diff --git a/mindspore/ccsrc/runtime/device/ascend/ascend_device_address.cc b/mindspore/ccsrc/runtime/device/ascend/ascend_device_address.cc
index a490f95fc62a85b80c9ff8099e05a7e10561c3dd..26dbef12e4327211b7d23094b23fc026d7d5cdba 100644
--- a/mindspore/ccsrc/runtime/device/ascend/ascend_device_address.cc
+++ b/mindspore/ccsrc/runtime/device/ascend/ascend_device_address.cc
@@ -16,14 +16,19 @@
 #include "runtime/device/ascend/ascend_device_address.h"
 #include <memory>
 #include <vector>
+#include <unordered_map>
+#include <utility>
 #include <set>
 #include <algorithm>
 #include "runtime/mem.h"
 #include "runtime/device/kernel_runtime_manager.h"
+#include "runtime/device/kernel_runtime.h"
 #include "runtime/device/convert_tensor_utils.h"
 #include "ir/dtype/type.h"
 #include "ir/tensor.h"
 #include "backend/kernel_compiler/common_utils.h"
+#include "backend/kernel_compiler/tbe/tbe_kernel_build.h"
+#include "backend/kernel_compiler/tbe/tbe_kernel_parallel_build.h"
 #include "utils/utils.h"
 #include "common/utils.h"
 #include "common/trans.h"
@@ -34,6 +39,58 @@
 #include "debug/tensor_load.h"
 #endif
 
+namespace {
+const std::unordered_map<mindspore::TypeId, std::string> type_id_name_map = {
+  {mindspore::kNumberTypeBool, "bool"},       {mindspore::kNumberTypeInt8, "int8"},
+  {mindspore::kNumberTypeInt16, "int16"},     {mindspore::kNumberTypeInt32, "int32"},
+  {mindspore::kNumberTypeInt64, "int64"},     {mindspore::kNumberTypeFloat16, "float16"},
+  {mindspore::kNumberTypeFloat32, "float32"}, {mindspore::kNumberTypeUInt8, "uint8"},
+  {mindspore::kNumberTypeUInt16, "uint16"},   {mindspore::kNumberTypeUInt32, "uint32"},
+  {mindspore::kNumberTypeUInt64, "uint64"}};
+const std::set<std::pair<std::string, std::string>> use_trans_data = {
+  std::make_pair("float16", mindspore::kOpFormat_NC1HWC0), std::make_pair("float32", mindspore::kOpFormat_NC1HWC0),
+  std::make_pair("bool", mindspore::kOpFormat_NC1HWC0),    std::make_pair("float32", mindspore::kOpFormat_FRAC_Z),
+  std::make_pair("float16", mindspore::kOpFormat_FRAC_Z),  std::make_pair("float16", mindspore::kOpFormat_FRAC_NZ),
+  std::make_pair("float32", mindspore::kOpFormat_FRAC_NZ), std::make_pair("int32", mindspore::kOpFormat_FRAC_NZ),
+  std::make_pair("float16", mindspore::kOpFormat_NHWC),    std::make_pair("float32", mindspore::kOpFormat_NHWC),
+  std::make_pair("int8", mindspore::kOpFormat_NHWC),       std::make_pair("int16", mindspore::kOpFormat_NHWC),
+  std::make_pair("int32", mindspore::kOpFormat_NHWC),      std::make_pair("int64", mindspore::kOpFormat_NHWC),
+  std::make_pair("uint8", mindspore::kOpFormat_NHWC),      std::make_pair("uint16", mindspore::kOpFormat_NHWC),
+  std::make_pair("uint32", mindspore::kOpFormat_NHWC),     std::make_pair("uint64", mindspore::kOpFormat_NHWC),
+  std::make_pair("float16", mindspore::kOpFormat_HWCN),    std::make_pair("float32", mindspore::kOpFormat_HWCN),
+  std::make_pair("int8", mindspore::kOpFormat_HWCN),       std::make_pair("int16", mindspore::kOpFormat_HWCN),
+  std::make_pair("int32", mindspore::kOpFormat_HWCN),      std::make_pair("int64", mindspore::kOpFormat_HWCN),
+  std::make_pair("uint8", mindspore::kOpFormat_HWCN),      std::make_pair("uint16", mindspore::kOpFormat_HWCN),
+  std::make_pair("uint32", mindspore::kOpFormat_HWCN),     std::make_pair("uint64", mindspore::kOpFormat_HWCN)};
+constexpr auto src_format = "src_format";
+constexpr auto dst_format = "dst_format";
+constexpr auto src = "src_0";
+constexpr auto dst = "dst";
+constexpr auto param_type_required = "required";
+constexpr auto gen_model_single = "single";
+constexpr auto trans_data = "trans_data";
