diff --git a/CHANGELOG.md b/CHANGELOG.md
index 875685460a..5fe3e6c7f3 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -137,6 +137,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 
 - Renamed the `TrainingTypePlugin` to `Strategy` ([#11120](https://github.com/PyTorchLightning/pytorch-lightning/pull/11120))
+    * Renamed the `ParallelPlugin` to `ParallelStrategy` ([#11123](https://github.com/PyTorchLightning/pytorch-lightning/pull/11123))
     * Renamed the `DataParallelPlugin` to `DataParallelStrategy` ([#11183](https://github.com/PyTorchLightning/pytorch-lightning/pull/11183))
     * Renamed the `DDPPlugin` to `DDPStrategy` ([#11142](https://github.com/PyTorchLightning/pytorch-lightning/pull/11142))
     * Renamed the `DeepSpeedPlugin` to `DeepSpeedStrategy` ([#11194](https://github.com/PyTorchLightning/pytorch-lightning/pull/11194))
@@ -151,7 +152,6 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
     * Renamed the `DDPSpawnShardedPlugin` to `DDPSpawnShardedStrategy` ([#11210](https://github.com/PyTorchLightning/pytorch-lightning/pull/11210))
 
 
-
 - Marked the `ResultCollection`, `ResultMetric`, and `ResultMetricCollection` classes as protected ([#11130](https://github.com/PyTorchLightning/pytorch-lightning/pull/11130))
 
 
diff --git a/docs/source/api_references.rst b/docs/source/api_references.rst
index cf88dad296..f2d2f4e28a 100644
--- a/docs/source/api_references.rst
+++ b/docs/source/api_references.rst
@@ -148,7 +148,7 @@ Training Type Plugins
 
     Strategy
     SingleDeviceStrategy
-    ParallelPlugin
+    ParallelStrategy
     DataParallelStrategy
     DDPStrategy
     DDP2Strategy
diff --git a/docs/source/extensions/plugins.rst b/docs/source/extensions/plugins.rst
index fe10eb7ef5..f51151d63c 100644
--- a/docs/source/extensions/plugins.rst
+++ b/docs/source/extensions/plugins.rst
@@ -107,7 +107,7 @@ Training Type Plugins
 
     Strategy
     SingleDeviceStrategy
-    ParallelPlugin
+    ParallelStrategy
     DataParallelStrategy
     DDPStrategy
     DDP2Strategy
diff --git a/pytorch_lightning/loops/utilities.py b/pytorch_lightning/loops/utilities.py
index dfbccfadcc..656f39711d 100644
--- a/pytorch_lightning/loops/utilities.py
+++ b/pytorch_lightning/loops/utilities.py
@@ -22,7 +22,7 @@ import torch
 from torch.optim import Optimizer
 
 import pytorch_lightning as pl
-from pytorch_lightning.plugins import ParallelPlugin
+from pytorch_lightning.plugins import ParallelStrategy
 from pytorch_lightning.utilities import rank_zero_warn
 from pytorch_lightning.utilities.exceptions import MisconfigurationException
 from pytorch_lightning.utilities.fetching import AbstractDataFetcher, DataLoaderIterDataFetcher
@@ -161,8 +161,8 @@ def _update_dataloader_iter(data_fetcher: AbstractDataFetcher, batch_idx: int) -
 
 @contextmanager
 def _block_parallel_sync_behavior(trainer: "pl.Trainer", block: bool = True) -> Generator[None, None, None]:
-    """Blocks synchronization in :class:`~pytorch_lightning.plugins.training_type.parallel.ParallelPlugin`. This is
-    useful for example when when accumulating gradients to reduce communication when it is not needed.
+    """Blocks synchronization in :class:`~pytorch_lightning.plugins.training_type.parallel.ParallelStrategy`. This
+    is useful for example when when accumulating gradients to reduce communication when it is not needed.
 
