write overlaps with execute

src/tools/nbench/benchmark_pipelined.cpp

@@ -48,10 +48,16 @@ static size_t current_iteration = 0;
 static size_t s_iterations;
 static size_t s_warmup_iterations;
 
-static void do_iteration(runtime::Executable* exec, const TensorCollection& tensors)
+static void
+    thread_entry(runtime::Executable* exec, const TensorCollection& tensors, size_t pipeline_stage)
 {
+    bool data_written = false;
     const vector<shared_ptr<runtime::Tensor>>& args = tensors.input_tensors;
     const vector<shared_ptr<runtime::Tensor>>& results = tensors.output_tensors;
+    while (current_iteration < s_iterations + s_warmup_iterations)
+    {
+        if (!data_written)
+        {
             for (size_t arg_index = 0; arg_index < args.size(); arg_index++)
             {
                 const shared_ptr<runtime::Tensor>& arg = args[arg_index];
@@ -62,22 +68,8 @@ static void do_iteration(runtime::Executable* exec, const TensorCollection& tens
                             data->get_element_count() * data->get_element_type().size());
                 }
             }
-    exec->call(results, args);
-    for (size_t result_index = 0; result_index < results.size(); result_index++)
-    {
-        const shared_ptr<runtime::HostTensor>& data = tensors.result_data[result_index];
-        const shared_ptr<runtime::Tensor>& result = results[result_index];
-        result->read(data->get_data_ptr(),
-                     data->get_element_count() * data->get_element_type().size());
+            data_written = true;
         }
-}
-
-static void
-    thread_entry(runtime::Executable* exec, const TensorCollection& tensors, size_t pipeline_stage)
-// static void thread_entry(size_t pipeline_stage)
-{
-    while (current_iteration < s_iterations + s_warmup_iterations)
-    {
         unique_lock<mutex> lock(s_mutex);
         if ((current_iteration & 1) != pipeline_stage)
         {
@@ -87,8 +79,16 @@ static void
         {
             // our turn to run
             NGRAPH_INFO << "stage " << pipeline_stage << " for iteration " << current_iteration;
-            do_iteration(exec, tensors);
+            exec->call(results, args);
+            for (size_t result_index = 0; result_index < results.size(); result_index++)
+            {
+                const shared_ptr<runtime::HostTensor>& data = tensors.result_data[result_index];
+                const shared_ptr<runtime::Tensor>& result = results[result_index];
+                result->read(data->get_data_ptr(),
+                            data->get_element_count() * data->get_element_type().size());
+            }
             current_iteration++;
+            data_written = false;
             s_condition.notify_all();
         }
     }