+constexpr auto platform_tbe = "TBE";
+constexpr auto name = "name";
+constexpr auto valid = "valid";
+constexpr auto value = "value";
+constexpr auto dtype = "dtype";
+constexpr auto format_str = "format";
+constexpr auto ori_format = "ori_format";
+constexpr auto ori_shape = "ori_shape";
+constexpr auto param_type = "param_type";
+constexpr auto shape_str = "shape";
+constexpr auto process_aicore = "aicore";
+constexpr auto gen_model_str = "gen_model";
+constexpr auto impl_path_str = "impl_path";
+constexpr auto attrs_str = "attrs";
+constexpr auto inputs_str = "inputs";
+constexpr auto outputs_str = "outputs";
+constexpr auto kernel_name_str = "kernel_name";
+constexpr auto op_info_str = "op_info";
+constexpr auto platform_str = "platform";
+constexpr auto fractal_z = "FRACTAL_Z";
+}  // namespace
+
 namespace mindspore {
 namespace device {
 namespace ascend {
@@ -96,6 +153,102 @@ bool SyncDeviceToHostAndFloatToFloat64(void *dst, size_t dst_size, const void *s
   return true;
 }
 
+size_t GetCommonAlignSize(size_t input_size) {
+  return (input_size + kMemAlignSize + 31) / kMemAlignSize * kMemAlignSize;
+}
+
+nlohmann::json ConstructAttrs(const std::string &format) {
+  nlohmann::json real_attr;
+  nlohmann::json src_attr;
+  nlohmann::json des_attr;
+  src_attr[name] = src_format;
+  src_attr[valid] = true;
+  if (format == kOpFormat_FRAC_Z) {
+    src_attr[value] = fractal_z;
+  } else {
+    src_attr[value] = format;
+  }
+  des_attr[name] = dst_format;
+  des_attr[valid] = true;
+  des_attr[value] = kOpFormat_NCHW;
+  real_attr.push_back(src_attr);
+  real_attr.push_back(des_attr);
+  return real_attr;
+}
+
+nlohmann::json ConstructInputs(const std::vector<size_t> &input_shape, const std::vector<size_t> &output_shape,
+                               const std::string &format, mindspore::TypeId type) {
+  nlohmann::json input;
+  nlohmann::json input_json;
+  nlohmann::json real_input;
+  real_input[dtype] = type_id_name_map.at(type);
+  if (format == kOpFormat_FRAC_Z) {
+    real_input[format_str] = fractal_z;
+  } else {
+    real_input[format_str] = format;
+  }
+  real_input[name] = src;
+  real_input[ori_format] = kOpFormat_NCHW;
+  for (auto shape : output_shape) {
+    real_input[ori_shape].push_back(shape);
+  }
+  real_input[param_type] = param_type_required;
+  // obtain inputs shape
+  for (auto shape : input_shape) {
+    real_input[shape_str].push_back(shape);
+  }
+  real_input[valid] = true;
+  input_json.push_back(real_input);
+  input.push_back(input_json);
+  return input;
+}
+
+nlohmann::json ConstructOutputs(const std::vector<size_t> &output_shape, mindspore::TypeId type) {
+  nlohmann::json output;
+  nlohmann::json output_json;
+  nlohmann::json real_output;
+  real_output[dtype] = type_id_name_map.at(type);
+  real_output[format_str] = kOpFormat_NCHW;
+  real_output[name] = dst;
+  real_output[ori_format] = kOpFormat_NCHW;
+  for (auto shape : output_shape) {
+    real_output[ori_shape].push_back(shape);
+  }
+  real_output[param_type] = param_type_required;
+  // obtain outputs shape
+  for (auto shape : output_shape) {
+    real_output[shape_str].push_back(shape);
+  }
+  real_output[valid] = true;
+  output_json.push_back(real_output);
+  output.push_back(output_json);
+  return output;
+}
+
+nlohmann::json ConstructTransDataKernelJson(const std::vector<size_t> &host_shape,
+                                            const std::vector<size_t> &device_shape, const std::string &format,
+                                            mindspore::TypeId type) {
+  // generate kernel json
+  nlohmann::json kernel_json;