     Args:
         trainer: the trainer instance with a reference to a training type plugin
@@ -171,7 +171,7 @@ def _block_parallel_sync_behavior(trainer: "pl.Trainer", block: bool = True) ->
     Returns:
         context manager with sync behaviour off
     """
-    if isinstance(trainer.training_type_plugin, ParallelPlugin) and block:
+    if isinstance(trainer.training_type_plugin, ParallelStrategy) and block:
         with trainer.training_type_plugin.block_backward_sync():
             yield None
     else:
diff --git a/pytorch_lightning/plugins/__init__.py b/pytorch_lightning/plugins/__init__.py
index 3d9a5f33da..a1369883d5 100644
--- a/pytorch_lightning/plugins/__init__.py
+++ b/pytorch_lightning/plugins/__init__.py
@@ -27,7 +27,7 @@ from pytorch_lightning.plugins.training_type.dp import DataParallelStrategy
 from pytorch_lightning.plugins.training_type.fully_sharded import DDPFullyShardedStrategy
 from pytorch_lightning.plugins.training_type.horovod import HorovodStrategy
 from pytorch_lightning.plugins.training_type.ipu import IPUStrategy
-from pytorch_lightning.plugins.training_type.parallel import ParallelPlugin
+from pytorch_lightning.plugins.training_type.parallel import ParallelStrategy
 from pytorch_lightning.plugins.training_type.sharded import DDPShardedStrategy
 from pytorch_lightning.plugins.training_type.sharded_spawn import DDPSpawnShardedStrategy
 from pytorch_lightning.plugins.training_type.single_device import SingleDeviceStrategy
@@ -64,7 +64,7 @@ __all__ = [
     "TPUBf16PrecisionPlugin",
     "TPUSpawnStrategy",
     "Strategy",
-    "ParallelPlugin",
+    "ParallelStrategy",
     "DDPShardedStrategy",
     "DDPSpawnShardedStrategy",
 ]
diff --git a/pytorch_lightning/plugins/training_type/__init__.py b/pytorch_lightning/plugins/training_type/__init__.py
index 81a1de7b7f..95718baf51 100644
--- a/pytorch_lightning/plugins/training_type/__init__.py
+++ b/pytorch_lightning/plugins/training_type/__init__.py
@@ -5,7 +5,7 @@ from pytorch_lightning.plugins.training_type.deepspeed import DeepSpeedStrategy
 from pytorch_lightning.plugins.training_type.dp import DataParallelStrategy  # noqa: F401
 from pytorch_lightning.plugins.training_type.fully_sharded import DDPFullyShardedStrategy  # noqa: F401
 from pytorch_lightning.plugins.training_type.horovod import HorovodStrategy  # noqa: F401
-from pytorch_lightning.plugins.training_type.parallel import ParallelPlugin  # noqa: F401
+from pytorch_lightning.plugins.training_type.parallel import ParallelStrategy  # noqa: F401
 from pytorch_lightning.plugins.training_type.sharded import DDPShardedStrategy  # noqa: F401
 from pytorch_lightning.plugins.training_type.sharded_spawn import DDPSpawnShardedStrategy  # noqa: F401
 from pytorch_lightning.plugins.training_type.single_device import SingleDeviceStrategy  # noqa: F401
diff --git a/pytorch_lightning/plugins/training_type/ddp.py b/pytorch_lightning/plugins/training_type/ddp.py
index 15ca9225e3..8b5d078a2d 100644
--- a/pytorch_lightning/plugins/training_type/ddp.py
+++ b/pytorch_lightning/plugins/training_type/ddp.py
@@ -37,7 +37,7 @@ from pytorch_lightning.overrides.distributed import prepare_for_backward
 from pytorch_lightning.plugins.environments.cluster_environment import ClusterEnvironment
 from pytorch_lightning.plugins.io.checkpoint_plugin import CheckpointIO
 from pytorch_lightning.plugins.precision import PrecisionPlugin
-from pytorch_lightning.plugins.training_type.parallel import ParallelPlugin
+from pytorch_lightning.plugins.training_type.parallel import ParallelStrategy
 from pytorch_lightning.trainer.states import TrainerFn
 from pytorch_lightning.utilities import (
     _FAIRSCALE_AVAILABLE,
@@ -73,7 +73,7 @@ if _TORCH_GREATER_EQUAL_1_8:
 log = logging.getLogger(__name__)
 
 
-class DDPStrategy(ParallelPlugin):
+class DDPStrategy(ParallelStrategy):
     """Plugin for multi-process single-device training on one or multiple nodes.
 
     The main process in each node spawns N-1 child processes via :func:`subprocess.Popen`, where N is the number of
diff --git a/pytorch_lightning/plugins/training_type/ddp_spawn.py b/pytorch_lightning/plugins/training_type/ddp_spawn.py
index 41be1931c2..500bd815c3 100644
--- a/pytorch_lightning/plugins/training_type/ddp_spawn.py
+++ b/pytorch_lightning/plugins/training_type/ddp_spawn.py
@@ -30,7 +30,7 @@ from pytorch_lightning.overrides.distributed import prepare_for_backward
 from pytorch_lightning.plugins.environments.cluster_environment import ClusterEnvironment
 from pytorch_lightning.plugins.io.checkpoint_plugin import CheckpointIO
 from pytorch_lightning.plugins.precision import PrecisionPlugin
-from pytorch_lightning.plugins.training_type.parallel import ParallelPlugin
+from pytorch_lightning.plugins.training_type.parallel import ParallelStrategy
 from pytorch_lightning.trainer.states import TrainerFn, TrainerState
 from pytorch_lightning.utilities import _TORCH_GREATER_EQUAL_1_8, rank_zero_warn
 from pytorch_lightning.utilities.apply_func import apply_to_collection, move_data_to_device
@@ -54,7 +54,7 @@ if _TORCH_GREATER_EQUAL_1_8:
 log = logging.getLogger(__name__)
 
