Imported Upstream version 1.4.0upstream/1.4.0submit/tizen/20200423.054851

17 files changed, 2188 insertions, 0 deletions

diff --git a/runtime/onert/test/CMakeLists.txt b/runtime/onert/test/CMakeLists.txt
new file mode 100644
index 000000000..0abdd4880
--- /dev/null
+++ b/runtime/onert/test/CMakeLists.txt
@@ -0,0 +1,15 @@
+set(TEST_ONERT test_onert)
+
+file(GLOB_RECURSE TESTS "*.cc")
+
+add_executable(${TEST_ONERT} ${TESTS})
+
+target_include_directories(${TEST_ONERT} PRIVATE ${CMAKE_CURRENT_SOURCE_DIR}/../core/src)
+
+target_link_libraries(${TEST_ONERT} onert_core)
+target_link_libraries(${TEST_ONERT} gtest)
+target_link_libraries(${TEST_ONERT} gtest_main)
+target_link_libraries(${TEST_ONERT} ${LIB_PTHREAD} dl)
+add_test(${TEST_ONERT} ${TEST_ONERT})
+
+install(TARGETS ${TEST_ONERT} DESTINATION unittest)
diff --git a/runtime/onert/test/core/compiler/Scheduler.cc b/runtime/onert/test/core/compiler/Scheduler.cc
new file mode 100644
index 000000000..926b82d94
--- /dev/null
+++ b/runtime/onert/test/core/compiler/Scheduler.cc
@@ -0,0 +1,569 @@
+/*
+ * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
+ *
+ * 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 <compiler/HEScheduler.h>
+#include <exec/ExecTime.h>
+#include <backend/IShapeFixer.h>
+
+#include <ir/Shape.h>
+#include <ir/InternalType.h>
+#include <ir/TypeInfo.h>
+#include <ir/DataType.h>
+
+#include <ir/operation/Add.h>
+#include <ir/operation/Sub.h>
+#include <ir/operation/Mul.h>
+#include <ir/operation/FullyConnected.h>
+
+#include <gtest/gtest.h>
+
+namespace
+{
+using namespace onert;
+using namespace ir;
+using namespace backend;
+using namespace operation;
+using namespace exec;
+
+//
+// Mock backends classes
+//
+
+// Backend could be created without ShapeFixer.
+// But it is used by scheduler to detect which operations are supported by backend.
+struct MockShapeFixer : IShapeFixer
+{
+  void visit(const Add &) override {}
+  void visit(const Sub &) override {}
+  void visit(const Mul &) override {}
+  void visit(const FullyConnected &) override {}
+};
+
+struct MockConfigCPU : public IConfig
+{
+  std::string id() override { return "cpu"; }
+  bool initialize() override { return true; };
+  bool SupportPermutation() override { return false; }
+};
+
+struct MockBackendCPU : public Backend
+{
+  std::shared_ptr<IConfig> config() const override { return std::make_shared<MockConfigCPU>(); }
+  std::unique_ptr<BackendContext>
+  newContext(const Graph &, const std::shared_ptr<custom::IKernelBuilder> &, bool) const override
+  {
+    return std::unique_ptr<BackendContext>(new BackendContext{
+        this, nullptr, nullptr, nullptr, nullptr, std::make_shared<MockShapeFixer>()});
+  }
+};
+
+struct MockConfigGPU : public IConfig
+{
+  std::string id() override { return "gpu"; }
+  bool initialize() override { return true; };
+  bool SupportPermutation() override { return false; }
+};
+
+struct MockBackendGPU : public Backend
+{
+  std::shared_ptr<IConfig> config() const override { return std::make_shared<MockConfigGPU>(); }
+  std::unique_ptr<BackendContext>
+  newContext(const Graph &, const std::shared_ptr<custom::IKernelBuilder> &, bool) const override
+  {
+    return std::unique_ptr<BackendContext>(new BackendContext{
+        this, nullptr, nullptr, nullptr, nullptr, std::make_shared<MockShapeFixer>()});
+  }
+};
+
+struct MockConfigNPU : public IConfig
+{
+  std::string id() override { return "npu"; }
+  bool initialize() override { return true; };
+  bool SupportPermutation() override { return false; }
+};
+
+struct MockBackendNPU : public Backend
+{
+  std::shared_ptr<IConfig> config() const override { return std::make_shared<MockConfigNPU>(); }
+  std::unique_ptr<BackendContext>
+  newContext(const Graph &, const std::shared_ptr<custom::IKernelBuilder> &, bool) const override
+  {
+    return std::unique_ptr<BackendContext>(new BackendContext{
+        this, nullptr, nullptr, nullptr, nullptr, std::make_shared<MockShapeFixer>()});
+  }
+};
+
+//
+// Constants
+//
+
+const int OPERAND_ELEMS = 268203;
+const int OPERAND_SIZE = OPERAND_ELEMS * 4;
+const int OPERATION_SIZE = OPERAND_SIZE * 3;
+
+const std::string LINEAR("Linear");
+const std::string DATAFLOW("Dataflow");
+const std::string PARALLEL("Parallel");
+
+//
+// Helper functions
+//
+
+// Set executor through environment variable
+void setExecutor(const std::string &executor) { setenv("EXECUTOR", executor.c_str(), true); }
+
+// Set profiling mode through environment variable
+void setProfilingMode(const bool value) { setenv("PROFILING_MODE", value ? "1" : "0", true); }
+
+// Calculate operation size by addition sizes of all input and output operands
+uint32_t calcOpSize(const std::shared_ptr<Graph> &graph, const OperationIndex &op_idx)
+{
+  uint32_t size = 0;
+  const auto &op = graph->operations().at(op_idx);
+  for (const auto &ind : op.getInputs() + op.getOutputs())
+    size += graph->operands().at(ind).info().total_size();
+  return size;
+}
+
+// Set execution operation time. This method is needed since ExecutionTime has only
+// 'updateOperationExecTime' method.
+void setOperationExecTime(ExecTime &et, const Backend *backend, const std::string &operation,
+                          bool quant, uint32_t op_size, int64_t time)
+{
+  // You shouldn't set negative time with this method since nnfw JSON deserializer can't read it
+  assert(time > 0);
+  int64_t prev_time = et.getOperationExecTime(backend, operation, quant, op_size);
+  int64_t time_to_set = prev_time == ExecTime::NOT_FOUND ? time : 2 * time - prev_time;
+  et.updateOperationExecTime(backend, operation, quant, op_size, time_to_set);
+  assert(et.getOperationExecTime(backend, operation, quant, op_size) == time);
+}
+
+// Set same execution time for all given backends/operations
+void setOperationsExecutionTime(const std::vector<const Backend *> &backends,
+                                const std::vector<std::string> &op_names,
+                                const std::vector<uint32_t> &op_sizes, int64_t exec_time)
+{
+  assert(op_names.size() == op_sizes.size());
+  ExecTime et(backends);
+  for (int i = 0; i < op_names.size(); ++i)
+  {
+    for (auto &backend : backends)
+      setOperationExecTime(et, backend, op_names[i], false, op_sizes[i], exec_time);
+  }
+  et.uploadOperationsExecTime();
+}
+
+// Set permute time from one backend to another. This method is needed since ExecutionTime has only
+// 'updatePermuteTime' method.
+void setPermutationTime(ExecTime &et, const Backend *from_backend, const Backend *to_backend,
+                        bool quant, uint32_t op_size, int64_t time)
+{
+  // You shouldn't set negative time with this method since nnfw JSON deserializer can't read it
+  assert(time > 0);
+  int64_t prev_time = et.getPermuteTime(from_backend, to_backend, quant, op_size);
+  int64_t time_to_set = prev_time == ExecTime::NOT_FOUND ? time : 2 * time - prev_time;
+  et.updatePermuteTime(from_backend, to_backend, quant, op_size, time_to_set);
+  assert(et.getPermuteTime(from_backend, to_backend, quant, op_size) == time);
+}
+
+// Set same permutation time between all given backends
+void setPermutationsExecutionTime(const std::vector<const Backend *> &backends,
+                                  const int operand_size, const int64_t exec_time)
+{
+  ExecTime et(backends);
+  for (const auto &backend : backends)
+  {
+    for (auto &other_backend : backends)
+    {
+      if (backend == other_backend)
+        continue;
+      setPermutationTime(et, backend, other_backend, false, operand_size, exec_time);
+    }
+  }
+  et.uploadOperationsExecTime();
+}
+
+//
+// Functions for creating graphs
+//
+
+using OIS = OperandIndexSequence;
+
+template <typename NodeT, typename... Types>
+OperationIndex create(std::shared_ptr<Graph> graph, Types &&... args)
+{
+  typename NodeT::Param op_params{Activation::NONE};
+  auto op = std::make_unique<NodeT>(std::forward<Types>(args)..., op_params);
+  auto op_idx = graph->addOperation(std::move(op));
+  // For now in scheduler test all operations in tested graphs has same size (for simplicity)
+  assert(calcOpSize(graph, op_idx) == OPERATION_SIZE);
+  return op_idx;
+}
+