+  kernel_json[gen_model_str] = gen_model_single;
+  kernel_json[impl_path_str] = "";
+  // construct op_info
+  nlohmann::json op_info;
+  op_info[attrs_str] = ConstructAttrs(format);
+  op_info[inputs_str] = ConstructInputs(device_shape, host_shape, format, type);
+  op_info[kernel_name_str] = "";
+  op_info[name] = trans_data;
+  op_info[outputs_str] = ConstructOutputs(host_shape, type);
+  kernel_json[op_info_str] = op_info;
+  kernel_json[platform_str] = platform_tbe;
+  std::string json_str = kernel_json[op_info_str].dump();
+  size_t hash_id = std::hash<std::string>()(json_str);
+  const std::string op_name = op_info[name];
+  const std::string json_name = op_name + "_" + std::to_string(hash_id);
+  kernel_json[op_info_str][kernel_name_str] = json_name;
+  return kernel_json;
+}
+
 void AscendDeviceAddress::SyncStream() const {
   MS_LOG(INFO) << "Start!";
   auto ms_context = MsContext::GetInstance();
@@ -158,31 +311,186 @@ bool AscendDeviceAddress::SyncDeviceToHost(const std::vector<int> &shape, size_t
   return sync_ok;
 }
 
+void AscendDeviceAddress::LaunchTransData(kernel::KernelModPtr kernel_mod_ptr, void *output_address_ptr,
+                                          size_t output_size, const std::vector<size_t> &workspace_size_list) const {
+  MS_EXCEPTION_IF_NULL(kernel_mod_ptr);
+  auto input_address = std::make_shared<kernel::Address>();
+  MS_EXCEPTION_IF_NULL(input_address);
+  input_address->addr = ptr_;
+  input_address->size = size_;
+  auto output_address = std::make_shared<kernel::Address>();
+  MS_EXCEPTION_IF_NULL(output_address);
+  output_address->addr = output_address_ptr;
+  output_address->size = output_size;
+  AddressPtrList kernel_inputs = {input_address};
+  AddressPtrList kernel_outputs = {output_address};
+  AddressPtrList kernel_workspaces;
+  std::vector<void *> workspaces_address_ptr(workspace_size_list.size(), nullptr);
+  if (!workspace_size_list.empty()) {
+    for (size_t i = 0; i < workspace_size_list.size(); ++i) {
+      auto workspace_size = GetCommonAlignSize(workspace_size_list[i]);
+      auto ret_malloc = rtMalloc(&workspaces_address_ptr[i], workspace_size, RT_MEMORY_HBM);
+      if (ret_malloc != RT_ERROR_NONE) {
+        MS_LOG(ERROR) << "Failed to rtMalloc memory";
+      }
+      auto workspace_address = std::make_shared<kernel::Address>();
+      MS_EXCEPTION_IF_NULL(workspace_address);
+      workspace_address->addr = workspaces_address_ptr[i];
+      workspace_address->size = workspace_size;
+      kernel_workspaces.push_back(workspace_address);
+    }
+  }
+  auto ms_context = MsContext::GetInstance();
+  MS_EXCEPTION_IF_NULL(ms_context);
+  auto device_id = ms_context->device_id();
+  auto runtime_instance = device::KernelRuntimeManager::Instance().GetKernelRuntime(kAscendDevice, device_id);
+  MS_EXCEPTION_IF_NULL(runtime_instance);
+  auto ret =
+    runtime_instance->LaunchTaskBasedOnSingleKernel(kernel_mod_ptr, kernel_inputs, kernel_outputs, kernel_workspaces);
+  if (!ret) {
+    MS_LOG(ERROR) << "Launch kernel failed.";
+  }
+  SyncStream();
+  if (!workspace_size_list.empty()) {
+    for (size_t i = 0; i < workspace_size_list.size(); ++i) {
+      auto ret_free = rtFree(workspaces_address_ptr[i]);
+      if (ret_free != RT_ERROR_NONE) {
+        MS_LOG(ERROR) << "Failed to rtFree memory";
+      }
+    }
+  }
+}
+
+kernel::KernelModPtr AscendDeviceAddress::CompileTransDataAndObtainKernelMod(const nlohmann::json &kernel_json) const {
+  static std::set<std::string> constructed_kernel;
+  auto build_manager = std::make_shared<kernel::ParallelBuildManager>();
+  MS_EXCEPTION_IF_NULL(build_manager);
+  std::string processor = process_aicore;
