
+    cmd_worker += " --worker_num=" + str(worker_num)
+    cmd_worker += " --server_num=" + str(server_num)
+    cmd_worker += " --scheduler_ip=" + scheduler_ip
+    cmd_worker += " --scheduler_port=" + str(scheduler_port)
+    cmd_worker += " --config_file_path=" + str(config_file_path)
+    cmd_worker += " --fl_iteration_num=" + str(fl_iteration_num)
+    cmd_worker += " --client_epoch_num=" + str(client_epoch_num)
+    cmd_worker += " --worker_step_num_per_iteration=" + str(worker_step_num_per_iteration)
+    cmd_worker += " --dataset_path=" + str(dataset_path)
+    cmd_worker += " --user_id=" + str(i)
+    cmd_worker += " > worker.log 2>&1 &"
+
+    subprocess.call(['bash', '-c', cmd_worker])
diff --git a/tests/st/fl/cross_silo_femnist/test_cross_silo_femnist.py b/tests/st/fl/cross_silo_femnist/test_cross_silo_femnist.py
new file mode 100644
index 00000000000..84ca569332e
--- /dev/null
+++ b/tests/st/fl/cross_silo_femnist/test_cross_silo_femnist.py
@@ -0,0 +1,368 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# Licensed 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.
+# ============================================================================
+
+import argparse
+import os
+import time
+import numpy as np
+
+import mindspore
+import mindspore.context as context
+import mindspore.nn as nn
+from mindspore.common.initializer import TruncatedNormal
+from mindspore import Tensor
+import mindspore.dataset as ds
+import mindspore.dataset.vision.py_transforms as PV
+import mindspore.dataset.transforms.py_transforms as PT
+import mindspore.dataset.transforms.c_transforms as tC
+from mindspore.train.serialization import save_checkpoint
+from mindspore.ops import operations as P
+from mindspore.train.callback import Callback
+from mindspore.nn.metrics import Accuracy
+from mindspore.train import Model
+
+parser = argparse.ArgumentParser(description="test_cross_silo_femnist")
+parser.add_argument("--device_target", type=str, default="CPU")
+parser.add_argument("--server_mode", type=str, default="FEDERATED_LEARNING")
+parser.add_argument("--ms_role", type=str, default="MS_WORKER")
+parser.add_argument("--worker_num", type=int, default=1)
+parser.add_argument("--server_num", type=int, default=1)
+parser.add_argument("--scheduler_ip", type=str, default="127.0.0.1")
+parser.add_argument("--scheduler_port", type=int, default=8113)
+parser.add_argument("--fl_server_port", type=int, default=6666)
+parser.add_argument("--start_fl_job_threshold", type=int, default=1)
+parser.add_argument("--start_fl_job_time_window", type=int, default=3000)
+parser.add_argument("--update_model_ratio", type=float, default=1.0)
+parser.add_argument("--update_model_time_window", type=int, default=3000)
+parser.add_argument("--fl_name", type=str, default="Lenet")
+parser.add_argument("--fl_iteration_num", type=int, default=25)
+parser.add_argument("--client_epoch_num", type=int, default=20)
+parser.add_argument("--client_batch_size", type=int, default=32)
+parser.add_argument("--client_learning_rate", type=float, default=0.1)
+parser.add_argument("--worker_step_num_per_iteration", type=int, default=65)
+parser.add_argument("--scheduler_manage_port", type=int, default=11202)
+parser.add_argument("--config_file_path", type=str, default="")
+parser.add_argument("--encrypt_type", type=str, default="NOT_ENCRYPT")
+parser.add_argument("--dp_eps", type=float, default=50.0)
+parser.add_argument("--dp_delta", type=float, default=0.01)
+parser.add_argument("--dp_norm_clip", type=float, default=1.0)
+parser.add_argument("--share_secrets_ratio", type=float, default=1.0)
+parser.add_argument("--cipher_time_window", type=int, default=300000)
+parser.add_argument("--reconstruct_secrets_threshold", type=int, default=3)
+parser.add_argument("--dataset_path", type=str, default="")
+parser.add_argument("--user_id", type=str, default="0")
+
+parser.add_argument('--img_size', type=int, default=(32, 32, 1), help='the image size of (h,w,c)')
+parser.add_argument('--batch_size', type=float, default=32, help='batch size')
+parser.add_argument('--repeat_size', type=int, default=1, help='the repeat size when create the dataLoader')
+
+args, _ = parser.parse_known_args()
+device_target = args.device_target
+server_mode = args.server_mode
+ms_role = args.ms_role