+// Create straight graph: Add->Sub->Mul
+std::shared_ptr<Graph> createStraightGraph()
+{
+  auto graph = std::make_shared<Graph>();
+  const TypeInfo float_op(DataType::FLOAT32);
+
+  // Create add node
+  auto add_lhs_idx = graph->addOperand(ir::Shape{OPERAND_ELEMS}, float_op);
+  auto add_rhs_idx = graph->addOperand(ir::Shape{OPERAND_ELEMS}, float_op);
+  auto add_out_idx = graph->addOperand(ir::Shape{OPERAND_ELEMS}, float_op);
+  create<Add>(graph, OIS{add_lhs_idx, add_rhs_idx}, OIS{add_out_idx});
+
+  // Create sub node
+  auto sub_const_idx = graph->addOperand(ir::Shape{OPERAND_ELEMS}, float_op);
+  auto sub_out_idx = graph->addOperand(ir::Shape{OPERAND_ELEMS}, float_op);
+  create<Sub>(graph, OIS{add_out_idx, sub_const_idx}, OIS{sub_out_idx});
+
+  // Create mul node
+  auto mul_const_idx = graph->addOperand(ir::Shape{OPERAND_ELEMS}, float_op);
+  auto mul_out_idx = graph->addOperand(ir::Shape{OPERAND_ELEMS}, float_op);
+  create<Mul>(graph, OIS{sub_out_idx, mul_const_idx}, OIS{mul_out_idx});
+
+  graph->finishBuilding();
+  return graph;
+}
+
+/* Create branched graph:
+ *       [Add]
+ *      //   \\
+ *   [Mul1]  [FC2]
+ *     ||     ||
+ *   [Mul2]  [FC2]
+ *      \\   //
+ *       [Sub]
+ */
+std::shared_ptr<Graph> createBranchedGraph()
+{
+  auto graph = std::make_shared<Graph>();
+  const TypeInfo float_op(DataType::FLOAT32);
+
+  // Create add node
+  auto add_lhs_idx = graph->addOperand(ir::Shape{OPERAND_ELEMS}, float_op);
+  auto add_rhs_idx = graph->addOperand(ir::Shape{OPERAND_ELEMS}, float_op);
+  auto add_out_idx = graph->addOperand(ir::Shape{OPERAND_ELEMS}, float_op);
+  create<Add>(graph, OIS{add_lhs_idx, add_rhs_idx}, OIS{add_out_idx});
+
+  // Create mul1 node
+  auto mul1_const_idx = graph->addOperand(ir::Shape{OPERAND_ELEMS}, float_op);
+  auto mul1_out_idx = graph->addOperand(ir::Shape{OPERAND_ELEMS}, float_op);
+  create<Mul>(graph, OIS{add_out_idx, mul1_const_idx}, OIS{mul1_out_idx});
+
+  // Create mul2 node
+  auto mul2_const_idx = graph->addOperand(ir::Shape{OPERAND_ELEMS}, float_op);
+  auto mul2_out_idx = graph->addOperand(ir::Shape{OPERAND_ELEMS}, float_op);
+  create<Mul>(graph, OIS{mul1_out_idx, mul2_const_idx}, OIS{mul2_out_idx});
+
+  // Create fc1 node
+  auto fc1_const_idx = graph->addOperand(ir::Shape{OPERAND_ELEMS}, float_op);
+  auto fc1_out_idx = graph->addOperand(ir::Shape{OPERAND_ELEMS}, float_op);
+  create<FullyConnected>(graph, OIS{add_out_idx, fc1_const_idx}, OIS{fc1_out_idx});
+
+  // Create fc2 node
+  auto fc2_const_idx = graph->addOperand(ir::Shape{OPERAND_ELEMS}, float_op);
+  auto fc2_out_idx = graph->addOperand(ir::Shape{OPERAND_ELEMS}, float_op);
+  create<FullyConnected>(graph, OIS{fc1_out_idx, fc2_const_idx}, OIS{fc2_out_idx});
+
+  // Create add2 node
+  auto sub_out_idx = graph->addOperand(ir::Shape{OPERAND_ELEMS}, float_op);
+  create<Sub>(graph, OIS{mul2_out_idx, fc2_out_idx}, OIS{sub_out_idx});
+
+  graph->finishBuilding();
+  return graph;
+}
+
+//
+// Tests setup/teardown
+//
+
+// SetUp/TearDown methods runs before/after each test and performs actions common for each test
+class SchedulerTest : public ::testing::Test
+{
+protected:
+  void SetUp() override
+  {
+    // Initialize mock backends
+    _cpu_backend = new MockBackendCPU();
+    _gpu_backend = new MockBackendGPU();
+    _npu_backend = new MockBackendNPU();
+    _mock_backends = {_cpu_backend, _gpu_backend, _npu_backend};
+
+    // Remove previous profile data if it exists
+    if (!remove("exec_time.json"))
+    {
+      // DO NOTHING (no profile data)
+    }
+
+    // Remember original value of 'EXECUTOR' environment variable
+    char *executor = std::getenv("EXECUTOR");
+    _original_executor = executor == nullptr ? "" : executor;
+
+    // Remember original value of 'PROFILING_MODE' environment variable
+    char *profiling_mode = std::getenv("PROFILING_MODE");
+    _original_profiling_mode = profiling_mode == nullptr ? "" : profiling_mode;
+  }
+
+  void TearDown() override
+  {
+    delete _cpu_backend;
+    delete _gpu_backend;
+    delete _npu_backend;
+    EXPECT_EQ(remove("exec_time.json"), 0);
+    setenv("EXECUTOR", _original_executor.c_str(), true);
+    setenv("PROFILING_MODE", _original_profiling_mode.c_str(), true);
+  }
+
+  backend::BackendContexts buildBackendContexts(const Graph &graph)
+  {
+    backend::BackendContexts contexts;
+    for (auto backend : _mock_backends)
+    {
+      contexts.emplace(backend, backend->newContext(graph, nullptr, false));
+    }
+    return contexts;
+  }
+
+  const MockBackendCPU *_cpu_backend{nullptr};
+  const MockBackendGPU *_gpu_backend{nullptr};
+  const MockBackendNPU *_npu_backend{nullptr};
+  std::vector<const Backend *> _mock_backends;
+
+  std::string _original_executor;
+  std::string _original_profiling_mode;
+};
+
+class SchedulerTestWithExecutorParam : public SchedulerTest,
+                                       public testing::WithParamInterface<std::string>
+{
+};
+
+//
+// HEScheduler tests
+//
+
+// Test scheduler behavior for straight graph with known execution time of all nodes and permutes.
+TEST_P(SchedulerTestWithExecutorParam, straight_graph_known_exec_time)
+{
+  setExecutor(GetParam());
+
+  // Prepare graph
+  auto graph(createStraightGraph());
+  OperationIndex add_op_idx(0), sub_op_idx(1), mul_op_idx(2);
+
+  // Set default execution and transfer time
+  setPermutationsExecutionTime(_mock_backends, OPERAND_SIZE, 1);
+  setOperationsExecutionTime(_mock_backends, {"Add", "Sub", "Mul"},
+                             {OPERATION_SIZE, OPERATION_SIZE, OPERATION_SIZE}, 1e4);
+
+  // Test 1
+  // Expected behaviour: scheduler assigns different backend to each node
+  {
+    // For each backend reduce execution time of one node
+    ExecTime et(_mock_backends);
+    setOperationExecTime(et, _cpu_backend, "Add", false, OPERATION_SIZE, 1);
+    setOperationExecTime(et, _gpu_backend, "Sub", false, OPERATION_SIZE, 1);
+    setOperationExecTime(et, _npu_backend, "Mul", false, OPERATION_SIZE, 1);
+    et.uploadOperationsExecTime();
+
+    // Test scheduler
+    auto backend_contexts = buildBackendContexts(*graph);
+    auto scheduler = compiler::HEScheduler(backend_contexts,
+                                           compiler::fetchCompilerOptionsFromGlobalConfig(*graph));
+    const auto br = scheduler.schedule(*graph);
+    ASSERT_EQ(br->getBackend(add_op_idx)->config()->id(), "cpu");
+    ASSERT_EQ(br->getBackend(sub_op_idx)->config()->id(), "gpu");
+    ASSERT_EQ(br->getBackend(mul_op_idx)->config()->id(), "npu");
+  }
+
+  // Test 2
+  // Expected behaviour: scheduler assigns single backend to all nodes because of big transfer time
+  {
+    // Increase transfer time
+    setPermutationsExecutionTime(_mock_backends, OPERAND_SIZE, 1e5);
+
+    // Test scheduler
+    auto backend_contexts = buildBackendContexts(*graph);
+    auto scheduler = compiler::HEScheduler(backend_contexts,
+                                           compiler::fetchCompilerOptionsFromGlobalConfig(*graph));
+    const auto br = scheduler.schedule(*graph);
+    ASSERT_EQ(br->getBackend(add_op_idx)->config()->id(), "cpu");
+    ASSERT_EQ(br->getBackend(sub_op_idx)->config()->id(), "cpu");
+    ASSERT_EQ(br->getBackend(mul_op_idx)->config()->id(), "cpu");
+  }
+}
+
+// Test scheduler behavior for branched graph with known execution time of all nodes and permutes
+TEST_P(SchedulerTestWithExecutorParam, branched_graph_known_exec_time)
+{
+  const int64_t NPU_ET = 5000;
+  setExecutor(GetParam());
+
+  // Prepare graph
+  auto graph(createBranchedGraph());
+  OperationIndex add_op_idx(0), mul1_op_idx(1), mul2_op_idx(2), fc1_op_idx(3), fc2_op_idx(4),
+      sub_op_idx(5);
+
+  // Set default execution and transfer time
+  setPermutationsExecutionTime(_mock_backends, OPERAND_SIZE, 1000);
+  setOperationsExecutionTime(_mock_backends, {"Add", "Sub", "Mul", "FullyConnected"},
+                             {OPERATION_SIZE, OPERATION_SIZE, OPERATION_SIZE, OPERATION_SIZE}, 1e4);
+
+  // Test 1
+  // Expected behaviour: for dataflow and linear executors scheduler assigns fastest backend to all
+  // nodes, in case of parallel executor scheduler assigns different backends to branches.