+  // get size
+  std::vector<size_t> input_size_list;
+  std::vector<size_t> output_size_list;
+  (void)kernel::TbeKernelBuild::GetIOSize(kernel_json, &input_size_list, &output_size_list);
+  std::string json_name = kernel_json[op_info_str][kernel_name_str];
+  // op build
+  if (constructed_kernel.find(json_name) == constructed_kernel.end()) {
+    auto task_id = build_manager->StartCompileOp(kernel_json);
+    build_manager->SaveTaskInfo(task_id, nullptr, json_name, input_size_list, output_size_list);
+  }
+  while (!build_manager->IsAllTaskFinish()) {
+    int task_id = -1;
+    char *task_result = nullptr;
+    char *pre_build_result = nullptr;
+    auto ret = build_manager->WaitOne(&task_id, &task_result, &pre_build_result);
+    if (!ret) {
+      MS_EXCEPTION(ArgumentError) << "Build Failed. wait one ret:" << ret << ", task id:" << task_id;
+    }
+    if ((task_result != nullptr) && (strcmp(task_result, "Success") != 0)) {
+      MS_EXCEPTION(ArgumentError) << "task compile Failed, task id:" << task_id << ", cause:" << task_result;
+    }
+    (void)build_manager->TaskFinishProcess(task_id, false);
+  }
+  constructed_kernel.insert(json_name);
+  // search cache
+  auto cached_kernel_pack = TbeUtils::SearchCache(json_name, processor);
+  MS_EXCEPTION_IF_NULL(cached_kernel_pack);
+  auto kernel_mod_ptr =
+    build_manager->GenKernelMod(json_name, processor, input_size_list, output_size_list, cached_kernel_pack);
+  return kernel_mod_ptr;
+}
+
+bool AscendDeviceAddress::SyncDeviceToHostAndConvertFormatBasedOnTransData(const std::vector<size_t> &host_shape,
+                                                                           const std::vector<size_t> &device_shape,
+                                                                           size_t size, mindspore::TypeId type,
+                                                                           void *host_ptr) const {
+  bool sync_ok = true;
+  // construct trans data kernel json
+  nlohmann::json kernel_json = ConstructTransDataKernelJson(host_shape, device_shape, format_, type_id_);
+  MS_LOG(INFO) << "Construct trans_data kernel json: " << kernel_json.dump();
+  auto kernel_mod_ptr = CompileTransDataAndObtainKernelMod(kernel_json);
+  MS_EXCEPTION_IF_NULL(kernel_mod_ptr);
+  auto host_size = size;
+  if (type_id_ != type) {
+    auto device_dtype_size = trans::TypeIdSize(type_id_);
+    if (device_dtype_size < 1) {
+      MS_LOG(ERROR) << "Illegal dtype.";
+    }
+    auto shape_size = trans::ShapeSize(host_shape);
+    auto size_tmp = device_dtype_size * shape_size;
+    size = GetCommonAlignSize(size_tmp);
+  }
+  void *output_address_ptr = nullptr;
+  auto ret_malloc = rtMalloc(&output_address_ptr, size, RT_MEMORY_HBM);
+  if (ret_malloc != RT_ERROR_NONE) {
+    MS_LOG(ERROR) << "Failed to rtMalloc memory";
+  }
+  auto workspace_size_list = GetWorkspaceSizeList(kernel_json);
+  // launch
+  LaunchTransData(kernel_mod_ptr, output_address_ptr, size, workspace_size_list);
+  if (type_id_ == type) {
+    SyncMemory(host_ptr, output_address_ptr, size, RT_MEMCPY_DEVICE_TO_HOST);
+  } else {
+    auto host = std::vector<uint8_t>(size);
+    SyncMemory(host.data(), output_address_ptr, size, RT_MEMCPY_DEVICE_TO_HOST);
+    auto shape_size = trans::ShapeSize(host_shape);
+    const trans::TypeIdArgs type_args{host.data(), shape_size, type_id_, type, host_size};
+    sync_ok = trans::TransDataType(type_args, host_ptr);
+    if (!sync_ok) {
+      MS_LOG(ERROR) << "Trans format failed.";
+      return false;
+    }
+  }
+  auto ret_free = rtFree(output_address_ptr);
+  if (ret_free != RT_ERROR_NONE) {