+worker_num = args.worker_num
+server_num = args.server_num
+scheduler_ip = args.scheduler_ip
+scheduler_port = args.scheduler_port
+fl_server_port = args.fl_server_port
+start_fl_job_threshold = args.start_fl_job_threshold
+start_fl_job_time_window = args.start_fl_job_time_window
+update_model_ratio = args.update_model_ratio
+update_model_time_window = args.update_model_time_window
+fl_name = args.fl_name
+fl_iteration_num = args.fl_iteration_num
+client_epoch_num = args.client_epoch_num
+client_batch_size = args.client_batch_size
+client_learning_rate = args.client_learning_rate
+worker_step_num_per_iteration = args.worker_step_num_per_iteration
+scheduler_manage_port = args.scheduler_manage_port
+config_file_path = args.config_file_path
+encrypt_type = args.encrypt_type
+share_secrets_ratio = args.share_secrets_ratio
+cipher_time_window = args.cipher_time_window
+reconstruct_secrets_threshold = args.reconstruct_secrets_threshold
+dp_eps = args.dp_eps
+dp_delta = args.dp_delta
+dp_norm_clip = args.dp_norm_clip
+dataset_path = args.dataset_path
+user_id = args.user_id
+
+ctx = {
+    "enable_fl": True,
+    "server_mode": server_mode,
+    "ms_role": ms_role,
+    "worker_num": worker_num,
+    "server_num": server_num,
+    "scheduler_ip": scheduler_ip,
+    "scheduler_port": scheduler_port,
+    "fl_server_port": fl_server_port,
+    "start_fl_job_threshold": start_fl_job_threshold,
+    "start_fl_job_time_window": start_fl_job_time_window,
+    "update_model_ratio": update_model_ratio,
+    "update_model_time_window": update_model_time_window,
+    "fl_name": fl_name,
+    "fl_iteration_num": fl_iteration_num,
+    "client_epoch_num": client_epoch_num,
+    "client_batch_size": client_batch_size,
+    "client_learning_rate": client_learning_rate,
+    "worker_step_num_per_iteration": worker_step_num_per_iteration,
+    "scheduler_manage_port": scheduler_manage_port,
+    "config_file_path": config_file_path,
+    "share_secrets_ratio": share_secrets_ratio,
+    "cipher_time_window": cipher_time_window,
+    "reconstruct_secrets_threshold": reconstruct_secrets_threshold,
+    "dp_eps": dp_eps,
+    "dp_delta": dp_delta,
+    "dp_norm_clip": dp_norm_clip,
+    "encrypt_type": encrypt_type
+}
+
+context.set_context(mode=context.GRAPH_MODE, device_target=device_target, save_graphs=False)
+context.set_fl_context(**ctx)
+
+
+def conv(in_channels, out_channels, kernel_size, stride=1, padding=0):
+    """weight initial for conv layer"""
+    weight = weight_variable()
+    return nn.Conv2d(
+        in_channels,
+        out_channels,
+        kernel_size=kernel_size,
+        stride=stride,
+        padding=padding,
+        weight_init=weight,
+        has_bias=False,
+        pad_mode="valid",
+    )
+
+
+def fc_with_initialize(input_channels, out_channels):
+    """weight initial for fc layer"""
+    weight = weight_variable()
+    bias = weight_variable()
+    return nn.Dense(input_channels, out_channels, weight, bias)
+
+
+def weight_variable():
+    """weight initial"""
+    return TruncatedNormal(0.02)
+
+
+class LeNet5(nn.Cell):
+    def __init__(self, num_class=10, channel=3):
+        super(LeNet5, self).__init__()
+        self.num_class = num_class
+        self.conv1 = conv(channel, 6, 5)
+        self.conv2 = conv(6, 16, 5)
+        self.fc1 = fc_with_initialize(16 * 5 * 5, 120)
+        self.fc2 = fc_with_initialize(120, 84)
+        self.fc3 = fc_with_initialize(84, self.num_class)
+        self.relu = nn.ReLU()
+        self.max_pool2d = nn.MaxPool2d(kernel_size=2, stride=2)
+        self.flatten = nn.Flatten()
+
+    def construct(self, x):
+        x = self.conv1(x)
+        x = self.relu(x)
+        x = self.max_pool2d(x)
+        x = self.conv2(x)
+        x = self.relu(x)
+        x = self.max_pool2d(x)
+        x = self.flatten(x)
+        x = self.fc1(x)
+        x = self.relu(x)
+        x = self.fc2(x)
+        x = self.relu(x)
+        x = self.fc3(x)
+        return x
+
+
+class LossGet(Callback):
+    # define loss callback for packaged model
+    def __init__(self, per_print_times, data_size):
+        super(LossGet, self).__init__()
+        if not isinstance(per_print_times, int) or per_print_times < 0:
+            raise ValueError("print_step must be int and >= 0.")