+  {
+    // Reduce execution time
+    ExecTime et(_mock_backends);
+    setOperationExecTime(et, _npu_backend, "Add", false, OPERATION_SIZE, NPU_ET);
+    setOperationExecTime(et, _npu_backend, "Mul", false, OPERATION_SIZE, NPU_ET);
+    setOperationExecTime(et, _npu_backend, "Sub", false, OPERATION_SIZE, NPU_ET);
+    setOperationExecTime(et, _npu_backend, "FullyConnected", false, OPERATION_SIZE, NPU_ET);
+    setOperationExecTime(et, _gpu_backend, "Mul", false, OPERATION_SIZE, NPU_ET + 1000);
+    setOperationExecTime(et, _gpu_backend, "FullyConnected", false, OPERATION_SIZE, NPU_ET + 1000);
+    et.uploadOperationsExecTime();
+
+    // Test scheduler
+    auto backend_contexts = buildBackendContexts(*graph);
+    auto scheduler = compiler::HEScheduler(backend_contexts,
+                                           compiler::fetchCompilerOptionsFromGlobalConfig(*graph));
+    const auto br = scheduler.schedule(*graph);
+
+    std::string branch1_expected_backend("npu"), branch2_expected_backend("npu");
+    if (GetParam() == PARALLEL)
+    {
+      branch1_expected_backend =
+          br->getBackend(mul1_op_idx)->config()->id() == "npu" ? "npu" : "gpu";
+      branch2_expected_backend = branch1_expected_backend == "npu" ? "gpu" : "npu";
+    }
+
+    ASSERT_EQ(br->getBackend(add_op_idx)->config()->id(), "npu");
+    ASSERT_EQ(br->getBackend(mul1_op_idx)->config()->id(), branch1_expected_backend);
+    ASSERT_EQ(br->getBackend(mul2_op_idx)->config()->id(), branch1_expected_backend);
+    ASSERT_EQ(br->getBackend(fc1_op_idx)->config()->id(), branch2_expected_backend);
+    ASSERT_EQ(br->getBackend(fc2_op_idx)->config()->id(), branch2_expected_backend);
+    ASSERT_EQ(br->getBackend(sub_op_idx)->config()->id(), "npu");
+  }
+
+  // Test 2
+  // Expected behaviour: scheduler assigns single backend to all nodes
+  {
+    // Increase execution time for GPU backend
+    ExecTime et(_mock_backends);
+    /* for parallel executor: set a time, that is larger than sum_of_other_branches_nodes_cnt *
+     * npu_exec_time so that npu is prefered: the ith branch will wait for npu until it finishes the
+     * [0;i-1] branches nodes in DFS order. In each branch it goes deep intul doesn't encounter
+     * branching or scheduler assigns another backend to a node*/
+    setOperationExecTime(et, _gpu_backend, "Mul", false, OPERATION_SIZE, NPU_ET * 3 + 1);
+    setOperationExecTime(et, _gpu_backend, "FullyConnected", false, OPERATION_SIZE, NPU_ET * 3 + 1);
+    et.uploadOperationsExecTime();
+
+    // Test scheduler
+    auto backend_contexts = buildBackendContexts(*graph);
+    auto scheduler = compiler::HEScheduler(backend_contexts,
+                                           compiler::fetchCompilerOptionsFromGlobalConfig(*graph));
+    const auto br = scheduler.schedule(*graph);
+    ASSERT_EQ(br->getBackend(add_op_idx)->config()->id(), "npu");
+    ASSERT_EQ(br->getBackend(mul1_op_idx)->config()->id(), "npu");
+    ASSERT_EQ(br->getBackend(mul2_op_idx)->config()->id(), "npu");
+    ASSERT_EQ(br->getBackend(fc1_op_idx)->config()->id(), "npu");
+    ASSERT_EQ(br->getBackend(fc2_op_idx)->config()->id(), "npu");
+    ASSERT_EQ(br->getBackend(sub_op_idx)->config()->id(), "npu");
+  }
+}
+
+// SchedulerTestWithExecutorParam tests are parameterized with executor name and runs three times -
+// one time for each executor
+INSTANTIATE_TEST_CASE_P(AllExecutors, SchedulerTestWithExecutorParam,
+                        testing::Values(LINEAR, DATAFLOW, PARALLEL));
+
+// Test scheduler behavior for branched graph and enabled profiling mode
+TEST_F(SchedulerTest, branched_graph_profiling_mode)
+{
+  const int ET = 1e5;
+
+  // Turn on profiling mode
+  setProfilingMode(true);
+  setExecutor(DATAFLOW);
+
+  // Prepare graph
+  auto graph(createBranchedGraph());
+  OperationIndex add_op_idx(0), mul1_op_idx(1), mul2_op_idx(2), fc1_op_idx(3), fc2_op_idx(4),
+      sub_op_idx(5);
+
+  // Test 1
+  // Expected behaviour: scheduler assigns backends to nodes with unknown execution time
+  {
+    // Set execution time for all backends/nodes except for cpu/Sub, npu/Mul, gpu/FC
+    ExecTime et(_mock_backends);
+    setOperationExecTime(et, _cpu_backend, "Add", false, OPERATION_SIZE, ET);
+    setOperationExecTime(et, _cpu_backend, "Mul", false, OPERATION_SIZE, ET + 1);
+    setOperationExecTime(et, _cpu_backend, "FullyConnected", false, OPERATION_SIZE, ET);
+    setOperationExecTime(et, _npu_backend, "Add", false, OPERATION_SIZE, ET);
+    setOperationExecTime(et, _npu_backend, "FullyConnected", false, OPERATION_SIZE, ET);
+    setOperationExecTime(et, _npu_backend, "Sub", false, OPERATION_SIZE, ET);
+    setOperationExecTime(et, _gpu_backend, "Add", false, OPERATION_SIZE, ET);
+    setOperationExecTime(et, _gpu_backend, "Mul", false, OPERATION_SIZE, ET + 1);
+    setOperationExecTime(et, _gpu_backend, "Sub", false, OPERATION_SIZE, ET);
+    et.uploadOperationsExecTime();
+
+    // Test scheduler
+    auto backend_contexts = buildBackendContexts(*graph);
+    auto scheduler = compiler::HEScheduler(backend_contexts,
+                                           compiler::fetchCompilerOptionsFromGlobalConfig(*graph));
+    const auto br = scheduler.schedule(*graph);
+    ASSERT_EQ(br->getBackend(mul1_op_idx)->config()->id(), "npu");
+    ASSERT_EQ(br->getBackend(mul2_op_idx)->config()->id(), "npu");
+    ASSERT_EQ(br->getBackend(fc1_op_idx)->config()->id(), "gpu");
+    ASSERT_EQ(br->getBackend(fc2_op_idx)->config()->id(), "gpu");
+    ASSERT_EQ(br->getBackend(sub_op_idx)->config()->id(), "cpu");
+  }
+
+  // Test 2
+  // Expected behaviour: scheduler shuffling backends, so different backends are assigned to
+  // neighbor nodes
+  {
+    // Set execution time for rest backends/nodes (cpu/Sub, npu/Mul, gpu/FC)
+    ExecTime et(_mock_backends);
+    setOperationExecTime(et, _cpu_backend, "Sub", false, OPERATION_SIZE, ET);
+    setOperationExecTime(et, _npu_backend, "Mul", false, OPERATION_SIZE, ET + 1);
+    setOperationExecTime(et, _gpu_backend, "FullyConnected", false, OPERATION_SIZE, ET);
+    et.uploadOperationsExecTime();
+
+    // Test scheduler
+    auto backend_contexts = buildBackendContexts(*graph);
+    auto scheduler = compiler::HEScheduler(backend_contexts,
+                                           compiler::fetchCompilerOptionsFromGlobalConfig(*graph));
+    const auto br = scheduler.schedule(*graph);
+    ASSERT_NE(br->getBackend(add_op_idx)->config()->id(),
+              br->getBackend(mul1_op_idx)->config()->id());
+    ASSERT_NE(br->getBackend(add_op_idx)->config()->id(),
+              br->getBackend(fc1_op_idx)->config()->id());
+    ASSERT_NE(br->getBackend(mul1_op_idx)->config()->id(),
+              br->getBackend(mul2_op_idx)->config()->id());
+    ASSERT_NE(br->getBackend(fc1_op_idx)->config()->id(),
+              br->getBackend(fc2_op_idx)->config()->id());
+    ASSERT_NE(br->getBackend(mul2_op_idx)->config()->id(),
+              br->getBackend(sub_op_idx)->config()->id());
+    ASSERT_NE(br->getBackend(fc2_op_idx)->config()->id(),
+              br->getBackend(sub_op_idx)->config()->id());
+  }
+}
+
+// TODO: Add tests with unknown execution and permutation time
+
+} // unnamed namespace
diff --git a/runtime/onert/test/core/exec/ExecInstance.cc b/runtime/onert/test/core/exec/ExecInstance.cc
new file mode 100644
index 000000000..7242486a0
--- /dev/null
+++ b/runtime/onert/test/core/exec/ExecInstance.cc
@@ -0,0 +1,306 @@
+/*
+ * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
+ *
+ * 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 <gtest/gtest.h>
+#include <thread>
+
+#include "ir/Graph.h"
+#include "compiler/Compiler.h"
+#include "exec/Execution.h"
+#include "ir/operation/Add.h"
+
+namespace
+{
+
+using namespace onert::ir;
+
+class CompiledMockUpModel
+{
+public:
+  CompiledMockUpModel()
+  {
+    // Model: two elementwise add operation
+    // model input: lhs, rhs1
+    // model output: second add result (result2)
+    // constant: rhs2
+    // result1 <= (lhs + rhs)
+    // result2 <= (result1 + rhs2)
+    // lhs, rhs1, rh2, result1, result2 shape: {1, 2, 2, 1}
+    // activation: none (constant)
+    graph = std::make_shared<Graph>();
+    // 1st add operands (result1 <= lhs + rhs1)
+    Shape shape{1, 2, 2, 1};
+    TypeInfo type{DataType::FLOAT32};
+    static float rhs2_data[4] = {3, 1, -1, 5};
+    auto operand_lhs = graph->addOperand(shape, type);
+    auto operand_rhs1 = graph->addOperand(shape, type);
+    auto operand_result1 = graph->addOperand(shape, type);
+    auto operand_rhs2 = graph->addOperand(shape, type);
+    auto operand_result2 = graph->addOperand(shape, type);
+    graph->operands()
+        .at(operand_rhs2)
+        .data(std::make_unique<CachedData>(reinterpret_cast<const uint8_t *>(&rhs2_data), 16));
+    // 2nd add operations (result2 <= result1 + rhs2)
+    operation::Add::Param param1;
+    param1.activation = Activation::NONE;
+    auto input_set1 = OperandIndexSequence{operand_lhs, operand_rhs1};
+    auto output_set1 = OperandIndexSequence{operand_result1};
+    graph->addOperation(std::make_unique<operation::Add>(input_set1, output_set1, param1));
+    operation::Add::Param param2;
+    param2.activation = Activation::NONE;
+    auto input_set2 = OperandIndexSequence{operand_result1, operand_rhs2};
+    auto output_set2 = OperandIndexSequence{operand_result2};