+    MS_LOG(ERROR) << "Failed to rtFree memory";
+  }
+  return sync_ok;
+}
+
+std::vector<size_t> AscendDeviceAddress::GetWorkspaceSizeList(const nlohmann::json &kernel_json) const {
+  std::string json_name = kernel_json[op_info_str][kernel_name_str];
+  std::string processor = process_aicore;
+  auto cached_kernel_pack = TbeUtils::SearchCache(json_name, processor);
+  MS_EXCEPTION_IF_NULL(cached_kernel_pack);
+  auto kernel_json_info = cached_kernel_pack->kernel_json_info();
+  return kernel_json_info.workspaces;
+}
+
+std::vector<size_t> AscendDeviceAddress::GetDeviceShape(std::vector<size_t> *host_shape) const {
+  std::vector<size_t> device_shape;
+  if (format_ == kOpFormat_FRAC_NZ || format_ == kOpFormat_NDHWC) {
+    device_shape = trans::TransShapeToDevice(*host_shape, format_);
+  } else {
+    if (host_shape_.empty()) {
+      *host_shape = trans::PaddingShapeTo4d(*host_shape);
+    } else {
+      host_shape->clear();
+      (void)std::transform(host_shape_.begin(), host_shape_.end(), std::back_inserter(*host_shape), IntToSize);
+    }
+    device_shape = trans::TransShapeToDevice(*host_shape, format_);
+  }
+  return device_shape;
+}
+
 bool AscendDeviceAddress::SyncDeviceToHostAndConvertFormat(const std::vector<int> &shape, size_t size,
                                                            mindspore::TypeId type, void *host_ptr) const {
   MS_LOG(INFO) << "SyncDeviceToHostAndConvertFormat, Device(format:" << format_ << ", type_id:" << TypeIdLabel(type_id_)
                << ", size:" << size_ << "), Host(type_id:" << TypeIdLabel(type) << ", size:" << size << ")";
   bool sync_ok = false;
-  auto host_tmp = std::vector<uint8_t>(size_);
-  SyncMemory(host_tmp.data(), ptr_, size_, RT_MEMCPY_DEVICE_TO_HOST);
   std::vector<size_t> host_shape;
   (void)std::transform(shape.begin(), shape.end(), std::back_inserter(host_shape), IntToSize);
-  std::vector<size_t> device_shape;
   if (host_shape.empty()) {
     host_shape.emplace_back(1);
   }
-  if (format_ == kOpFormat_FRAC_NZ || format_ == kOpFormat_NDHWC) {
-    device_shape = trans::TransShapeToDevice(host_shape, format_);
-  } else {
-    if (host_shape_.empty()) {
-      host_shape = trans::PaddingShapeTo4d(host_shape);
-    } else {
-      host_shape.clear();
-      (void)std::transform(host_shape_.begin(), host_shape_.end(), std::back_inserter(host_shape), IntToSize);
+  std::vector<size_t> device_shape = GetDeviceShape(&host_shape);
+  if (type_id_name_map.find(type_id_) != type_id_name_map.end()) {
+    std::pair<std::string, std::string> type_format = std::make_pair(type_id_name_map.at(type_id_), format_);
+    if (use_trans_data.find(type_format) != use_trans_data.end()) {
+      sync_ok = SyncDeviceToHostAndConvertFormatBasedOnTransData(host_shape, device_shape, size, type, host_ptr);
+      return sync_ok;
     }
-
-    device_shape = trans::TransShapeToDevice(host_shape, format_);
   }
+  auto host_tmp = std::vector<uint8_t>(size_);
+  SyncMemory(host_tmp.data(), ptr_, size_, RT_MEMCPY_DEVICE_TO_HOST);
   if (type_id_ != type) {
     const trans::FormatArgs format_args{host_tmp.data(), size_,        kOpFormat_NCHW, format_,
                                         host_shape,      device_shape, type_id_};
diff --git a/mindspore/ccsrc/runtime/device/ascend/ascend_device_address.h b/mindspore/ccsrc/runtime/device/ascend/ascend_device_address.h
index b554e560cf773fc09efa65524c51113d0839666d..6f1bec2d1581afeb98be039c459c21eadbcc3dc1 100644
--- a/mindspore/ccsrc/runtime/device/ascend/ascend_device_address.h
+++ b/mindspore/ccsrc/runtime/device/ascend/ascend_device_address.h
@@ -20,9 +20,11 @@
