1 files changed, 140 insertions, 0 deletions
diff --git a/runtimes/neurun/core/src/exec/ParallelExecutor.cc b/runtimes/neurun/core/src/exec/ParallelExecutor.cc
new file mode 100644
index 000000000..81d4ac03f
--- /dev/null
+++ b/runtimes/neurun/core/src/exec/ParallelExecutor.cc
@@ -0,0 +1,140 @@
+/*
+ * 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 "ParallelExecutor.h"
+
+#include <cassert>
+
+#include "util/logging.h"
+#include "exec/IFunction.h"
+
+namespace neurun
+{
+namespace exec
+{
+
+class HookFunction : public IFunction
+{
+public:
+  HookFunction(IFunction *fn, std::function<void()> teardown) : _fn{fn}, _teardown{teardown} {}
+
+public:
+  void run() override
+  {
+    // TODO Introduce and call setup() function here
+    _fn->run();
+    _teardown();
+  }
+  void runSync() override { throw("runSync is needed just for profiling in Dataflow executor"); }
+
+private:
+  IFunction *_fn;
+  std::function<void()> _teardown;
+};
+
+void ParallelExecutor::notify(uint32_t finished_job_id)
+{
+  std::unique_lock<std::mutex> lock{_mu_jobs};
+
+  DataflowExecutor::notify(finished_job_id);
+
+  lock.unlock();
+  _cv_jobs.notify_all();
+}
+
+ParallelExecutor::ParallelExecutor(const std::shared_ptr<const model::Model> &model,
+                                   std::unique_ptr<model::Subgraphs> subgraphs,
+                                   const std::shared_ptr<compiler::OperandContext> &operand_context,
+                                   std::unique_ptr<graph::LowerInfoMap> lower_info,
+                                   std::unique_ptr<backend::TensorManagerSet> tensor_mgrs,
+                                   CodeMap &&code_map)
+    : DataflowExecutor{model,
+                       std::move(subgraphs),
+                       operand_context,
+                       std::move(lower_info),
+                       std::move(tensor_mgrs),
+                       std::move(code_map)}
+{
+  VERBOSE(ParallelExecutor) << "Constructing Parallel Executor" << std::endl;
+}
+
+void ParallelExecutor::executeImpl()
+{
+  // Init scheduler
+  // TODO Consider to have distinct backend set in LowerInfoMap
+  graph::BackendSet backends;
+  for (auto &itr : _lower_info->operation)
+  {
+    backends.add(itr.second->backend());
+  }
+  _scheduler = nnfw::cpp14::make_unique<ParallelScheduler>(backends);
+
+  assert(noWaitingJobs());
+
+  // Execution setup
+  _waiting_jobs.swap(_finished_jobs); // Move finished jobs to waiting jobs
+
+  for (uint32_t i = 0; i < _waiting_jobs.size(); ++i)
+  {
+    VERBOSE(ParallelExecutor) << i << ": " << _input_info[i] << std::endl;
+    if (_input_info[i] == 0)
+    {
+      emplaceToReadyJobs(i);
+    }
+  }
+  assert(!_ready_jobs.empty()); // Cannot begin if there is no initial jobs
+
+  VERBOSE(ParallelExecutor) << "INITIAL JOBS : " << _ready_jobs.size() << std::endl;
+
+  while (true)
+  {
+    std::unique_lock<std::mutex> lock{_mu_jobs};
+
+    if (_ready_jobs.empty())
+    {
+      _cv_jobs.wait(lock, [this] { return !_ready_jobs.empty() || noWaitingJobs(); });
+      // Check finish condition
+      if (_ready_jobs.empty() && noWaitingJobs())
+      {
+        break;
+      }
+    }
+
+    auto job = std::move(_ready_jobs.begin()->second);
+    _ready_jobs.erase(_ready_jobs.begin());
+
+    lock.unlock();
+
+    VERBOSE(ParallelExecutor) << "Assigning fn #" << job->index() << std::endl;
+
+    auto job_index = job->index();
+    auto teardown = [&, job_index]() { notify(job_index); };
+
+    _scheduler->assign(nnfw::cpp14::make_unique<HookFunction>(job->fn(), teardown), job->backend());
+    _finished_jobs[job_index] = std::move(job);
+  }
+
+  assert(noWaitingJobs());
+
+  // Wait for all the jobs done
+  _scheduler->finish();
+
+  // Reset input info for the next execution
+  _input_info = _initial_input_info;
+}
+
+} // namespace exec
+} // namespace neurun