diff --git a/tests/python/multidevice/conftest.py b/tests/python/multidevice/conftest.py
index 4c67519a622..6dffae8ca16 100644
--- a/tests/python/multidevice/conftest.py
+++ b/tests/python/multidevice/conftest.py
@@ -11,6 +11,7 @@
 
 import torch
 import torch.distributed as dist
+import torch.distributed._symmetric_memory as symm_mem
 
 import nvfuser_direct as nvfuser
 
@@ -133,13 +134,21 @@ def setup_default_process_group():
 
     torch.cuda.set_device(local_rank)
 
-    # The default port as used by https://github.com/pytorch/pytorch/blob/45a8b5682eb69d865cbf68c7f2f689b56b4efd53/torch/csrc/distributed/c10d/TCPStore.hpp#L51.
+    opts = dist.ProcessGroupNCCL.Options()
+    opts.config.cta_policy = dist.ProcessGroupNCCL.NCCL_CTA_POLICY_ZERO
     dist.init_process_group(
         backend="nccl",
+        pg_options=opts,
+        # The default port as used by https://github.com/pytorch/pytorch/blob/45a8b5682eb69d865cbf68c7f2f689b56b4efd53/torch/csrc/distributed/c10d/TCPStore.hpp#L51.
         init_method="tcp://localhost:29500",
         world_size=world_size,
         rank=rank,
-        device_id=torch.device(f"cuda:{local_rank}"),
+        device_id=local_rank,
     )
+
+    symm_mem.set_backend("NCCL")
+    symm_mem.enable_symm_mem_for_group(dist.group.WORLD.group_name)
+
     yield
+
     dist.destroy_process_group()
diff --git a/tests/python/multidevice/test_overlap.py b/tests/python/multidevice/test_overlap.py
index 02fdb1bfa53..a634da471c0 100644
--- a/tests/python/multidevice/test_overlap.py
+++ b/tests/python/multidevice/test_overlap.py
@@ -7,6 +7,7 @@
 
 import torch
 import torch.distributed as dist
+import torch.distributed._symmetric_memory as symm_mem
 from torch.distributed.tensor import distribute_tensor, Shard
 
 import nvfuser_direct as nvfuser
@@ -168,22 +169,17 @@ def get(self, sid: int) -> torch.cuda.Stream:
 def row_parallel_linear_forward_reference(
     inp_shard: torch.Tensor,
     weight_shard: torch.Tensor,
+    out: torch.Tensor,
     num_chunks: int,
     stream_pool: StreamPool,
 ) -> torch.Tensor:
-    out = torch.empty(
-        inp_shard.size(0),
-        weight_shard.size(0),
-        device="cuda",
-        dtype=inp_shard.dtype,
-    )
     inp_chunks = inp_shard.chunk(num_chunks)
     out_chunks = out.chunk(num_chunks)
 
     main_stream = torch.cuda.current_stream()
     worker_streams = []
     for i, (inp_chunk, out_chunk) in enumerate(zip(inp_chunks, out_chunks)):
-        worker_stream = stream_pool.get(i)
+        worker_stream = stream_pool.get(i % 2)
         worker_streams.append(worker_stream)
         worker_stream.wait_stream(main_stream)
         with torch.cuda.stream(worker_stream):
@@ -222,7 +218,15 @@ def test_row_parallel_linear_forward_reference(setup_default_process_group):
         weight_ref, mesh, placements=[Shard(-1)]
     ).to_local()
     stream_pool = StreamPool()
-    out = row_parallel_linear_forward_reference(inp_shard, weight_shard, s, stream_pool)
+
+    out = symm_mem.empty(
+        inp_shard.size(0),
+        weight_shard.size(0),
+        device="cuda",
+        dtype=inp_shard.dtype,
+    )
+    symm_mem.rendezvous(out, group=dist.group.WORLD)
+    row_parallel_linear_forward_reference(inp_shard, weight_shard, out, s, stream_pool)
 
     torch.testing.assert_close(out.cpu(), out_ref)
 
@@ -232,7 +236,7 @@ def test_row_parallel_linear_forward_reference(setup_default_process_group):
 def test_row_parallel_linear_forward_reference_benchmark(
     setup_default_process_group, benchmark
 ):
-    h, s, t = 8192, 2, 8192
+    h, s, t = 8192, 4, 8192
     d = dist.get_world_size()
     if (h * 4) % d != 0:
         pytest.skip(
@@ -251,9 +255,16 @@ def test_row_parallel_linear_forward_reference_benchmark(
     ).to_local()
 
     stream_pool = StreamPool()
+    out = symm_mem.empty(
+        inp_shard.size(0),
+        weight_shard.size(0),
+        device="cuda",
+        dtype=inp_shard.dtype,
+    )
+    symm_mem.rendezvous(out, group=dist.group.WORLD)
     warmup_fn, benchmark_fn = get_benchmark_fns(
         lambda: row_parallel_linear_forward_reference(
-            inp_shard, weight_shard, s, stream_pool
+            inp_shard, weight_shard, out, s, stream_pool
         )
     )
     warmup_fn()