 #include <string>
 #include <vector>
 #include <memory>
+#include <nlohmann/json.hpp>
 #include "runtime/device/device_address.h"
 #include "runtime/device/ascend/ascend_memory_pool.h"
 #include "ir/dtype.h"
+#include "backend/kernel_compiler/kernel.h"
 
 namespace mindspore {
 #ifdef ENABLE_DEBUGGER
@@ -53,7 +55,16 @@ class AscendDeviceAddress : public DeviceAddress {
   bool SyncDeviceToHostAndConvertFormat(const std::vector<int> &shape, size_t size, TypeId type, void *host_ptr) const;
   bool ConvertFormatAndSyncHostToDevice(const std::vector<int> &shape, size_t size, TypeId type,
                                         const void *host_ptr) const;
+  bool SyncDeviceToHostAndConvertFormatBasedOnTransData(const std::vector<size_t> &host_shape,
+                                                        const std::vector<size_t> &device_shape, size_t size,
+                                                        mindspore::TypeId type, void *host_ptr) const;
   void SyncStream() const;
+
+  void LaunchTransData(kernel::KernelModPtr kernel_mod_ptr, void *output_address_ptr, size_t output_size,
+                       const std::vector<size_t> &workspace_size_list) const;
+  std::vector<size_t> GetDeviceShape(std::vector<size_t> *host_shape) const;
+  std::vector<size_t> GetWorkspaceSizeList(const nlohmann::json &kernel_json) const;
+  kernel::KernelModPtr CompileTransDataAndObtainKernelMod(const nlohmann::json &kernel_json) const;
 };
 using AscendDeviceAddressPtr = std::shared_ptr<AscendDeviceAddress>;
 }  // namespace ascend
diff --git a/mindspore/ccsrc/runtime/device/kernel_runtime.cc b/mindspore/ccsrc/runtime/device/kernel_runtime.cc
index d6cce971c2565168866931eecda7e60bda1e7a39..77d19e6121710c14027ddd15ccad9fe2a5c12c1c 100644
--- a/mindspore/ccsrc/runtime/device/kernel_runtime.cc
+++ b/mindspore/ccsrc/runtime/device/kernel_runtime.cc
@@ -757,6 +757,18 @@ void KernelRuntime::ClearGraphRuntimeResource(uint32_t graph_id) {
   MS_LOG(INFO) << "Clear graph:" << graph_id << " runtime resource";
 }
 
+bool KernelRuntime::LaunchTaskBasedOnSingleKernel(kernel::KernelModPtr kernel_mod_ptr, AddressPtrList kernel_inputs,
+                                                  AddressPtrList kernel_outputs,
+                                                  AddressPtrList kernel_workspaces) const {
+  MS_EXCEPTION_IF_NULL(kernel_mod_ptr);
+  auto ret = kernel_mod_ptr->Launch(kernel_inputs, kernel_workspaces, kernel_outputs, stream_);
+  if (!ret) {
+    MS_LOG(ERROR) << "Launch kernel failed.";
+    return false;
+  }
+  return true;
+}
+
 #ifdef ENABLE_DUMP_E2E
 bool KernelRuntime::SetDumpConf() {
   dump_conf_ptr_ = std::make_shared<Dump>();
diff --git a/mindspore/ccsrc/runtime/device/kernel_runtime.h b/mindspore/ccsrc/runtime/device/kernel_runtime.h
index 41cbd6f4e4912b3d5e7105df5aaf0b8a0f1f672d..e84b55f00778a6e4d9619d1543201cb2bcd04c8c 100644
--- a/mindspore/ccsrc/runtime/device/kernel_runtime.h
+++ b/mindspore/ccsrc/runtime/device/kernel_runtime.h
@@ -61,6 +61,8 @@ class KernelRuntime {
   virtual bool RunTask(const session::KernelGraph *graph);
   virtual bool GenTask(const session::KernelGraph *graph);
   bool LaunchKernel(const session::KernelGraph *graph);
+  bool LaunchTaskBasedOnSingleKernel(kernel::KernelModPtr kernel_mod_ptr, AddressPtrList kernel_inputs,
+                                     AddressPtrList kernel_outputs, AddressPtrList kernel_workspaces) const;
   virtual void AssignStaticMemoryInput(const session::KernelGraph *graph);
   virtual void AssignStaticMemoryValueNode(session::KernelGraph *graph);
   virtual void ClearGraphRuntimeResource(uint32_t graph_id);