 
-class DDPSpawnStrategy(ParallelPlugin):
+class DDPSpawnStrategy(ParallelStrategy):
     """Spawns processes using the :func:`torch.multiprocessing.spawn` method and joins processes after training
     finishes."""
 
diff --git a/pytorch_lightning/plugins/training_type/dp.py b/pytorch_lightning/plugins/training_type/dp.py
index fdf235f70d..f688d81cfd 100644
--- a/pytorch_lightning/plugins/training_type/dp.py
+++ b/pytorch_lightning/plugins/training_type/dp.py
@@ -20,14 +20,14 @@ import pytorch_lightning as pl
 from pytorch_lightning.overrides.data_parallel import LightningParallelModule
 from pytorch_lightning.plugins.io.checkpoint_plugin import CheckpointIO
 from pytorch_lightning.plugins.precision import PrecisionPlugin
-from pytorch_lightning.plugins.training_type.parallel import ParallelPlugin
+from pytorch_lightning.plugins.training_type.parallel import ParallelStrategy
 from pytorch_lightning.utilities.apply_func import apply_to_collection, move_data_to_device
 from pytorch_lightning.utilities.enums import _StrategyType
 from pytorch_lightning.utilities.model_helpers import is_overridden
 from pytorch_lightning.utilities.types import _METRIC_COLLECTION, STEP_OUTPUT
 
 
-class DataParallelStrategy(ParallelPlugin):
+class DataParallelStrategy(ParallelStrategy):
     """Implements data-parallel training in a single process, i.e., the model gets replicated to each device and
     each gets a split of the data."""
 
diff --git a/pytorch_lightning/plugins/training_type/horovod.py b/pytorch_lightning/plugins/training_type/horovod.py
index 27588d1a4d..2c7973309e 100644
--- a/pytorch_lightning/plugins/training_type/horovod.py
+++ b/pytorch_lightning/plugins/training_type/horovod.py
@@ -23,7 +23,7 @@ import pytorch_lightning as pl
 from pytorch_lightning.core.optimizer import LightningOptimizer
 from pytorch_lightning.plugins.io.checkpoint_plugin import CheckpointIO
 from pytorch_lightning.plugins.precision import PrecisionPlugin
-from pytorch_lightning.plugins.training_type.parallel import ParallelPlugin
+from pytorch_lightning.plugins.training_type.parallel import ParallelStrategy
 from pytorch_lightning.utilities import _HOROVOD_AVAILABLE
 from pytorch_lightning.utilities.distributed import distributed_available
 from pytorch_lightning.utilities.distributed import group as dist_group
@@ -34,7 +34,7 @@ if _HOROVOD_AVAILABLE:
     import horovod.torch as hvd
 
 
-class HorovodStrategy(ParallelPlugin):
+class HorovodStrategy(ParallelStrategy):
     """Plugin for Horovod distributed training integration."""
 
     distributed_backend = _StrategyType.HOROVOD
diff --git a/pytorch_lightning/plugins/training_type/ipu.py b/pytorch_lightning/plugins/training_type/ipu.py
index 1338b1e97e..51cd2edfc9 100644
--- a/pytorch_lightning/plugins/training_type/ipu.py
+++ b/pytorch_lightning/plugins/training_type/ipu.py
@@ -23,7 +23,7 @@ from pytorch_lightning.overrides.base import _LightningModuleWrapperBase
 from pytorch_lightning.plugins.environments.cluster_environment import ClusterEnvironment
 from pytorch_lightning.plugins.io.checkpoint_plugin import CheckpointIO
 from pytorch_lightning.plugins.precision import PrecisionPlugin
-from pytorch_lightning.plugins.training_type.parallel import ParallelPlugin
+from pytorch_lightning.plugins.training_type.parallel import ParallelStrategy
 from pytorch_lightning.trainer.states import RunningStage, TrainerFn
 from pytorch_lightning.utilities import _IPU_AVAILABLE, _POPTORCH_AVAILABLE
 from pytorch_lightning.utilities.apply_func import apply_to_collection
@@ -57,7 +57,7 @@ class LightningIPUModule(_LightningModuleWrapperBase):
         return batch
 
