diff --git a/paddle/fluid/operators/fused/fused_attention_op.cu b/paddle/fluid/operators/fused/fused_attention_op.cu
index 059d94031ac8e59b678577ac7b177d5020a08187..5ff01e0bc18cc4308c3cb2c31159adaf61203c5a 100644
--- a/paddle/fluid/operators/fused/fused_attention_op.cu
+++ b/paddle/fluid/operators/fused/fused_attention_op.cu
@@ -30,7 +30,7 @@ limitations under the License. */
 #include "paddle/phi/kernels/funcs/math_function.h"
 
 #if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
-#include "paddle/fluid/distributed/collective/ProcessGroup.h"
+#include "paddle/fluid/distributed/collective/ProcessGroupNCCL.h"
 #include "paddle/fluid/platform/collective_helper.h"
 #include "paddle/fluid/platform/device/gpu/nccl_helper.h"
 #endif
@@ -50,13 +50,15 @@ static void AllReduce(framework::Tensor &tensor,  // NOLINT
 
   if (map->has(ring_id)) {
     paddle::distributed::ProcessGroup *pg = map->get(ring_id);
+    auto pg_nccl = static_cast<distributed::ProcessGroupNCCL *>(pg);
+
     std::vector<phi::DenseTensor> in_tensor;
     std::vector<phi::DenseTensor> out_tensor;
     in_tensor.push_back(tensor);
     out_tensor.push_back(tensor);
     paddle::distributed::AllreduceOptions opts;
     opts.reduce_op = distributed::ReduceOp::SUM;
-    auto task = pg->AllReduce(in_tensor, out_tensor, opts);
+    auto task = pg_nccl->AllReduce(in_tensor, out_tensor, opts, true, true);
     task->Wait();
   } else {
     auto dtype = platform::ToNCCLDataType(
diff --git a/paddle/fluid/operators/fused/fused_feedforward_op.cu b/paddle/fluid/operators/fused/fused_feedforward_op.cu
index 33d1e89bf28fe2a2059cdfcdac17e31f3163fb8b..95f13806562f2aa424a83bb5a01dcf2f7cdb2354 100644
--- a/paddle/fluid/operators/fused/fused_feedforward_op.cu
+++ b/paddle/fluid/operators/fused/fused_feedforward_op.cu
@@ -23,7 +23,7 @@ limitations under the License. */
 #include "paddle/phi/kernels/funcs/elementwise_functor.h"
 
 #if defined(PADDLE_WITH_NCCL) || defined(PADDLE_WITH_RCCL)
-#include "paddle/fluid/distributed/collective/ProcessGroup.h"
+#include "paddle/fluid/distributed/collective/ProcessGroupNCCL.h"
 #include "paddle/fluid/platform/collective_helper.h"
 #include "paddle/fluid/platform/device/gpu/nccl_helper.h"
 #endif
@@ -43,13 +43,15 @@ static void AllReduce(framework::Tensor& tensor,  // NOLINT
 
   if (map->has(ring_id)) {
     paddle::distributed::ProcessGroup* pg = map->get(ring_id);
+    auto pg_nccl = static_cast<distributed::ProcessGroupNCCL*>(pg);
+
     std::vector<phi::DenseTensor> in_tensor;
     std::vector<phi::DenseTensor> out_tensor;
     in_tensor.push_back(tensor);
     out_tensor.push_back(tensor);
     paddle::distributed::AllreduceOptions opts;
     opts.reduce_op = distributed::ReduceOp::SUM;
-    auto task = pg->AllReduce(in_tensor, out_tensor, opts);
+    auto task = pg_nccl->AllReduce(in_tensor, out_tensor, opts, true, true);
     task->Wait();
   } else {
     auto dtype = platform::ToNCCLDataType(
diff --git a/python/paddle/distributed/fleet/layers/mpu/mp_ops.py b/python/paddle/distributed/fleet/layers/mpu/mp_ops.py
index a2f3bde6cfc648b0fea433c1a367b9abef38bd06..18e7b6617783e295070886852c75390e0eb4d339 100644
--- a/python/paddle/distributed/fleet/layers/mpu/mp_ops.py
+++ b/python/paddle/distributed/fleet/layers/mpu/mp_ops.py
@@ -43,7 +43,26 @@ def _c_identity(tensor, group=None):
         return
     ring_id = 0 if group is None else group.id
 
-    if _non_static_mode():
+    if in_dygraph_mode():
+        from paddle.autograd import PyLayer
+
+        class c_identity_eager(PyLayer):
+
+            @staticmethod
+            def forward(ctx, tensor):
+                return _legacy_C_ops.c_identity(tensor, 'use_calc_stream', True,
+                                                'ring_id', group.id,
+                                                'use_model_parallel', True)
+
+            @staticmethod
+            def backward(ctx, dy):
+                op_type = collective._get_reduce_op(ReduceOp.SUM, "_c_identity")
+                group.process_group.allreduce_on_calc_stream(dy, op_type)
+                return dy
+
+        return c_identity_eager.apply(tensor)
+
+    elif _in_legacy_dygraph():
         return _legacy_C_ops.c_identity(tensor, 'use_calc_stream', True,
                                         'ring_id', ring_id,
                                         'use_model_parallel', True)
diff --git a/python/paddle/distributed/fleet/meta_parallel/pp_utils/p2p_communication.py b/python/paddle/distributed/fleet/meta_parallel/pp_utils/p2p_communication.py
index e2ca6f8d2a034c4f036bdfee35c87b2cfad5312e..c1cf0527e1b2b25062549bab485acda13da9bd2c 100644
--- a/python/paddle/distributed/fleet/meta_parallel/pp_utils/p2p_communication.py
+++ b/python/paddle/distributed/fleet/meta_parallel/pp_utils/p2p_communication.py
@@ -173,7 +173,9 @@ def _partial_send_op(tensor, group, use_calc_stream, ring_id, dst, nranks,
     elif in_dygraph_mode():
         group = paddle.distributed.collective._get_default_group(
         ) if group is None else group
-        return group.process_group.send_partial(tensor, dst, nranks, rank_id)
+        comm_op = group.process_group.send_partial_on_calc_stream \
+            if use_calc_stream else group.process_group.send_partial
+        return comm_op(tensor, dst, nranks, rank_id)
 
 
 def send_partial(tensor,
@@ -212,12 +214,9 @@ def _partial_recv_op(tensor, group, use_calc_stream, ring_id, src, nranks,
     elif in_dygraph_mode():
         group = paddle.distributed.collective._get_default_group(
         ) if group is None else group
-        task = group.process_group.recv_partial(tensor, src, nranks, rank_id)
-        if use_calc_stream:
-            task.wait()
-            return None
-        else:
-            return task
+        comm_op = group.process_group.recv_partial_on_calc_stream \
+            if use_calc_stream else group.process_group.recv_partial
+        return comm_op(tensor, src, nranks, rank_id)
 
 
 def recv_partial(tensor,
@@ -255,13 +254,9 @@ def _partial_allgather_op(tensor, group, use_calc_stream, ring_id, nranks,
     elif in_dygraph_mode():
         group = paddle.distributed.collective._get_default_group(
         ) if group is None else group
-        task = group.process_group.all_gather_partial(tensor, tensor, nranks,
-                                                      rank_id)
-        if use_calc_stream:
-            task.wait()
-            return None
-        else:
-            return task
+        comm_op = group.process_group.all_gather_partial_on_calc_stream \
+            if use_calc_stream else group.process_group.all_gather_partial
+        return comm_op(tensor, tensor, nranks, rank_id)
 
 
 def allgather_partial(tensor,