diff --git a/benchmarks/cloudmask/target/greene_v0.5/simple.rivanna.slurm b/benchmarks/cloudmask/target/greene_v0.5/simple.rivanna.slurm
index af671e1c..f3c7fc4a 100644
--- a/benchmarks/cloudmask/target/greene_v0.5/simple.rivanna.slurm
+++ b/benchmarks/cloudmask/target/greene_v0.5/simple.rivanna.slurm
@@ -31,12 +31,12 @@ nvidia-smi
 
 cd $TARGET
 
-# mkdir -p outputs/slstr_cloud
+mkdir -p outputs/slstr_cloud
 
 # sleep 1
 
 cms gpu watch --gpu=0 --delay=0.5 --dense > outputs/gpu0.log &
 
-python slstr_cloud.py --config config_simple.yaml
+python ./slstr_uva_nyu_cloud.py --config config_simple_rivanna.yaml
 
 seff $SLURM_JOB_ID
diff --git a/benchmarks/cloudmask/target/greene_v0.5/slstr_uva_nyu_cloud.py b/benchmarks/cloudmask/target/greene_v0.5/slstr_uva_nyu_cloud.py
index 65d369e4..a533e3bf 100755
--- a/benchmarks/cloudmask/target/greene_v0.5/slstr_uva_nyu_cloud.py
+++ b/benchmarks/cloudmask/target/greene_v0.5/slstr_uva_nyu_cloud.py
@@ -44,7 +44,7 @@
 from mlperf_logging import mllog
 import logging
 from tensorflow.keras.callbacks import EarlyStopping, LearningRateScheduler
-from cloudmesh.common.FlatDict import read_config_parameters
+from cloudmesh.common.FlatDict import FlatDict
 import random
 
 # config = read_config_parameters(filename='config.yaml')
@@ -364,17 +364,29 @@ def main():
                         help='path to config file')
     command_line_args = parser.parse_args()
 
+
     configYamlFile = os.path.expanduser(command_line_args.config)
-    config = read_config_parameters(filename=configYamlFile)
 
-    log_file = os.path.expanduser(config['log_file'])
+    print("Config file:", configYamlFile)
 
-    user_name = config["submission.submitter"]
+    config = FlatDict
+    config.load(content=configYamlFile)
 
+    print (config)
+
+
+    # setup
+    log_file = os.path.expanduser(config['log_file'])
+    user_name = config["submission.submitter"]
 
     # MLCommons logging
     mlperf_logfile = os.path.expanduser(config['mlperf_logfile'])
     mllog.config(filename=mlperf_logfile)
+
+    print("user", user_name)
+    print("log_file", log_file)
+    print ("mllog", mlperf_logfile)
+
     mllogger = mllog.get_mllogger()
     logger = logging.getLogger(__name__)