+    graph->addOperation(std::make_unique<operation::Add>(input_set2, output_set2, param2));
+    // Identify model inputs and outputs
+    graph->addInput(operand_lhs);
+    graph->addInput(operand_rhs1);
+    graph->addOutput(operand_result2);
+    graph->finishBuilding();
+
+    // Compile
+    auto compiler = new onert::compiler::Compiler{graph};
+    compiler->compile();
+    compiler->release(executor);
+    delete compiler;
+  }
+
+public:
+  std::shared_ptr<Graph> graph;
+  std::shared_ptr<onert::exec::IExecutor> executor;
+};
+
+TEST(ExecInstance, simple)
+{
+  auto mockup = CompiledMockUpModel();
+  auto graph = mockup.graph;
+  auto executor = mockup.executor;
+
+  auto input1 = IOIndex{0};
+  auto input2 = IOIndex{1};
+  auto output = IOIndex{0};
+
+  const float input1_buffer[4] = {1, 0, -1, -2};
+  const float input2_buffer[4] = {1, -3, 2, -4};
+  float output_buffer[4] = {};
+  const float output_expected[4] = {5, -2, 0, -1};
+
+  auto execution = new onert::exec::Execution(executor);
+
+  execution->setInput(input1, reinterpret_cast<const void *>(input1_buffer), 16);
+  execution->setInput(input2, reinterpret_cast<const void *>(input2_buffer), 16);
+  execution->setOutput(output, reinterpret_cast<void *>(output_buffer), 16);
+  execution->execute();
+
+  for (auto i = 0; i < 4; i++)
+  {
+    EXPECT_EQ(output_buffer[i], output_expected[i]);
+  }
+
+  delete execution;
+}
+
+TEST(ExecInstance, twoCompile)
+{
+  auto mockup = CompiledMockUpModel();
+  auto graph = mockup.graph;
+  auto executor1 = mockup.executor;
+  auto execution1 = new onert::exec::Execution(executor1);
+
+  auto input1 = IOIndex{0};
+  auto input2 = IOIndex{1};
+  auto output = IOIndex{0};
+
+  const float exe1_input1_buffer[4] = {1, 0, -1, -2};
+  const float exe1_input2_buffer[4] = {1, -3, 2, -4};
+  float exe1_output_buffer[4] = {};
+  const float exe1_output_expected[4] = {5, -2, 0, -1};
+
+  execution1->setInput(input1, reinterpret_cast<const void *>(exe1_input1_buffer), 16);
+  execution1->setInput(input2, reinterpret_cast<const void *>(exe1_input2_buffer), 16);
+  execution1->setOutput(output, reinterpret_cast<void *>(exe1_output_buffer), 16);
+
+  // Make new executor: compile again
+  auto compiler = new onert::compiler::Compiler{graph};
+  compiler->compile();
+  std::shared_ptr<onert::exec::IExecutor> executor2;
+  compiler->release(executor2);
+  auto execution2 = new onert::exec::Execution(executor2);
+
+  const float exe2_input1_buffer[4] = {2, 1, -2, 0};
+  const float exe2_input2_buffer[4] = {-3, 3, 1, 2};
+  float exe2_output_buffer[4] = {};
+  const float exe2_output_expected[4] = {2, 5, -2, 7};
+
+  execution2->setInput(input1, reinterpret_cast<const void *>(exe2_input1_buffer), 16);
+  execution2->setInput(input2, reinterpret_cast<const void *>(exe2_input2_buffer), 16);
+  execution2->setOutput(output, reinterpret_cast<void *>(exe2_output_buffer), 16);
+
+  execution1->execute();
+  execution2->execute();
+
+  for (auto i = 0; i < 4; i++)
+  {
+    EXPECT_EQ(exe1_output_buffer[i], exe1_output_expected[i]);
+    EXPECT_EQ(exe2_output_buffer[i], exe2_output_expected[i]);
+  }
+
+  delete compiler;
+  delete execution1;
+  delete execution2;
+}
+
+// Support two initialized execution instance then ordered execution
+TEST(ExecInstance, twoExecution)
+{
+  auto mockup = CompiledMockUpModel();
+  auto executor = mockup.executor;
+  auto input1 = IOIndex{0};
+  auto input2 = IOIndex{1};
+  auto output1 = IOIndex{0};
+
+  const float exe1_input1_buffer[4] = {1, 0, -1, -2};
+  const float exe1_input2_buffer[4] = {1, -3, 2, -4};
+  float exe1_output_buffer[4] = {};
+  const float exe1_output_expected[4] = {5, -2, 0, -1};
+  const float exe2_output_expected[4] = {2, 5, -2, 7};
+
+  auto execution1 = new onert::exec::Execution(executor);
+  execution1->setInput(input1, reinterpret_cast<const void *>(exe1_input1_buffer), 16);
+  execution1->setInput(input2, reinterpret_cast<const void *>(exe1_input2_buffer), 16);
+  execution1->setOutput(output1, reinterpret_cast<void *>(exe1_output_buffer), 16);
+
+  const float exe2_input1_buffer[4] = {2, 1, -2, 0};
+  const float exe2_input2_buffer[4] = {-3, 3, 1, 2};
+  float exe2_output_buffer[4] = {};
+
+  // Make new execution
+  auto execution2 = new onert::exec::Execution(executor);
+  execution2->setInput(input1, reinterpret_cast<const void *>(exe2_input1_buffer), 16);
+  execution2->setInput(input2, reinterpret_cast<const void *>(exe2_input2_buffer), 16);
+  execution2->setOutput(output1, reinterpret_cast<void *>(exe2_output_buffer), 16);
+
+  execution1->execute();
+  execution2->execute();
+
+  for (auto i = 0; i < 4; i++)
+  {
+    EXPECT_EQ(exe1_output_buffer[i], exe1_output_expected[i]);
+    EXPECT_EQ(exe2_output_buffer[i], exe2_output_expected[i]);
+  }
+
+  delete execution1;
+  delete execution2;
+}
+
+class Inference
+{
+public:
+  Inference(const float (&input1)[4], const float (&input2)[4], float (&output)[4],
+            std::shared_ptr<onert::exec::IExecutor> &executor)
+      : _input1{input1}, _input2{input2}, _output{output}, _executor{executor}
+  {
+    // DO NOTHING
+  }
+
+  void inference(void)
+  {
+    auto input1 = IOIndex{0};
+    auto input2 = IOIndex{1};
+    auto output1 = IOIndex{0};
+
+    auto execution = new onert::exec::Execution(_executor);
+    execution->setInput(input1, reinterpret_cast<const void *>(_input1), 16);
+    execution->setInput(input2, reinterpret_cast<const void *>(_input2), 16);
+    execution->setOutput(output1, reinterpret_cast<void *>(_output), 16);
+
+    execution->execute();
+
+    delete execution;
+  }
+
+private:
+  const float (&_input1)[4];
+  const float (&_input2)[4];
+  float (&_output)[4];
+  std::shared_ptr<onert::exec::IExecutor> &_executor;
+};
+
+// Support multi-thread execution
+TEST(ExecInstance, twoThreads)
+{
+  auto mockup = CompiledMockUpModel();
+  auto executor = mockup.executor;
+
+  const float exe1_input1_buffer[4] = {1, 0, -1, -2};
+  const float exe1_input2_buffer[4] = {1, -3, 2, -4};
+  float exe1_output_buffer[4] = {};
+  const float exe1_output_expected[4] = {5, -2, 0, -1};
+
+  Inference execution1{exe1_input1_buffer, exe1_input2_buffer, exe1_output_buffer, executor};
+
+  const float exe2_input1_buffer[4] = {2, 1, -2, 0};
+  const float exe2_input2_buffer[4] = {-3, 3, 1, 2};
+  float exe2_output_buffer[4] = {};
+  const float exe2_output_expected[4] = {2, 5, -2, 7};
+
+  Inference execution2{exe2_input1_buffer, exe2_input2_buffer, exe2_output_buffer, executor};
+
+  std::thread t1{&Inference::inference, &execution1};
+  std::thread t2{&Inference::inference, &execution2};
+
+  t1.join();
+  t2.join();
+
+  for (auto i = 0; i < 4; i++)
+  {
+    EXPECT_EQ(exe1_output_buffer[i], exe1_output_expected[i]);
+    EXPECT_EQ(exe2_output_buffer[i], exe2_output_expected[i]);
+  }
+}
+
+// Support asynchronous execution
+TEST(ExecInstance, async)
+{
+  auto mockup = CompiledMockUpModel();
+  auto graph = mockup.graph;
+  auto executor = mockup.executor;
+
+  auto input1 = IOIndex{0};
+  auto input2 = IOIndex{1};
+  auto output = IOIndex{0};
+
+  const float input1_buffer[4] = {1, 0, -1, -2};
+  const float input2_buffer[4] = {1, -3, 2, -4};
+  float output_buffer[4] = {};
+  const float output_expected[4] = {5, -2, 0, -1};
+
+  auto execution = new onert::exec::Execution(executor);
+
+  execution->setInput(input1, reinterpret_cast<const void *>(input1_buffer), 16);
+  execution->setInput(input2, reinterpret_cast<const void *>(input2_buffer), 16);
+  execution->setOutput(output, reinterpret_cast<void *>(output_buffer), 16);
+  execution->startExecute();
+  execution->waitFinish();
+
+  for (auto i = 0; i < 4; i++)
+  {
+    EXPECT_EQ(output_buffer[i], output_expected[i]);
+  }
+
+  delete execution;
+}
+
+} // namespace
diff --git a/runtime/onert/test/core/exec/ExecTime.test.cc b/runtime/onert/test/core/exec/ExecTime.test.cc
new file mode 100644
index 000000000..ab8b79935
--- /dev/null
+++ b/runtime/onert/test/core/exec/ExecTime.test.cc
@@ -0,0 +1,99 @@
+/*
+ * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
+ *
+ * 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 "exec/ExecTime.h"
+#include "backend/IConfig.h"
+#include "backend/Backend.h"
+#include <gtest/gtest.h>
+#include <string>
+
+namespace
+{
+using namespace onert;
+using namespace exec;
+using namespace backend;
+
+struct MockConfig : public IConfig
+{
+  std::string id() override { return "b1"; }
+  bool initialize() override { return true; };
+  bool SupportPermutation() override { return false; }
+};
+
+struct MockBackend : public ::onert::backend::Backend
+{
+  std::shared_ptr<onert::backend::IConfig> config() const override
+  {
+    return std::make_shared<MockConfig>();
+  }
+  std::unique_ptr<BackendContext> newContext(const ir::Graph &,
+                                             const std::shared_ptr<custom::IKernelBuilder> &kb,
+                                             bool) const override
+  {
+    return nullptr;
+  }
+};
+
+TEST(ExecTime, roundtrip_ok)
+{
+  const auto *b = new MockBackend();
+  std::vector<const Backend *> bs = {b};
+  {
+    ExecTime et(bs);
+    et.updateOperationExecTime(b, "op1", true, 100, 100);
+    et.updateOperationExecTime(b, "op1", true, 200, 200);
+    et.updateOperationExecTime(b, "op1", false, 100, 888);
+    et.uploadOperationsExecTime();
+  }
+  {
+    ExecTime et(bs);
