diff --git a/codalab/worker/docker_utils.py b/codalab/worker/docker_utils.py
index e21dfb5eb..61293e063 100644
--- a/codalab/worker/docker_utils.py
+++ b/codalab/worker/docker_utils.py
@@ -152,7 +152,11 @@ def get_nvidia_devices(self, use_docker=True):
             docker.errors.ImageNotFound if the CUDA image cannot be pulled
             docker.errors.APIError if another server error occurs
         """
-        cuda_image = 'sulfurheron/nvidia-cuda:9.0-cudnn7-devel-ubuntu16.04-2018-06-08'
+
+        # Note: Do NOT update the NVIDIA image to use a CUDA version higher than
+        # that supported by the NLP machines. Otherwise, Slurm Batch Worker
+        # Manager will no longer function.
+        cuda_image = 'nvidia/cuda:11.5.2-base-ubuntu20.04'
         nvidia_command = 'nvidia-smi --query-gpu=index,uuid --format=csv,noheader'
         if use_docker:
             self.client.images.pull(cuda_image)
diff --git a/codalab/worker/main.py b/codalab/worker/main.py
index ef98f0c9e..35b1f76f8 100644
--- a/codalab/worker/main.py
+++ b/codalab/worker/main.py
@@ -453,13 +453,17 @@ def parse_gpuset_args(arg):
 
     try:
         all_gpus = DockerRuntime().get_nvidia_devices()  # Dict[GPU index: GPU UUID]
-    except DockerException:
+    except DockerException as e:
+        logger.error(e)
+        logger.error("Setting all_gpus to be empty...")
         all_gpus = {}
     # Docker socket can't be used
     except requests.exceptions.ConnectionError:
         try:
             all_gpus = DockerRuntime().get_nvidia_devices(use_docker=False)
-        except SingularityError:
+        except SingularityError as e:
+            logger.error(e)
+            logger.error("Setting all_gpus to be empty...")
             all_gpus = {}
 
     if arg == 'ALL':