+        self._per_print_times = per_print_times
+        self._loss = 0.0
+        self.data_size = data_size
+        self.loss_list = []
+
+    def step_end(self, run_context):
+        cb_params = run_context.original_args()
+        loss = cb_params.net_outputs
+
+        if isinstance(loss, (tuple, list)):
+            if isinstance(loss[0], Tensor) and isinstance(loss[0].asnumpy(), np.ndarray):
+                loss = loss[0]
+
+        if isinstance(loss, Tensor) and isinstance(loss.asnumpy(), np.ndarray):
+            loss = np.mean(loss.asnumpy())
+
+        cur_step_in_epoch = (cb_params.cur_step_num - 1) % cb_params.batch_num + 1
+
+        if isinstance(loss, float) and (np.isnan(loss) or np.isinf(loss)):
+            raise ValueError("epoch: {} step: {}. Invalid loss, terminating training."
+                             .format(cb_params.cur_epoch_num, cur_step_in_epoch))
+        if self._per_print_times != 0 and cb_params.cur_step_num % self._per_print_times == 0:
+            self._loss = loss
+            self.loss_list.append(loss)
+
+    def epoch_begin(self, run_context):
+        self.epoch_time = time.time()
+
+    def epoch_end(self, run_context):
+        epoch_mseconds = (time.time() - self.epoch_time) * 1000
+        self._per_step_mseconds = epoch_mseconds / self.data_size
+
+    def get_loss(self):
+        return self.loss_list  # todo return self._loss
+
+    def get_per_step_time(self):
+        return self._per_step_mseconds
+
+
+def mkdir(path):
+    if not os.path.exists(path):
+        os.mkdir(path)
+
+
+def count_id(path):
+    files = os.listdir(path)
+    ids = {}
+    for i in files:
+        ids[i] = int(i)
+    return ids
+
+
+def create_dataset_from_folder(data_path, img_size, batch_size=32, repeat_size=1, num_parallel_workers=1,
+                               shuffle=False):
+    """ create dataset for train or test
+        Args:
+            data_path: Data path
+            batch_size: The number of data records in each group
+            repeat_size: The number of replicated data records
+            num_parallel_workers: The number of parallel workers
+        """
+    # define dataset
+    ids = count_id(data_path)
+    mnist_ds = ds.ImageFolderDataset(dataset_dir=data_path, decode=False, class_indexing=ids)
+    # define operation parameters
+    resize_height, resize_width = img_size[0], img_size[1]
+
+    transform = [
+        PV.Decode(),
+        PV.Grayscale(1),
+        PV.Resize(size=(resize_height, resize_width)),
+        PV.Grayscale(3),
+        PV.ToTensor()
+    ]
+    compose = PT.Compose(transform)
+
+    # apply map operations on images
+    mnist_ds = mnist_ds.map(input_columns="label", operations=tC.TypeCast(mindspore.int32))
+    mnist_ds = mnist_ds.map(input_columns="image", operations=compose)
+
+    # apply DatasetOps
+    buffer_size = 10000
+    if shuffle:
+        mnist_ds = mnist_ds.shuffle(buffer_size=buffer_size)  # 10000 as in LeNet train script
+    mnist_ds = mnist_ds.batch(batch_size, drop_remainder=True)
+    mnist_ds = mnist_ds.repeat(repeat_size)
+    return mnist_ds
+
+
+def evalute_process(model, eval_data, img_size, batch_size):
+    """Define the evaluation method."""