+    auto time = et.getOperationExecTime(b, "op1", true, 100);
+    ASSERT_EQ(time, 100);
+    // Check interpolation
+    time = et.getOperationExecTime(b, "op1", true, 150);
+    ASSERT_EQ(time, 150);
+    time = et.getOperationExecTime(b, "op1", false, 100);
+    ASSERT_EQ(time, 888);
+    et.uploadOperationsExecTime();
+  }
+  // clean up
+  EXPECT_EQ(remove("exec_time.json"), 0);
+}
+
+TEST(ExecTime, structure)
+{
+
+  const auto *b = new MockBackend();
+  std::vector<const Backend *> bs = {b};
+  {
+    ExecTime et(bs);
+    et.updateOperationExecTime(b, "op1", true, 100, 100);
+    et.updateOperationExecTime(b, "op1", true, 200, 200);
+    et.uploadOperationsExecTime();
+  }
+  {
+    ExecTime et(bs);
+    auto time = et.getOperationExecTime(b, "op1", true, 100);
+    ASSERT_EQ(time, 100);
+    // Check interpolation
+    time = et.getOperationExecTime(b, "op1", true, 200);
+    ASSERT_EQ(time, 200);
+    et.uploadOperationsExecTime();
+  }
+  // clean up
+  EXPECT_EQ(remove("exec_time.json"), 0);
+}
+} // unnamed namespace
diff --git a/runtime/onert/test/core/interp/ExecManager.cc b/runtime/onert/test/core/interp/ExecManager.cc
new file mode 100644
index 000000000..2b56357c2
--- /dev/null
+++ b/runtime/onert/test/core/interp/ExecManager.cc
@@ -0,0 +1,333 @@
+/*
+ * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
+ *
+ * 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 <gtest/gtest.h>
+
+#include <memory>
+
+#include "ir/Graph.h"
+#include "interp/InterpExecutor.h"
+#include "exec/Execution.h"
+#include "ir/operation/Add.h"
+
+namespace
+{
+
+using namespace onert::ir;
+using InterpExecutor = onert::interp::InterpExecutor;
+using Execution = onert::exec::Execution;
+
+class InterpExecutorTest : public ::testing::Test
+{
+protected:
+  virtual void SetUp() {}
+  void CreateSimpleModel()
+  {
+    // Model: one elementwise add operation
+    // model input: lhs, rhs
+    // model output: add result
+    // lhs, rhs, result shape: {1, 2, 2, 1}
+    // activation: none (constant)
+    _graph = std::make_unique<Graph>();
+
+    // Add operands
+
+    Shape shape{1, 2, 2, 1};
+    TypeInfo type{DataType::INT32};
+    Shape shape_scalar(0);
+    TypeInfo type_scalar{DataType::INT32};
+
+    auto operand_lhs = _graph->addOperand(shape, type);
+    auto operand_rhs = _graph->addOperand(shape, type);
+    auto operand_result = _graph->addOperand(shape, type);
+
+    // Add operations
+
+    operation::Add::Param param;
+    param.activation = Activation::NONE;
+    auto input_set = OperandIndexSequence{operand_lhs, operand_rhs};
+    auto output_set = OperandIndexSequence{operand_result};
+    _graph->addOperation(std::make_unique<operation::Add>(input_set, output_set, param));
+
+    // Identify model inputs and outputs
+
+    _graph->getInputs().append(operand_lhs);
+    _graph->getInputs().append(operand_rhs);
+    _graph->getOutputs().append(operand_result);
+
+    _graph->finishBuilding();
+
+    _executor = std::make_unique<InterpExecutor>(*_graph);
+  }
+
+  void CreateTwoStepModel()
+  {
+    // Model: two elementwise add operation
+    // model input: lhs, rhs1
+    // model output: second add result (result2)
+    // constant: rhs2
+    // result1 <= (lhs + rhs)
+    // result2 <= (result1 + rhs2)
+    // lhs, rhs1, rh2, result1, result2 shape: {1, 2, 2, 1}
+    // activation: none (constant)
+    _graph = std::make_unique<Graph>();
+
+    // 1st add operands (result1 <= lhs + rhs1)
+
+    Shape shape{1, 2, 2, 1};
+    TypeInfo type{DataType::INT32};
+    Shape shape_scalar(0);
+    TypeInfo type_scalar{DataType::INT32};
+
+    static int32_t rhs2_data[4] = {3, 1, -1, 5};
+
+    auto operand_lhs = _graph->addOperand(shape, type);
+    auto operand_rhs1 = _graph->addOperand(shape, type);
+    auto operand_result1 = _graph->addOperand(shape, type);
+    auto operand_rhs2 = _graph->addOperand(shape, type);
+    auto operand_result2 = _graph->addOperand(shape, type);
+    _graph->operands()
+        .at(operand_rhs2)
+        .data(std::make_unique<CachedData>(reinterpret_cast<const uint8_t *>(&rhs2_data), 16));
+
+    // 2nd add operations (result2 <= result1 + rhs2)
+
+    operation::Add::Param param1;
+    param1.activation = Activation::NONE;
+    auto input_set1 = OperandIndexSequence{operand_lhs, operand_rhs1};
+    auto output_set1 = OperandIndexSequence{operand_result1};
+    _graph->addOperation(std::make_unique<operation::Add>(input_set1, output_set1, param1));
+
+    operation::Add::Param param2;
+    param2.activation = Activation::NONE;
+    auto input_set2 = OperandIndexSequence{operand_result1, operand_rhs2};
+    auto output_set2 = OperandIndexSequence{operand_result2};
+    _graph->addOperation(std::make_unique<operation::Add>(input_set2, output_set2, param2));
+
+    // Identify model inputs and outputs
+
+    _graph->getInputs().append(operand_lhs);
+    _graph->getInputs().append(operand_rhs1);
+    _graph->getOutputs().append(operand_result2);
+
+    _graph->finishBuilding();
+
+    _executor = std::make_unique<InterpExecutor>(*_graph);
+  }
+
+  void CreateUnspecifiedDimensionsModel()
+  {
+    // Model: one elementwise add operation
+    // model input: lhs, rhs
+    // model output: add result
+    // lhs, rhs, result shape: {1, unknown, 2, 1}
+    // activation: none (constant)
+    _graph = std::make_unique<Graph>();
+
+    // Add operands
+
+    Shape shape{1, 0, 2, 1};
+    TypeInfo type{DataType::INT32};
+    Shape shape_scalar(0);
+    TypeInfo type_scalar{DataType::INT32};
+
+    auto operand_lhs = _graph->addOperand(shape, type);
+    auto operand_rhs = _graph->addOperand(shape, type);
+
+    auto operand_activation = _graph->addOperand(shape_scalar, type_scalar);
+    _graph->operands()
+        .at(operand_activation)
+        .data(
+            std::make_unique<CachedData>(reinterpret_cast<const uint8_t *>(&_activation_value), 4));
+
+    auto operand_result = _graph->addOperand(shape, type);
+
+    // Add operations
+
+    operation::Add::Param param;
+    param.activation = Activation::NONE;
+    auto input_set = OperandIndexSequence{operand_lhs, operand_rhs};
+    auto output_set = OperandIndexSequence{operand_result};
+    _graph->addOperation(std::make_unique<operation::Add>(input_set, output_set, param));
+
+    // Identify model inputs and outputs
+
+    _graph->getInputs().append(operand_lhs);
+    _graph->getInputs().append(operand_rhs);
+    _graph->getOutputs().append(operand_result);
+
+    _graph->finishBuilding();
+
+    _executor = std::make_unique<InterpExecutor>(*_graph);
+  }
+
+  void createExecution() { _execution = std::make_unique<Execution>(_executor); }
+
+  virtual void TearDown() { _executor = nullptr; }
+
+  std::unique_ptr<Graph> _graph{nullptr};
+  std::shared_ptr<InterpExecutor> _executor{nullptr};
+  std::unique_ptr<Execution> _execution{nullptr};
+  const int32_t _activation_value{0};
+};
+
+TEST_F(InterpExecutorTest, create_empty)
+{
+  Graph graph;
+  graph.finishBuilding();
+  _executor = std::make_unique<InterpExecutor>(graph);
+  ASSERT_NE(_executor, nullptr);
+}
+
+TEST_F(InterpExecutorTest, create_simple)
+{
+  CreateSimpleModel();
+  ASSERT_NE(_executor, nullptr);
+}
+
+TEST_F(InterpExecutorTest, setInput)
+{
+  CreateSimpleModel();
+  createExecution();
+
+  auto input1 = IOIndex{0};
+  const int32_t input1_buffer[4] = {1, 0, -1, -2};
+
+  EXPECT_THROW(_execution->setInput(input1, reinterpret_cast<const void *>(input1_buffer), 4),
+               std::runtime_error);
+  EXPECT_THROW(_execution->setInput(input1, reinterpret_cast<const void *>(input1_buffer), 12),
+               std::runtime_error);
+  EXPECT_NO_THROW(_execution->setInput(input1, reinterpret_cast<const void *>(input1_buffer), 16));
+}
+
+TEST_F(InterpExecutorTest, setOutput)
+{
+  CreateSimpleModel();
+  createExecution();
+
+  auto output = IOIndex{0};
+  auto output_idx = _graph->getOutputs().at(output);
+
+  int32_t output_buffer[4] = {};
+
+  EXPECT_THROW(_execution->setOutput(output, reinterpret_cast<void *>(output_buffer), 4),
+               std::runtime_error);
+  EXPECT_THROW(_execution->setOutput(output, reinterpret_cast<void *>(output_buffer), 12),
+               std::runtime_error);
+  EXPECT_NO_THROW(_execution->setOutput(output, reinterpret_cast<void *>(output_buffer), 16));
+}
+
+TEST_F(InterpExecutorTest, setInputForUnspecifiedDimensions)
+{
+  CreateUnspecifiedDimensionsModel();
+  createExecution();
+
+  auto input1 = IOIndex{0};
+  const int32_t input1_buffer[4] = {1, 0, -1, -2};
+
+  TypeInfo operand_type{DataType::INT32};
+  Shape operand_shape{1, 2, 2, 1};
+
+  EXPECT_THROW(_execution->setInput(input1, operand_type, operand_shape,
+                                    reinterpret_cast<const void *>(input1_buffer), 4),
+               std::runtime_error);
+  EXPECT_THROW(_execution->setInput(input1, operand_type, operand_shape,
+                                    reinterpret_cast<const void *>(input1_buffer), 12),
+               std::runtime_error);
+  EXPECT_NO_THROW(_execution->setInput(input1, operand_type, operand_shape,
+                                       reinterpret_cast<const void *>(input1_buffer), 16));
+}
+
+TEST_F(InterpExecutorTest, setOutputForUnspecifiedDimensions)
+{
+  CreateUnspecifiedDimensionsModel();
+  createExecution();
+
+  auto output = IOIndex{0};
+  auto output_idx = _graph->getOutputs().at(output);
+
+  TypeInfo operand_type{DataType::INT32};
