diff --git a/torchtitan/parallelisms/parallelize_llama.py b/torchtitan/parallelisms/parallelize_llama.py
index 634c70a0c3..31eabc6c84 100644
--- a/torchtitan/parallelisms/parallelize_llama.py
+++ b/torchtitan/parallelisms/parallelize_llama.py
@@ -413,13 +413,27 @@ def apply_tp(
             parallelize_plan=layer_plan,
         )
 
+    # updates expressly for async tensor parallel
     if job_config.experimental.enable_async_tensor_parallel:
         from torch.distributed._symmetric_memory import enable_symm_mem_for_group
 
+        torch._dynamo.config.cache_size_limit = 10000
+        logger.info(
+            "Updating torch._dynamo.config.cache_size_limit to 10000 to support Async TP"
+        )
+
         torch._inductor.config._micro_pipeline_tp = True
         enable_symm_mem_for_group(tp_mesh.get_group().group_name)
 
-    logger.info("Applied Tensor Parallelism to the model")
+        if not job_config.training.compile:
+            logger.warning(
+                "Async TP requires compilation...auto enabling compile = True for this job to resolve."
+            )
+            job_config.training.compile = True
+
+    logger.info(
+        f"Applied{' Async ' if job_config.experimental.enable_async_tensor_parallel else ' '}Tensor Parallelism to the model"
+    )
     return model
 
 
diff --git a/train_configs/debug_model.toml b/train_configs/debug_model.toml
index 7c8499767a..b36e9d0c7b 100644
--- a/train_configs/debug_model.toml
+++ b/train_configs/debug_model.toml
@@ -43,6 +43,7 @@ dataset = "c4_mini"  # supported datasets: c4_mini (45K), c4 (177M)
 
 [experimental]
 pipeline_parallel_degree = 1
+enable_async_tensor_parallel = false
 
 [checkpoint]
 enable_checkpoint = false