 
-class IPUStrategy(ParallelPlugin):
+class IPUStrategy(ParallelStrategy):
     """Plugin for training on IPU devices."""
 
     def __init__(
diff --git a/pytorch_lightning/plugins/training_type/parallel.py b/pytorch_lightning/plugins/training_type/parallel.py
index 97c4c1a577..472040cf7f 100644
--- a/pytorch_lightning/plugins/training_type/parallel.py
+++ b/pytorch_lightning/plugins/training_type/parallel.py
@@ -29,7 +29,7 @@ from pytorch_lightning.utilities import _XLA_AVAILABLE
 from pytorch_lightning.utilities.distributed import all_gather_ddp_if_available, ReduceOp
 
 
-class ParallelPlugin(Strategy, ABC):
+class ParallelStrategy(Strategy, ABC):
     """Plugin for training with multiple processes in parallel."""
 
     def __init__(
diff --git a/pytorch_lightning/trainer/trainer.py b/pytorch_lightning/trainer/trainer.py
index fd0ebbf681..450590066c 100644
--- a/pytorch_lightning/trainer/trainer.py
+++ b/pytorch_lightning/trainer/trainer.py
@@ -45,7 +45,7 @@ from pytorch_lightning.plugins import (
     ApexMixedPrecisionPlugin,
     DDPSpawnStrategy,
     NativeMixedPrecisionPlugin,
-    ParallelPlugin,
+    ParallelStrategy,
     PLUGIN_INPUT,
     PrecisionPlugin,
     Strategy,
@@ -1927,7 +1927,7 @@ class Trainer(
 
     @property
     def distributed_sampler_kwargs(self) -> Optional[dict]:
-        if isinstance(self.training_type_plugin, ParallelPlugin):
+        if isinstance(self.training_type_plugin, ParallelStrategy):
             return self.training_type_plugin.distributed_sampler_kwargs
 
     @property
diff --git a/tests/accelerators/test_accelerator_connector.py b/tests/accelerators/test_accelerator_connector.py
index 676634b4aa..72d1ac83de 100644
--- a/tests/accelerators/test_accelerator_connector.py
+++ b/tests/accelerators/test_accelerator_connector.py
@@ -32,7 +32,7 @@ from pytorch_lightning.plugins import (
     DDPSpawnStrategy,
     DDPStrategy,
     DeepSpeedStrategy,
-    ParallelPlugin,
+    ParallelStrategy,
     PrecisionPlugin,
     SingleDeviceStrategy,
 )
@@ -427,7 +427,7 @@ def test_plugin_accelerator_choice(accelerator: Optional[str], plugin: str):
 @mock.patch("torch.cuda.device_count", return_value=2)
 @pytest.mark.parametrize("gpus", [1, 2])
 def test_accelerator_choice_multi_node_gpu(
-    mock_is_available, mock_device_count, tmpdir, accelerator: str, plugin: ParallelPlugin, gpus: int
+    mock_is_available, mock_device_count, tmpdir, accelerator: str, plugin: ParallelStrategy, gpus: int
 ):
     with pytest.deprecated_call(match=r"accelerator=.*\)` has been deprecated"):
         trainer = Trainer(accelerator=accelerator, default_root_dir=tmpdir, num_nodes=2, gpus=gpus)
diff --git a/tests/plugins/test_custom_plugin.py b/tests/plugins/test_custom_plugin.py
index 40ebb3502e..bf20f6ac93 100644
--- a/tests/plugins/test_custom_plugin.py
+++ b/tests/plugins/test_custom_plugin.py
@@ -23,7 +23,7 @@ from tests.helpers import BoringModel
 from tests.helpers.runif import RunIf
 
 
-class CustomParallelPlugin(DDPStrategy):
+class CustomParallelStrategy(DDPStrategy):
     def __init__(self, **kwargs):
         super().__init__(**kwargs)
         # Set to None so it will be overwritten by the accelerator connector.
@@ -34,7 +34,7 @@ class CustomParallelPlugin(DDPStrategy):
 def test_sync_batchnorm_set(tmpdir):
     """Tests if sync_batchnorm is automatically set for custom plugin."""
     model = BoringModel()
-    plugin = CustomParallelPlugin()
+    plugin = CustomParallelStrategy()
     assert plugin.sync_batchnorm is None
     trainer = Trainer(max_epochs=1, strategy=plugin, default_root_dir=tmpdir, sync_batchnorm=True)
     trainer.fit(model)