+  Shape operand_shape{1, 2, 2, 1};
+
+  int32_t output_buffer[4] = {};
+
+  EXPECT_THROW(_execution->setOutput(output, operand_type, operand_shape,
+                                     reinterpret_cast<void *>(output_buffer), 4),
+               std::runtime_error);
+  EXPECT_THROW(_execution->setOutput(output, operand_type, operand_shape,
+                                     reinterpret_cast<void *>(output_buffer), 12),
+               std::runtime_error);
+  EXPECT_NO_THROW(_execution->setOutput(output, operand_type, operand_shape,
+                                        reinterpret_cast<void *>(output_buffer), 16));
+}
+
+TEST_F(InterpExecutorTest, execute)
+{
+  CreateSimpleModel();
+  createExecution();
+
+  auto input1 = IOIndex{0};
+  auto input2 = IOIndex{1};
+  auto input1_idx = _graph->getInputs().at(input1);
+  auto input2_idx = _graph->getInputs().at(input2);
+
+  const int32_t input1_buffer[4] = {1, 0, -1, -2};
+  const int32_t input2_buffer[4] = {1, -3, 2, -4};
+
+  auto output = IOIndex{0};
+  auto output_idx = _graph->getOutputs().at(output);
+
+  int32_t output_buffer[4] = {};
+
+  EXPECT_NO_THROW(_execution->setInput(input1, reinterpret_cast<const void *>(input1_buffer), 16));
+  EXPECT_NO_THROW(_execution->setInput(input2, reinterpret_cast<const void *>(input2_buffer), 16));
+  EXPECT_NO_THROW(_execution->setOutput(output, reinterpret_cast<void *>(output_buffer), 16));
+  EXPECT_NO_THROW(_execution->execute());
+  EXPECT_EQ(output_buffer[0], 2);
+  EXPECT_EQ(output_buffer[1], -3);
+  EXPECT_EQ(output_buffer[2], 1);
+  EXPECT_EQ(output_buffer[3], -6);
+}
+
+TEST_F(InterpExecutorTest, executeTwoStep)
+{
+  CreateTwoStepModel();
+  createExecution();
+
+  auto input1 = IOIndex{0};
+  auto input2 = IOIndex{1};
+  auto input1_idx = _graph->getInputs().at(input1);
+  auto input2_idx = _graph->getInputs().at(input2);
+
+  const int32_t input1_buffer[4] = {1, 0, -1, -2};
+  const int32_t input2_buffer[4] = {1, -3, 2, -4};
+
+  auto output = IOIndex{0};
+  auto output_idx = _graph->getOutputs().at(output);
+
+  int32_t output_buffer[4] = {};
+
+  EXPECT_NO_THROW(_execution->setInput(input1, reinterpret_cast<const void *>(input1_buffer), 16));
+  EXPECT_NO_THROW(_execution->setInput(input2, reinterpret_cast<const void *>(input2_buffer), 16));
+  EXPECT_NO_THROW(_execution->setOutput(output, reinterpret_cast<void *>(output_buffer), 16));
+  EXPECT_NO_THROW(_execution->execute());
+  EXPECT_EQ(output_buffer[0], 5);
+  EXPECT_EQ(output_buffer[1], -2);
+  EXPECT_EQ(output_buffer[2], 0);
+  EXPECT_EQ(output_buffer[3], -1);
+}
+
+} // namespace
diff --git a/runtime/onert/test/graph/Graph.cc b/runtime/onert/test/graph/Graph.cc
new file mode 100644
index 000000000..34e9fe002
--- /dev/null
+++ b/runtime/onert/test/graph/Graph.cc
@@ -0,0 +1,52 @@
+/*
+ * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved
+ *
+ * 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 <gtest/gtest.h>
+
+#include "ir/Graph.h"
+
+TEST(Graph, inputs_and_outputs)
+{
+  onert::ir::Graph graph;
+
+  onert::ir::OperandIndex index0{0u};
+  onert::ir::OperandIndex index1{1u};
+
+  graph.addInput({index0});
+  graph.addInput({index1});
+
+  onert::ir::OperandIndex index10{10u};
+  onert::ir::OperandIndex index11{11u};
+  onert::ir::OperandIndex index12{12u};
+
+  graph.addOutput({index10});
+  graph.addOutput({index11});
+  graph.addOutput({index12});
+
+  ASSERT_EQ(graph.getInputs().size(), 2);
+  ASSERT_EQ(graph.getOutputs().size(), 3);
+
+  onert::ir::IOIndex io_index0{0};
+  onert::ir::IOIndex io_index1{1};
+  onert::ir::IOIndex io_index2{2};
+
+  ASSERT_EQ(graph.getInputs().at(io_index0), 0);
+  ASSERT_EQ(graph.getInputs().at(io_index1), 1);
+
+  ASSERT_EQ(graph.getOutputs().at(io_index0), 10);
+  ASSERT_EQ(graph.getOutputs().at(io_index1), 11);
+  ASSERT_EQ(graph.getOutputs().at(io_index2), 12);
+}
diff --git a/runtime/onert/test/graph/Index.cc b/runtime/onert/test/graph/Index.cc
new file mode 100644
index 000000000..358e64c82
--- /dev/null
+++ b/runtime/onert/test/graph/Index.cc
@@ -0,0 +1,34 @@
+/*
+ * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved
+ *
+ * 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 <gtest/gtest.h>
+
+#include "util/Index.h"
+
+using Index = ::onert::util::Index<uint32_t, struct TestTag>;
+
+TEST(Index, index_test)
+{
+  Index idx1{1u};
+  Index idx2{2u};
+  Index idx3{idx1};
+
+  ASSERT_EQ(idx1, 1);
+  ASSERT_EQ(idx1, 1u);
+  ASSERT_EQ(idx1.value(), 1u);
+  ASSERT_NE(idx1, idx2);
+  ASSERT_EQ(idx1, idx3);
+}
diff --git a/runtime/onert/test/graph/MockNode.h b/runtime/onert/test/graph/MockNode.h
new file mode 100644
index 000000000..60b4719ed
--- /dev/null
+++ b/runtime/onert/test/graph/MockNode.h
@@ -0,0 +1,47 @@
+/*
+ * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved
+ *
+ * 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 __ONERT_TEST_GRAPH_MOCK_NODE_H__
+#define __ONERT_TEST_GRAPH_MOCK_NODE_H__
+
+#include "ir/Operation.h"
+#include "ir/OperandIndexSequence.h"
+
+namespace onert_test
+{
+namespace ir
+{
+
+class SimpleMock : public onert::ir::Operation
+{
+public:
+  SimpleMock(const onert::ir::OperandIndexSequence &inputs,
+             const onert::ir::OperandIndexSequence &outputs)
+      : Operation{onert::ir::OperandConstraint::createAny()}
+  {
+    setInputs(inputs);
+    setOutputs(outputs);
+  }
+
+public:
+  void accept(onert::ir::OperationVisitor &) const override {}
+  onert::ir::OpCode opcode() const final { return onert::ir::OpCode::Invalid; }
+};
+
+} // namespace ir
+} // namespace onert_test
+
+#endif // __ONERT_TEST_GRAPH_MOCK_NODE_H__
diff --git a/runtime/onert/test/graph/operand/IndexSet.cc b/runtime/onert/test/graph/operand/IndexSet.cc
new file mode 100644
index 000000000..6215e0d24
--- /dev/null
+++ b/runtime/onert/test/graph/operand/IndexSet.cc
@@ -0,0 +1,52 @@
+/*
+ * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved
+ *
+ * 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 <gtest/gtest.h>
+
+#include "ir/OperandIndexSequence.h"
+
+using onert::ir::OperandIndex;
+using onert::ir::OperandIndexSequence;
+
+TEST(graph_OperandIndexSequence, append)
+{
+  OperandIndexSequence iset{0, 2, 4, 8};
+
+  ASSERT_EQ(iset.size(), 4);
+
+  iset.append(OperandIndex{10});
+
+  ASSERT_EQ(iset.size(), 5);
+
+  onert::ir::IOIndex index1{1};
+  onert::ir::IOIndex index2{4};
+
+  ASSERT_EQ(iset.at(index1), 2);
+  ASSERT_EQ(iset.at(index2), 10);
+
+  ASSERT_TRUE(iset.contains(OperandIndex{2}));
+  ASSERT_TRUE(iset.contains(OperandIndex{10}));
+  ASSERT_FALSE(iset.contains(OperandIndex{11}));
+}
+
+TEST(graph_OperandIndexSequence, replace)
+{
+  OperandIndexSequence iset{0, 1, 2, 3};
+
+  iset.replace(OperandIndex{1}, OperandIndex{9});
+  ASSERT_FALSE(iset.contains(OperandIndex{1}));
+  ASSERT_TRUE(iset.contains(OperandIndex{9}));
+}
diff --git a/runtime/onert/test/graph/operand/LayoutSet.cc b/runtime/onert/test/graph/operand/LayoutSet.cc
new file mode 100644
index 000000000..e35bddd8b
--- /dev/null
+++ b/runtime/onert/test/graph/operand/LayoutSet.cc
@@ -0,0 +1,43 @@
+/*
+ * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved
+ *
+ * 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 <gtest/gtest.h>
+
+#include "ir/LayoutSet.h"
+
+using onert::ir::Layout;
+using onert::ir::LayoutSet;
+
+TEST(graph_operand_LayoutSet, layout_set_operators)
+{
+  LayoutSet set1{Layout::NCHW};
+  LayoutSet set2{Layout::NHWC};
+  LayoutSet set3 = set1 | set2;
+
+  ASSERT_EQ(set3.size(), 2);
+
+  ASSERT_EQ((set3 - set1).size(), 1);
+  ASSERT_EQ((set3 - set1).contains(Layout::NHWC), true);
+  ASSERT_EQ((set3 - set2).size(), 1);
+  ASSERT_EQ((set3 - set2).contains(Layout::NCHW), true);
+  ASSERT_EQ((set3 - set3).size(), 0);
+
+  ASSERT_EQ((set3 & set1).size(), 1);
+  ASSERT_EQ((set3 & set1).contains(Layout::NCHW), true);
+  ASSERT_EQ((set3 & set2).size(), 1);
+  ASSERT_EQ((set3 & set2).contains(Layout::NHWC), true);
+  ASSERT_EQ((set1 & set2).size(), 0);
+}
diff --git a/runtime/onert/test/graph/operand/Set.cc b/runtime/onert/test/graph/operand/Set.cc
new file mode 100644
index 000000000..0d35b5581
--- /dev/null
+++ b/runtime/onert/test/graph/operand/Set.cc
@@ -0,0 +1,45 @@
+/*
+ * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved
+ *
+ * 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 <gtest/gtest.h>
+
+#include "ir/Operands.h"
+
+TEST(graph_operand_Set, set_test)
+{
+  onert::ir::Operands set;
+
+  onert::ir::Shape shape0{1, 2, 3};
+
+  onert::ir::Shape shape1(4);
+  shape1.dim(0) = 10;
+  shape1.dim(1) = 20;
+  shape1.dim(2) = 30;
+  shape1.dim(3) = 40;
+
+  onert::ir::TypeInfo type{onert::ir::DataType::INT32};
+
+  set.emplace(shape0, type);
+  set.emplace(shape1, type);
+
+  ASSERT_EQ(set.exist(onert::ir::OperandIndex{0u}), true);
+  ASSERT_EQ(set.exist(onert::ir::OperandIndex{1u}), true);
+  ASSERT_EQ(set.exist(onert::ir::OperandIndex{2u}), false);
+
+  ASSERT_EQ(set.at(onert::ir::OperandIndex{0u}).shape().dim(0), 1);
+  ASSERT_EQ(set.at(onert::ir::OperandIndex{0u}).shape().dim(1), 2);
+  ASSERT_EQ(set.at(onert::ir::OperandIndex{0u}).shape().dim(2), 3);
+}
diff --git a/runtime/onert/test/graph/operand/UseDef.cc b/runtime/onert/test/graph/operand/UseDef.cc
new file mode 100644
index 000000000..3e8b14b8b
--- /dev/null
+++ b/runtime/onert/test/graph/operand/UseDef.cc
@@ -0,0 +1,85 @@
+/*
+ * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved
