diff --git a/test/spmd/test_xla_sharding.py b/test/spmd/test_xla_sharding.py
index f42289f8d26..04e079089f2 100644
--- a/test/spmd/test_xla_sharding.py
+++ b/test/spmd/test_xla_sharding.py
@@ -1089,6 +1089,13 @@ def test_mark_shard_scalar(self):
     with self.assertRaises(AttributeError):
       xt.mesh_shape
 
+  def test_global_mesh(self):
+    expected_mesh = self._get_mesh((1, self.n_devices))
+    xs.set_global_mesh(expected_mesh)
+    mesh = xs.get_global_mesh()
+
+    self.assertEqual(id(mesh), id(expected_mesh))
+
 
 if __name__ == '__main__':
   test = unittest.main()
diff --git a/torch_xla/distributed/spmd/__init__.py b/torch_xla/distributed/spmd/__init__.py
index 7f494b74c9d..53376979d3c 100644
--- a/torch_xla/distributed/spmd/__init__.py
+++ b/torch_xla/distributed/spmd/__init__.py
@@ -1,7 +1,8 @@
 from .xla_sharded_tensor import XLAShard, XLAShardedTensor
 from .xla_sharding import (Mesh, HybridMesh, ShardingType, ShardingSpec,
                            XLAPatchedLinear, mark_sharding, clear_sharding,
-                           wrap_if_sharded, xla_patched_nn_linear_forward)
+                           wrap_if_sharded, xla_patched_nn_linear_forward,
+                           set_global_mesh, get_global_mesh)
 from .api import xla_distribute_tensor, xla_distribute_module
 
 __all__ = [
@@ -18,4 +19,6 @@
     "xla_distribute_tensor",
     "xla_distribute_module",
     "xla_patched_nn_linear_forward",
+    "set_global_mesh",
+    "get_global_mesh",
 ]
diff --git a/torch_xla/distributed/spmd/xla_sharding.py b/torch_xla/distributed/spmd/xla_sharding.py
index 6c7061aeb87..4c5d1cde0c8 100644
--- a/torch_xla/distributed/spmd/xla_sharding.py
+++ b/torch_xla/distributed/spmd/xla_sharding.py
@@ -123,6 +123,19 @@ def get_op_sharding(self,
                                       replication_groups, sharding_type)
 
 
+_GLOBAL_MESH: Mesh = None
+
+
+def set_global_mesh(mesh: Mesh):
+  global _GLOBAL_MESH
+  _GLOBAL_MESH = mesh
+
+
+def get_global_mesh():
+  global _GLOBAL_MESH
+  return _GLOBAL_MESH
+
+
 # HybridDevice class has been inspired from jax's mesh_utils: https://github.com/google/jax/blob/fc5960f2b8b7a0ef74dbae4e27c5c08ff1564cff/jax/experimental/mesh_utils.py#L4ƒ
 class HybridMesh(Mesh):
   """Creates a hybrid device mesh of devices connected with ICI and DCN networks.