Optimize project variable updates to use parallel node processing

Performance improvement for project variable updates when multiple containers
are present. Previously, nodes were updated serially in a for loop, causing:
- 5 containers: ~35 seconds (7s per container)
- 10 containers: ~70 seconds
- 20 containers: ~140 seconds (2min 20sec)

Changed to parallel processing using asyncio.gather(), reducing total time
to the duration of the slowest single node update (~7 seconds regardless
of container count).

The change maintains error handling with return_exceptions=True to ensure
one node's update failure doesn't prevent others from completing.

This is particularly important for users with large topologies containing
many Docker containers that need to be recreated when project variables change.

Related to issue #2755 ghost node timeout fix.

gns3server/compute/project.py

@@ -293,9 +293,14 @@ class Project:
 
         # we need to update docker nodes when variables changes
         if original_variables != variables:
+            # Parallelize node updates for better performance
+            tasks = []
             for node in self.nodes:
                 if hasattr(node, "update"):
-                    await node.update()
+                    tasks.append(node.update())
+
+            if tasks:
+                await asyncio.gather(*tasks, return_exceptions=True)
 
     async def close(self):
         """