+ *
+ * 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 <gtest/gtest.h>
+
+#include "ir/Graph.h"
+#include "ir/verifier/Verifier.h"
+#include <memory>
+#include "../MockNode.h"
+
+#include <typeindex>
+
+namespace
+{
+
+using IndexSet = onert::ir::OperandIndexSequence;
+using Mock = onert_test::ir::SimpleMock;
+
+} // namespace
+
+TEST(graph_operand_usedef, usedef_test)
+{
+  onert::ir::Graph graph;
+  onert::ir::verifier::DAGChecker verifier;
+
+  onert::ir::Shape shape(3);
+  onert::ir::TypeInfo type{onert::ir::DataType::INT32};
+
+  // Model Input/Output
+  auto input_operand = graph.addOperand(shape, type);
+  auto output_operand = graph.addOperand(shape, type);
+
+  graph.addInput(input_operand);
+  graph.addOutput(output_operand);
+
+  // MockNode1
+  auto operand_index1 = graph.addOperand(shape, type);
+  auto mocknode_index1 =
+      graph.addOperation(std::make_unique<Mock>(IndexSet{input_operand}, IndexSet{operand_index1}));
+
+  // MockNode2
+  auto operand_index2 = graph.addOperand(shape, type);
+  auto mocknode_index2 =
+      graph.addOperation(std::make_unique<Mock>(IndexSet{input_operand}, IndexSet{operand_index2}));
+
+  // MockNode3(two input)
+  auto multiinput_index = graph.addOperation(
+      std::make_unique<Mock>(IndexSet{operand_index1, operand_index2}, IndexSet{output_operand}));
+
+  graph.finishBuilding();
+
+  ASSERT_EQ(verifier.verify(graph), true);
+
+  // Check def
+  ASSERT_EQ(graph.operands().at(operand_index1).getDef().contains(mocknode_index1), true);
+  ASSERT_EQ(graph.operands().at(operand_index2).getDef().contains(mocknode_index2), true);
+  ASSERT_EQ(graph.operands().at(output_operand).getDef().contains(multiinput_index), true);
+
+  ASSERT_EQ(graph.operands().at(operand_index1).getDef().contains(mocknode_index2), false);
+  ASSERT_EQ(graph.operands().at(operand_index1).getDef().contains(multiinput_index), false);
+
+  // Check use
+  ASSERT_EQ(graph.operands().at(input_operand).getUses().contains(mocknode_index1), true);
+  ASSERT_EQ(graph.operands().at(input_operand).getUses().contains(mocknode_index2), true);
+  ASSERT_EQ(graph.operands().at(input_operand).getUses().contains(multiinput_index), false);
+  ASSERT_EQ(graph.operands().at(operand_index1).getUses().contains(multiinput_index), true);
+  ASSERT_EQ(graph.operands().at(operand_index2).getUses().contains(multiinput_index), true);
+
+  ASSERT_EQ(graph.operands().at(input_operand).getUses().size(), 2);
+  ASSERT_EQ(graph.operands().at(operand_index1).getUses().size(), 1);
+  ASSERT_EQ(graph.operands().at(output_operand).getUses().size(), 0);
+}
diff --git a/runtime/onert/test/graph/operation/Set.cc b/runtime/onert/test/graph/operation/Set.cc
new file mode 100644
index 000000000..088c44b8c
--- /dev/null
+++ b/runtime/onert/test/graph/operation/Set.cc
@@ -0,0 +1,33 @@
+/*
+ * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved
+ *
+ * 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 <gtest/gtest.h>
+
+#include "../MockNode.h"
+#include "ir/Operations.h"
+
+using onert::ir::Operation;
+using onert::ir::OperationIndex;
+using onert::ir::Operations;
+
+TEST(graph_operation_Set, operation_test)
+{
+  Operations ops;
+  ops.push(std::unique_ptr<Operation>(new onert_test::ir::SimpleMock({1, 2, 3, 4}, {5, 6, 7})));
+  OperationIndex idx{0u};
+  ASSERT_EQ(ops.at(idx).getInputs().size(), 4);
+  ASSERT_EQ(ops.at(idx).getOutputs().size(), 3);
+}
diff --git a/runtime/onert/test/graph/operation/SetIO.cc b/runtime/onert/test/graph/operation/SetIO.cc
new file mode 100644
index 000000000..378c5b4b9
--- /dev/null
+++ b/runtime/onert/test/graph/operation/SetIO.cc
@@ -0,0 +1,99 @@
+/*
+ * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved
+ *
+ * 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 <gtest/gtest.h>
+
+#include "ir/Graph.h"
+#include "ir/Index.h"
+#include "ir/OperandIndexSequence.h"
+#include "ir/operation/Conv2D.h"
+#include "ir/operation/Concat.h"
+
+#include <memory>
+
+#include <stdexcept>
+
+using Index = onert::ir::IOIndex;
+using IndexSet = onert::ir::OperandIndexSequence;
+
+TEST(graph_operation_setIO, operation_setIO_conv)
+{
+  onert::ir::Graph graph;
+
+  onert::ir::Shape shape{3};
+  onert::ir::TypeInfo type{onert::ir::DataType::INT32};
+
+  // Add Conv
+  using Graph = onert::ir::operation::Conv2D;
+
+  auto input_operand = graph.addOperand(shape, type);
+  auto kernel_operand = graph.addOperand(shape, type);
+  auto bias_operand = graph.addOperand(shape, type);
+  IndexSet inputs{input_operand, kernel_operand, bias_operand};
+
+  Graph::Param conv_params;
+  conv_params.padding.type = onert::ir::PaddingType::SAME;
+  conv_params.stride.horizontal = 1;
+  conv_params.stride.vertical = 1;
+  conv_params.activation = onert::ir::Activation::NONE;
+
+  auto output_operand = graph.addOperand(shape, type).value();
+  IndexSet outputs{output_operand};
+
+  auto conv = std::make_unique<Graph>(inputs, outputs, conv_params);
+
+  ASSERT_NE(conv, nullptr);
+  ASSERT_EQ(conv->getInputs().at(Index{0}).value(), inputs.at(0).value());
+  conv->setInputs({8, 9, 10});
+  ASSERT_NE(conv->getInputs().at(Index{0}).value(), inputs.at(0).value());
+  ASSERT_EQ(conv->getInputs().at(Index{0}).value(), 8);
+}
+
+TEST(graph_operation_setIO, operation_setIO_concat)
+{
+  onert::ir::Graph graph;
+
+  onert::ir::Shape shape{3};
+
+  onert::ir::TypeInfo type{onert::ir::DataType::INT32};
+
+  using Graph = onert::ir::operation::Concat;
+
+  // Add Concat
+  IndexSet inputs;
+  for (int i = 0; i < 6; ++i)
+  {
+    inputs.append(graph.addOperand(shape, type));
+  }
+
+  Graph::Param concat_params{0};
+
+  auto output_operand = graph.addOperand(shape, type).value();
+  IndexSet outputs{output_operand};
+
+  auto concat = std::make_unique<Graph>(inputs, outputs, concat_params);
+
+  ASSERT_NE(concat, nullptr);
+  ASSERT_EQ(concat->getInputs().size(), 6);
+  ASSERT_EQ(concat->getInputs().at(Index{0}).value(), inputs.at(0).value());
+
+  concat->setInputs({80, 6, 9, 11});
+  ASSERT_EQ(concat->getInputs().size(), 4);
+  ASSERT_NE(concat->getInputs().at(Index{0}).value(), inputs.at(0).value());
+  ASSERT_EQ(concat->getInputs().at(Index{0}).value(), 80);
+  ASSERT_EQ(concat->getInputs().at(Index{2}).value(), 9);
+  ASSERT_THROW(concat->getInputs().at(Index{5}), std::out_of_range);
+}
diff --git a/runtime/onert/test/graph/verifier/Verifier.cc b/runtime/onert/test/graph/verifier/Verifier.cc
new file mode 100644
index 000000000..f8c7557e3
--- /dev/null
+++ b/runtime/onert/test/graph/verifier/Verifier.cc
@@ -0,0 +1,49 @@
+/*
+ * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved
+ *
+ * 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 <gtest/gtest.h>
+
+#include "ir/Operation.h"
+#include "ir/Graph.h"
+#include "ir/verifier/Verifier.h"
+#include <memory>
+#include "ir/Operand.h"
+#include "../MockNode.h"
+
+using IndexSet = onert::ir::OperandIndexSequence;
+using Mock = onert_test::ir::SimpleMock;
+
+TEST(Verifier, dag_checker)
+{
+  onert::ir::Graph graph;
+
+  onert::ir::Shape shape{3};
+  onert::ir::TypeInfo type{onert::ir::DataType::INT32};
+
+  auto operand1 = graph.addOperand(shape, type);
+  auto operand2 = graph.addOperand(shape, type);
+
+  graph.addInput(operand1);
+  graph.addOutput(operand2);
+
+  graph.addOperation(std::make_unique<Mock>(IndexSet{operand1}, IndexSet{operand2}));
+
+  graph.finishBuilding();
+
+  onert::ir::verifier::DAGChecker verifier;
+
+  ASSERT_EQ(verifier.verify(graph), true);
+}
diff --git a/runtime/onert/test/util/ObjectManager.cc b/runtime/onert/test/util/ObjectManager.cc
new file mode 100644
index 000000000..5051bcfa6
--- /dev/null
+++ b/runtime/onert/test/util/ObjectManager.cc
@@ -0,0 +1,97 @@
+/*
+ * Copyright (c) 2020 Samsung Electronics Co., Ltd. All Rights Reserved
+ *
+ * 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 <gtest/gtest.h>
+
+#include "util/ObjectManager.h"
+#include "util/Index.h"
+
+using namespace onert;
+
+struct TestTag;
+using Index = typename util::Index<uint32_t, TestTag>;
+
+TEST(ObjectManager, emplace)
+{
+  util::ObjectManager<Index, int> man;
+
+  auto index = man.emplace(100);
+  ASSERT_EQ(man.at(index), 100);
+}
+
+TEST(ObjectManager, remove_1)
+{
+  util::ObjectManager<Index, int> man;
+
+  Index index = man.emplace(100);
+  ASSERT_TRUE(man.exist(index));
+  ASSERT_EQ(man.at(index), 100);
+
+  man.remove(index);
+  ASSERT_FALSE(man.exist(index));
+}
+
+TEST(ObjectManager, remove_2)
+{
+  util::ObjectManager<Index, int> man;
+
+  auto index0 = man.emplace(100);
+  auto index1 = man.emplace(200);
+  ASSERT_TRUE(man.exist(index0));
+  ASSERT_EQ(man.at(index0), 100);
+  ASSERT_TRUE(man.exist(index1));
+  ASSERT_EQ(man.at(index1), 200);
+
+  man.remove(index0);
+  ASSERT_FALSE(man.exist(index0));
+  ASSERT_TRUE(man.exist(index1));
+  ASSERT_EQ(man.at(index1), 200);
+}
+
+TEST(ObjectManager, push)
+{
+  util::ObjectManager<Index, int> man;
+
+  auto index = man.push(std::unique_ptr<int>{new int{100}});
+  ASSERT_EQ(man.at(index), 100);
+}
+
+TEST(ObjectManager, const_iterate)
+{
+  util::ObjectManager<Index, int> man;
+
+  auto index0 = man.emplace(100);
+  auto index1 = man.emplace(200);
+  auto index2 = man.emplace(300);
+
+  int sum = 0;
+  man.iterate([&](const Index &index, const int &val) { sum += val; });
+  ASSERT_EQ(sum, 600);
+}
+
+TEST(ObjectManager, non_const_iterate)
+{
+  util::ObjectManager<Index, int> man;
+
+  auto index0 = man.emplace(100);
