1 files changed, 93 insertions, 0 deletions
diff --git a/runtimes/neurun/backend/cpu/MemoryManager.cc b/runtimes/neurun/backend/cpu/MemoryManager.cc
new file mode 100644
index 000000000..192a6db36
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+++ b/runtimes/neurun/backend/cpu/MemoryManager.cc
@@ -0,0 +1,93 @@
+/*
+ * 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 "MemoryManager.h"
+
+#include <cassert>
+
+#include "MemoryPlannerFactory.h"
+#include <backend/operand/Object.h>
+#include "util/logging.h"
+#include "util/ConfigSource.h"
+
+namespace neurun
+{
+namespace backend
+{
+namespace cpu
+{
+
+MemoryManager::MemoryManager() : _mem_planner{createMemoryPlanner()}
+{
+  // DO NOTHING
+}
+
+IMemoryPlanner *MemoryManager::createMemoryPlanner()
+{
+  auto planner_id = util::getConfigString(util::config::CPU_MEMORY_PLANNER);
+  return MemoryPlannerFactory::instance().create(planner_id);
+}
+
+void MemoryManager::buildTensor(const model::OperandIndex &ind, const model::OperandInfo &info)
+{
+  auto tensor = std::make_shared<operand::Tensor>(info);
+  _tensors[ind] = tensor;
+}
+
+void MemoryManager::claimPlan(const model::OperandIndex &ind, uint32_t size)
+{
+  _mem_planner->claim(ind, size);
+}
+
+void MemoryManager::releasePlan(const model::OperandIndex &ind) { _mem_planner->release(ind); }
+
+void MemoryManager::allocate(void)
+{
+  _mem_alloc = std::make_shared<Allocator>(_mem_planner->capacity());
+  assert(_mem_alloc->base());
+
+  for (auto &mem_plan : _mem_planner->memory_plans())
+  {
+    auto ind = mem_plan.first;
+    auto mem_blk = mem_plan.second;
+
+    uint8_t *buffer = _mem_alloc->base() + mem_blk.offset;
+    auto tensor = _tensors[ind];
+    tensor->setBuffer(buffer);
+
+    VERBOSE(CPU_MEMORYMANAGER) << "TENSOR(#" << ind.value() << "): " << static_cast<void *>(buffer)
+                               << std::endl;
+
+    // If we do not make tensor here currently, kernel generation would cause segmentation fault.
+    // See also : Comments in `allocate` method.
+  }
+}
+
+std::shared_ptr<backend::operand::IObject> MemoryManager::wrapTensor(const model::OperandIndex &ind)
+{
+  if (_objects.find(ind) != _objects.end())
+  {
+    return _objects.at(ind);
+  }
+  else
+  {
+    return _objects[ind] = std::make_shared<::neurun::backend::operand::Object>(_tensors.at(ind));
+  }
+}
+
+} // namespace cpu
+} // namespace backend
+} // namespace neurun