+    ds_eval = create_dataset_from_folder(eval_data, img_size, batch_size)
+    acc = model.eval(ds_eval, dataset_sink_mode=False)
+    return acc['Accuracy'], acc['Loss']
+
+
+class StartFLJob(nn.Cell):
+    def __init__(self, data_size):
+        super(StartFLJob, self).__init__()
+        self.start_fl_job = P.StartFLJob(data_size)
+
+    def construct(self):
+        return self.start_fl_job()
+
+
+class UpdateAndGetModel(nn.Cell):
+    def __init__(self, weights):
+        super(UpdateAndGetModel, self).__init__()
+        self.update_model = P.UpdateModel()
+        self.get_model = P.GetModel()
+        self.weights = weights
+
+    def construct(self):
+        self.update_model(self.weights)
+        get_model = self.get_model(self.weights)
+        return get_model
+
+
+def train():
+    epoch = client_epoch_num
+    network = LeNet5(62, 3)
+
+    # define the loss function
+    net_loss = nn.SoftmaxCrossEntropyWithLogits(sparse=True, reduction='mean')
+    # define the optimizer
+    net_opt = nn.Momentum(network.trainable_params(), 0.01, 0.9)
+    model = Model(network, net_loss, net_opt, metrics={"Accuracy": Accuracy(), 'Loss': nn.Loss()})
+
+    ds.config.set_seed(1)
+    data_root_path = dataset_path
+    user = "dataset_" + user_id
+    train_path = os.path.join(data_root_path, user, "train")
+    test_path = os.path.join(data_root_path, user, "test")
+
+    dataset = create_dataset_from_folder(train_path, args.img_size, args.batch_size, args.repeat_size)
+    print("size is ", dataset.get_dataset_size(), flush=True)
+    num_batches = dataset.get_dataset_size()
+
+    loss_cb = LossGet(1, num_batches)
+    cbs = []
+    cbs.append(loss_cb)
+    ckpt_path = "ckpt"
+    os.makedirs(ckpt_path)
+
+    for iter_num in range(fl_iteration_num):
+        if context.get_fl_context("ms_role") == "MS_WORKER":
+            start_fl_job = StartFLJob(dataset.get_dataset_size() * args.batch_size)
+            start_fl_job()
+
+        for _ in range(epoch):
+            print("step is ", epoch, flush=True)
+            model.train(1, dataset, callbacks=cbs, dataset_sink_mode=False)
+
+        if context.get_fl_context("ms_role") == "MS_WORKER":
+            update_and_get_model = UpdateAndGetModel(net_opt.parameters)
+            update_and_get_model()
+
+        ckpt_name = user_id + "-fl-ms-bs32-" + str(iter_num) + "epoch.ckpt"
+        ckpt_name = os.path.join(ckpt_path, ckpt_name)
+        save_checkpoint(network, ckpt_name)
+
+        train_acc, _ = evalute_process(model, train_path, args.img_size, args.batch_size)
+        test_acc, _ = evalute_process(model, test_path, args.img_size, args.batch_size)
+        loss_list = loss_cb.get_loss()
+        loss = sum(loss_list) / len(loss_list)
+        print('local epoch: {}, loss: {}, trian acc: {}, test acc: {}'.format(iter_num, loss, train_acc, test_acc),
+              flush=True)
+
+
+if __name__ == "__main__":
+    train()
diff --git a/tests/ut/cpp/CMakeLists.txt b/tests/ut/cpp/CMakeLists.txt
index a36a3e676a9..f8cebf1cc0e 100644
--- a/tests/ut/cpp/CMakeLists.txt
+++ b/tests/ut/cpp/CMakeLists.txt
@@ -176,6 +176,7 @@ list(REMOVE_ITEM MINDSPORE_SRC_LIST "../../../mindspore/ccsrc/ps/ps_cache/gpu/gp
 list(REMOVE_ITEM MINDSPORE_SRC_LIST "../../../mindspore/ccsrc/ps/ps_cache/ascend/ascend_ps_cache.cc")
 list(REMOVE_ITEM MINDSPORE_SRC_LIST "../../../mindspore/ccsrc/ps/ps_cache/ps_cache_manager.cc")
 list(REMOVE_ITEM MINDSPORE_SRC_LIST "../../../mindspore/ccsrc/fl/server/kernel/apply_momentum_kernel.cc")
+list(REMOVE_ITEM MINDSPORE_SRC_LIST "../../../mindspore/ccsrc/fl/server/kernel/sgd_kernel.cc")
 list(REMOVE_ITEM MINDSPORE_SRC_LIST "../../../mindspore/ccsrc/backend/optimizer/gpu/batch_norm_add_relu_fusion.cc")
 list(REMOVE_ITEM MINDSPORE_SRC_LIST "../../../mindspore/ccsrc/backend/optimizer/gpu/post_batch_norm_add_relu_fusion.cc")
 list(REMOVE_ITEM MINDSPORE_SRC_LIST "../../../mindspore/ccsrc/backend/optimizer/gpu/batch_norm_add_relu_grad_fusion.cc")