+  auto index1 = man.emplace(200);
+  auto index2 = man.emplace(300);
+
+  man.iterate([&](const Index &index, int &val) { val += 1; });
+  ASSERT_EQ(man.at(index0), 101);
+  ASSERT_EQ(man.at(index1), 201);
+  ASSERT_EQ(man.at(index2), 301);
+}
diff --git a/runtime/onert/test/util/ShapeInference.cc b/runtime/onert/test/util/ShapeInference.cc
new file mode 100644
index 000000000..053b635f2
--- /dev/null
+++ b/runtime/onert/test/util/ShapeInference.cc
@@ -0,0 +1,230 @@
+/*
+ * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
+ *
+ * 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 <gtest/gtest.h>
+
+#include "ir/Layout.h"
+#include "util/ShapeInference.h"
+
+using namespace onert::ir;
+
+TEST(ShapeInference, Elementwise)
+{
+  Shape lhs_shape{1, 299, 299, 3};
+  Shape rhs_shape{3};
+  auto infered_shapes = onert::shape_inference::inferEltwiseShape(lhs_shape, rhs_shape);
+  auto infered_out_shape = infered_shapes[0];
+
+  ASSERT_EQ(infered_out_shape.rank(), 4);
+  ASSERT_EQ(infered_out_shape.dim(0), 1);
+  ASSERT_EQ(infered_out_shape.dim(1), 299);
+  ASSERT_EQ(infered_out_shape.dim(2), 299);
+  ASSERT_EQ(infered_out_shape.dim(3), 3);
+}
+
+TEST(ShapeInference, IncorrectElementwise)
+{
+  Shape lhs_shape{1, 299, 299, 3};
+  Shape rhs_shape{5, 3};
+  ASSERT_THROW(onert::shape_inference::inferEltwiseShape(lhs_shape, rhs_shape), std::runtime_error);
+}
+
+TEST(ShapeInference, Pool2DNodeSame)
+{
+  Shape in_shape{10, 6, 12, 20};
+  Stride stride{3, 7};
+  Padding padding{PaddingType::SAME};
+
+  operation::AvgPool2D::Param avg_pool_param{3, 6, stride, padding, Activation::NONE};
+  auto infered_shapes = onert::shape_inference::inferAvgPoolShape(in_shape, avg_pool_param);
+  auto infered_out_shape = infered_shapes[0];
+
+  ASSERT_EQ(infered_out_shape.rank(), 4);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).N, 10);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).H, 2);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).W, 2);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).C, 20);
+
+  operation::MaxPool2D::Param max_pool_param{3, 6, stride, padding, Activation::NONE};
+  infered_shapes = onert::shape_inference::inferMaxPoolShape(in_shape, max_pool_param);
+  infered_out_shape = infered_shapes[0];
+
+  ASSERT_EQ(infered_out_shape.rank(), 4);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).N, 10);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).H, 2);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).W, 2);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).C, 20);
+}
+
+TEST(ShapeInference, Pool2DNodeValid)
+{
+  Shape in_shape{10, 6, 12, 20};
+  Stride stride{3, 7};
+  Padding padding{PaddingType::VALID};
+
+  operation::AvgPool2D::Param avg_pool_param{3, 6, stride, padding, Activation::NONE};
+  auto infered_shapes = onert::shape_inference::inferAvgPoolShape(in_shape, avg_pool_param);
+  auto infered_out_shape = infered_shapes[0];
+
+  ASSERT_EQ(infered_out_shape.rank(), 4);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).N, 10);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).H, 2);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).W, 1);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).C, 20);
+
+  operation::MaxPool2D::Param max_pool_param{3, 6, stride, padding, Activation::NONE};
+  infered_shapes = onert::shape_inference::inferMaxPoolShape(in_shape, max_pool_param);
+  infered_out_shape = infered_shapes[0];
+
+  ASSERT_EQ(infered_out_shape.rank(), 4);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).N, 10);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).H, 2);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).W, 1);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).C, 20);
+}
+
+TEST(ShapeInference, Pool2DNodeExplicit)
+{
+  Shape in_shape{10, 3, 5, 20};
+
+  Stride stride{3, 7};
+  Padding padding{4, 3, 2, 1};
+
+  operation::AvgPool2D::Param avg_pool_param{3, 6, stride, padding, Activation::NONE};
+  auto infered_shapes = onert::shape_inference::inferAvgPoolShape(in_shape, avg_pool_param);
+  auto infered_out_shape = infered_shapes[0];
+
+  ASSERT_EQ(infered_out_shape.rank(), 4);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).N, 10);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).H, 2);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).W, 1);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).C, 20);
+
+  operation::MaxPool2D::Param max_pool_param{3, 6, stride, padding, Activation::NONE};
+  infered_shapes = onert::shape_inference::inferMaxPoolShape(in_shape, max_pool_param);
+  infered_out_shape = infered_shapes[0];
+
+  ASSERT_EQ(infered_out_shape.rank(), 4);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).N, 10);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).H, 2);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).W, 1);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).C, 20);
+}
+
+TEST(ShapeInference, Conv2D)
+{
+  Shape in_shape{10, 6, 12, 20};
+  Shape ker_shape{30, 3, 6, 20};
+
+  operation::Conv2D::Param param{Stride{3, 7}, Padding{PaddingType::VALID}, Activation::NONE};
+  auto infered_shapes = onert::shape_inference::inferConv2DShape(in_shape, ker_shape, param);
+  auto infered_out_shape = infered_shapes[0];
+
+  ASSERT_EQ(infered_out_shape.rank(), 4);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).N, 10);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).H, 2);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).W, 1);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).C, 30);
+
+  param = operation::Conv2D::Param{Stride{3, 7}, Padding{PaddingType::SAME}, Activation::NONE};
+  infered_shapes = onert::shape_inference::inferConv2DShape(in_shape, ker_shape, param);
+  infered_out_shape = infered_shapes[0];
+
+  ASSERT_EQ(infered_out_shape.rank(), 4);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).N, 10);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).H, 2);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).W, 2);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).C, 30);
+
+  param = operation::Conv2D::Param{Stride{3, 7}, Padding{4, 3, 2, 1}, Activation::NONE};
+  infered_shapes = onert::shape_inference::inferConv2DShape(in_shape, ker_shape, param);
+  infered_out_shape = infered_shapes[0];
+
+  ASSERT_EQ(infered_out_shape.rank(), 4);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).N, 10);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).H, 3);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).W, 2);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).C, 30);
+}
+
+TEST(ShapeInference, DepthwiseConv2D)
+{
+  Shape in_shape{10, 6, 12, 20};
+  Shape ker_shape{1, 3, 6, 60};
+
+  operation::DepthwiseConv2D::Param param{Stride{3, 7}, Padding{PaddingType::VALID}, 3,
+                                          Activation::NONE};
+  auto infered_shapes =
+      onert::shape_inference::inferDepthwiseConv2DShape(in_shape, ker_shape, param);
+  auto infered_out_shape = infered_shapes[0];
+
+  ASSERT_EQ(infered_out_shape.rank(), 4);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).N, 10);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).H, 2);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).W, 1);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).C, 60);
+
+  param = operation::DepthwiseConv2D::Param{Stride{3, 7}, Padding{PaddingType::SAME}, 3,
+                                            Activation::NONE};
+  infered_shapes = onert::shape_inference::inferDepthwiseConv2DShape(in_shape, ker_shape, param);
+  infered_out_shape = infered_shapes[0];
+
+  ASSERT_EQ(infered_out_shape.rank(), 4);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).N, 10);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).H, 2);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).W, 2);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).C, 60);
+
+  param = operation::DepthwiseConv2D::Param{Stride{3, 7}, Padding{4, 3, 2, 1}, 3, Activation::NONE};
+  infered_shapes = onert::shape_inference::inferDepthwiseConv2DShape(in_shape, ker_shape, param);
+  infered_out_shape = infered_shapes[0];
+
+  ASSERT_EQ(infered_out_shape.rank(), 4);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).N, 10);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).H, 3);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).W, 2);
+  ASSERT_EQ(infered_out_shape.asFeature(Layout::NHWC).C, 60);
+}
+
+TEST(ShapeInference, Concat)
+{
+  Shape in1{10, 20, 30, 3, 50};
+  Shape in2{10, 20, 30, 2, 50};
+  Shape in3{10, 20, 30, 2, 50};
+
+  operation::Concat::Param param{3};
+  auto infered_shapes = onert::shape_inference::inferConcatShape({in1, in2, in3}, param);
+  auto infered_out_shape = infered_shapes[0];
+
+  ASSERT_EQ(infered_out_shape.rank(), 5);
+  ASSERT_EQ(infered_out_shape.dim(0), 10);
+  ASSERT_EQ(infered_out_shape.dim(1), 20);
+  ASSERT_EQ(infered_out_shape.dim(2), 30);
+  ASSERT_EQ(infered_out_shape.dim(3), 7);
+  ASSERT_EQ(infered_out_shape.dim(4), 50);
+}
+
+TEST(ShapeInference, FullyConnected)
+{
+  Shape in_shape{3, 4, 5, 6};
+  Shape ker_shape{3, 10};
+  auto infered_shapes = onert::shape_inference::inferFullyConnectedShape(in_shape, ker_shape);
+  auto infered_out_shape = infered_shapes[0];
+
+  ASSERT_EQ(infered_out_shape.rank(), 2);
+  ASSERT_EQ(infered_out_shape.dim(0), 36);
+  ASSERT_EQ(infered_out_shape.dim(1), 3);
+}