Implementing DAG reset, still need to make sure GraphExecutor is not executing DAG during reset ...

Signed-off-by: Dmitry I. Lyakh <quant4me@gmail.com>

src/runtime/graph/boost/directed_boost_graph.cpp

 /** ExaTN:: Tensor Runtime: Directed acyclic graph of tensor operations
-REVISION: 2020/06/23
+REVISION: 2021/09/21
 
-Copyright (C) 2018-2020 Tiffany Mintz, Dmitry Lyakh, Alex McCaskey
-Copyright (C) 2018-2020 Oak Ridge National Laboratory (UT-Battelle)
+Copyright (C) 2018-2021 Dmitry Lyakh, Alex McCaskey, Tiffany Mintz
+Copyright (C) 2018-2021 Oak Ridge National Laboratory (UT-Battelle)
 **/
 
 #include "directed_boost_graph.hpp"
@@ -167,5 +167,15 @@ void DirectedBoostGraph::printIt()
   return;
 }
 
+
+void DirectedBoostGraph::clear()
+{
+  lock();
+  dag_->clear();
+  exec_state_.clear();
+  unlock();
+  return;
+}
+
 } // namespace runtime
 } // namespace exatn

src/runtime/graph/boost/directed_boost_graph.hpp

 /** ExaTN:: Tensor Runtime: Directed acyclic graph of tensor operations
-REVISION: 2020/06/08
+REVISION: 2021/09/21
 
-Copyright (C) 2018-2020 Tiffany Mintz, Dmitry Lyakh, Alex McCaskey
-Copyright (C) 2018-2020 Oak Ridge National Laboratory (UT-Battelle)
+Copyright (C) 2018-2021 Dmitry Lyakh, Alex McCaskey, Tiffany Mintz
+Copyright (C) 2018-2021 Oak Ridge National Laboratory (UT-Battelle)
 
 Rationale:
  (a) Tensor graph is a directed acyclic graph in which vertices
@@ -121,6 +121,8 @@ public:
     return std::make_shared<DirectedBoostGraph>();
   }
 
+  virtual void clear() override;
+
 protected:
   DirectedGraphType dag_; //std::shared_ptr<d_adj_list>
 };

src/runtime/graph/tensor_exec_state.cpp

 /** ExaTN:: Tensor Runtime: Tensor graph execution state
-REVISION: 2020/06/23
+REVISION: 2021/09/21
 
-Copyright (C) 2018-2020 Dmitry Lyakh, Tiffany Mintz, Alex McCaskey
-Copyright (C) 2018-2020 Oak Ridge National Laboratory (UT-Battelle)
+Copyright (C) 2018-2021 Dmitry Lyakh, Tiffany Mintz, Alex McCaskey
+Copyright (C) 2018-2021 Oak Ridge National Laboratory (UT-Battelle)
 **/
 
 #include "tensor_exec_state.hpp"
@@ -137,5 +137,14 @@ VertexIdType TensorExecState::getFrontNode() const
  return front_node_;
 }
 
+void TensorExecState::clear()
+{
+ assert(nodes_ready_.empty());
+ assert(nodes_executing_.empty());
+ tensor_info_.clear();
+ front_node_ = 0;
+ return;
+}
+
 } // namespace runtime
 } // namespace exatn

src/runtime/graph/tensor_exec_state.hpp

 /** ExaTN:: Tensor Runtime: Tensor graph execution state
-REVISION: 2020/06/23
+REVISION: 2021/09/21
 
-Copyright (C) 2018-2020 Dmitry Lyakh, Tiffany Mintz, Alex McCaskey
-Copyright (C) 2018-2020 Oak Ridge National Laboratory (UT-Battelle)
+Copyright (C) 2018-2021 Dmitry Lyakh, Tiffany Mintz, Alex McCaskey
+Copyright (C) 2018-2021 Oak Ridge National Laboratory (UT-Battelle)
 
 Rationale:
  (a) Tensor graph is a directed acyclic graph in which vertices
@@ -132,6 +132,9 @@ public:
   /** Returns the front node id. **/
   VertexIdType getFrontNode() const;
 
+  /** Clears the object. **/
+  void clear();
+
 private:
   /** Table for tracking the execution status of a given tensor:
       Tensor Hash --> TensorExecInfo **/

src/runtime/graph/tensor_graph.hpp

 /** ExaTN:: Tensor Runtime: Directed acyclic graph (DAG) of tensor operations
-REVISION: 2020/06/23
+REVISION: 2021/09/21
 
-Copyright (C) 2018-2020 Tiffany Mintz, Dmitry Lyakh, Alex McCaskey
-Copyright (C) 2018-2020 Oak Ridge National Laboratory (UT-Battelle)
+Copyright (C) 2018-2021 Dmitry Lyakh, Alex McCaskey, Tiffany Mintz
+Copyright (C) 2018-2021 Oak Ridge National Laboratory (UT-Battelle)
 
 Rationale:
  (a) The execution space consists of one or more DAGs in which nodes
@@ -343,6 +343,13 @@ public:
     return (exec_state_.getFrontNode() < this->getNumNodes());
   }
 
+  virtual void clear() {
+    lock();
+    exec_state_.clear();
+    unlock();
+    return;
+  }
+
   inline void lock() {mtx_.lock();}
   inline void unlock() {mtx_.unlock();}
 

src/runtime/tensor_runtime.cpp

 /** ExaTN:: Tensor Runtime: Task-based execution layer for tensor operations
-REVISION: 2021/04/01
+REVISION: 2021/09/21
 
 Copyright (C) 2018-2021 Dmitry Lyakh, Tiffany Mintz, Alex McCaskey
 Copyright (C) 2018-2021 Oak Ridge National Laboratory (UT-Battelle)
@@ -276,6 +276,13 @@ bool TensorRuntime::sync(bool wait) {
    if(current_dag_->hasUnexecutedNodes()) executing_.store(true);
    still_working = executing_.load();
   }
+  if(wait && (!still_working)){
+   if(current_dag_->getNumNodes() > MAX_RUNTIME_DAG_SIZE){
+    std::cout << "#DEBUG(TensorRuntime::sync)[MAIN_THREAD]: Clearing DAG ... "; //debug
+    current_dag_->clear();
+    std::cout << "Done\n" << std::flush; //debug
+   }
+  }
   return !still_working;
 }
 

src/runtime/tensor_runtime.hpp

 /** ExaTN:: Tensor Runtime: Task-based execution layer for tensor operations
-REVISION: 2021/04/01
+REVISION: 2021/09/21
 
 Copyright (C) 2018-2021 Dmitry Lyakh, Tiffany Mintz, Alex McCaskey
 Copyright (C) 2018-2021 Oak Ridge National Laboratory (UT-Battelle)
@@ -69,6 +69,8 @@ class TensorRuntime final {
 
 public:
 
+  static constexpr std::size_t MAX_RUNTIME_DAG_SIZE = 1000000000;
+
 #ifdef MPI_ENABLED
   TensorRuntime(const MPICommProxy & communicator,                               //MPI communicator proxy
                 const ParamConf & parameters,                                    //runtime configuration parameters