diff --git a/PyTorch/Segmentation/nnUNet/generate_benchmark_jobs.sh b/PyTorch/Segmentation/nnUNet/generate_benchmark_jobs.sh
index 159d4bcf73041311107ebc75c9272c3e77208f3a..d9db6da5eca1208ccf690a4db435c281ead9e952 100644
--- a/PyTorch/Segmentation/nnUNet/generate_benchmark_jobs.sh
+++ b/PyTorch/Segmentation/nnUNet/generate_benchmark_jobs.sh
@@ -4,9 +4,9 @@ MODULE_NAME=nnunet_for_pytorch
 MODULE_VERSION=21.11.0
 WORK_DIR=/proj/nsc_testing/xuan/berzelius-benchmarks/PyTorch/Segmentation/nnUNet
 CONTAINER_DIR=/proj/nsc_testing/xuan/containers/${MODULE_NAME}_${MODULE_VERSION}.sif
-SBATCH_DIR=$WORK_DIR/sbatch_scripts/benchmark_${5}_dim${1}_nodes${2}_gpus${3}_batchsize${4}_fat.sbatch
-SBATCH_OUT_DIR=$WORK_DIR/sbatch_out/benchmark_${5}_dim${1}_nodes${2}_gpus${3}_batchsize${4}_fat.out
-LOG_DIR=benchmark_${5}_dim${1}_nodes${2}_gpus${3}_batchsize${4}_amp_fat.json
+SBATCH_DIR=$WORK_DIR/sbatch_scripts/benchmark_${6}_${5}_dim${1}_nodes${2}_gpus${3}_batchsize${4}.sbatch
+SBATCH_OUT_DIR=$WORK_DIR/sbatch_out/benchmark_${6}_${5}_dim${1}_nodes${2}_gpus${3}_batchsize${4}.out
+LOG_DIR=benchmark_${6}_${5}_dim${1}_nodes${2}_gpus${3}_batchsize${4}_amp.json
 mkdir -p $WORK_DIR/sbatch_out $WORK_DIR/sbatch_scripts
 
 cat <<EOT >  $SBATCH_DIR
@@ -17,10 +17,23 @@ cat <<EOT >  $SBATCH_DIR
 #SBATCH --gpus=${3}
 #SBATCH --time=0-0:10:00
 #SBATCH --output=$SBATCH_OUT_DIR
-##SBATCH --reservation=devel
-#SBATCH -C "fat"
+
+EOT
+
+if [ ${6} == "thin" ]; then
+    cat <<EOT >>  $SBATCH_DIR
+    #SBATCH --reservation=devel
+    EOT
+
+else
+    cat <<EOT >>  $SBATCH_DIR
+    #SBATCH -C "fat"
+    EOT
+fi
+
+cat <<EOT >>  $SBATCH_DIR
 
 rm -f $WORK_DIR/results/$LOG_DIR
 apptainer exec --nv -B ${WORK_DIR}/data:/data -B ${WORK_DIR}/results:/results --pwd /workspace/nnunet_pyt $CONTAINER_DIR python scripts/benchmark.py --mode ${5} --gpus ${3} --dim ${1} --batch_size ${4} --amp --logname='$LOG_DIR'
 
-EOT
\ No newline at end of file
+EOT
diff --git a/PyTorch/Segmentation/nnUNet/submit_benchmark_jobs.sh b/PyTorch/Segmentation/nnUNet/submit_benchmark_jobs.sh
index 52874a62bf6acaf26698311ac0556cb3468fce83..4ea31f2dbebf3ee094ed73157dfb633d8cf3e715 100644
--- a/PyTorch/Segmentation/nnUNet/submit_benchmark_jobs.sh
+++ b/PyTorch/Segmentation/nnUNet/submit_benchmark_jobs.sh
@@ -3,20 +3,23 @@ set -e
 
 WORK_DIR=/proj/nsc_testing/xuan/berzelius-benchmarks/PyTorch/Segmentation/nnUNet
 benchmark_modes=("train" "predict")
+node_types=("thin" "fat")
 
 dim=2
 for nodes in {1..1}; do
     for gpus in {1,8}; do
         for batch_size in 256; do
             for benchmark_mode in "${benchmark_modes[@]}"; do
+                for node_type in "${node_types[@]}"; do
+        
 
-                echo dim ${dim}, nodes ${nodes}, gpus ${gpus}, batch_size ${batch_size}, benchmark_mode ${benchmark_mode}
+                    echo dim ${dim}, nodes ${nodes}, gpus ${gpus}, batch_size ${batch_size}, benchmark_mode ${benchmark_mode}, node_type ${node_type}
 
-                # For single node
-                bash $WORK_DIR/generate_benchmark_jobs.sh ${dim} ${nodes} ${gpus} ${batch_size} ${benchmark_mode}
-                SBATCH_DIR=$WORK_DIR/sbatch_scripts/benchmark_${benchmark_mode}_dim${dim}_nodes${nodes}_gpus${gpus}_batchsize${batch_size}.sbatch
-                sbatch $SBATCH_DIR
-                sleep 1 
+                    # For single node
+                    bash $WORK_DIR/generate_benchmark_jobs.sh ${dim} ${nodes} ${gpus} ${batch_size} ${benchmark_mode}
+                    SBATCH_DIR=$WORK_DIR/sbatch_scripts/benchmark_${node_type}_${benchmark_mode}_dim${dim}_nodes${nodes}_gpus${gpus}_batchsize${batch_size}.sbatch
+                    #sbatch $SBATCH_DIR
+                    sleep 1 
                 
             done
         done