diff --git a/distributed/comm/ucx.py b/distributed/comm/ucx.py
index fc187dcc614..a29441ec4d5 100644
--- a/distributed/comm/ucx.py
+++ b/distributed/comm/ucx.py
@@ -156,6 +156,9 @@ async def write(
                 frames = await to_frames(
                     msg, serializers=serializers, on_error=on_error
                 )
+                send_frames = [
+                    each_frame for each_frame in frames if len(each_frame) > 0
+                ]
 
                 # Send meta data
                 cuda_frames = np.array(
@@ -167,6 +170,7 @@ async def write(
                 await self.ep.send(
                     np.array([nbytes(f) for f in frames], dtype=np.uint64)
                 )
+
                 # Send frames
 
                 # It is necessary to first synchronize the default stream before start sending
@@ -177,10 +181,9 @@ async def write(
                 if cuda_frames.any():
                     synchronize_stream(0)
 
-                for frame in frames:
-                    if nbytes(frame) > 0:
-                        await self.ep.send(frame)
-                return sum(map(nbytes, frames))
+                for each_frame in send_frames:
+                    await self.ep.send(each_frame)
+                return sum(map(nbytes, send_frames))
             except (ucp.exceptions.UCXBaseException):
                 self.abort()
                 raise CommClosedError("While writing, the connection was closed")
@@ -206,30 +209,23 @@ async def read(self, deserializers=("cuda", "dask", "pickle", "error")):
                 raise CommClosedError("While reading, the connection was closed")
             else:
                 # Recv frames
-                frames = []
-                for is_cuda, size in zip(is_cudas.tolist(), sizes.tolist()):
-                    if size > 0:
-                        if is_cuda:
-                            frame = cuda_array(size)
-                        else:
-                            frame = np.empty(size, dtype=np.uint8)
-                        frames.append(frame)
-                    else:
-                        if is_cuda:
-                            frames.append(cuda_array(size))
-                        else:
-                            frames.append(b"")
+                frames = [
+                    cuda_array(each_size)
+                    if is_cuda
+                    else np.empty(each_size, dtype=np.uint8)
+                    for is_cuda, each_size in zip(is_cudas.tolist(), sizes.tolist())
+                ]
+                recv_frames = [
+                    each_frame for each_frame in frames if len(each_frame) > 0
+                ]
 
                 # It is necessary to first populate `frames` with CUDA arrays and synchronize
                 # the default stream before starting receiving to ensure buffers have been allocated
                 if is_cudas.any():
                     synchronize_stream(0)
-                for i, (is_cuda, size) in enumerate(
-                    zip(is_cudas.tolist(), sizes.tolist())
-                ):
-                    if size > 0:
-                        await self.ep.recv(frames[i])
 
+                for each_frame in recv_frames:
+                    await self.ep.recv(each_frame)
                 msg = await from_frames(
                     frames, deserialize=self.deserialize, deserializers=deserializers
                 )