Update 3 files

- /scripts/benchmark_multi_node.sbatch
- /scripts/benchmark_sbatch_submit.sh
- /README.md

README.md

-# Benchmark of nnU-Net for PyTorch on Berzelius  
-
+# Berzelius nnU-Net Benchmark   
 
 The benchmarking is based on [Nvidia NGC nnU-net for Pytorch](https://catalog.ngc.nvidia.com/orgs/nvidia/resources/nnunet_for_pytorch) v21.11.0.  
 
@@ -27,8 +26,9 @@ docker push xuagu37/nvidia_nnu-net_for_pytorch:21.11.0
 
 - Create directories
 ```
-mkdir -p /proj/nsc_testing/xuan/nnUnet_benchmark
-cd /proj/nsc_testing/xuan/nnUnet_benchmark
+cd /proj/nsc_testing/xuan
+git clone https://gitlab.liu.se/xuagu37/Berzelius-nnU-Net-Benchmark.git
+cd Berzelius-nnU-Net-Benchmark
 mkdir data results
 ```
 <!-- - Clone the repository  
@@ -77,14 +77,13 @@ Exit the image.
 
 - For benchmarking purpose, we use 1000 copied of a single image 
 ```
-bash copy_data_for_benchmark.sh
+bash srtips/copy_data_for_benchmark.sh
 ```
 - Run the script.   
 You need to modify the script for e.g. the name of your reservation, number of nodes, batch_size, etc. Also, choose either singularity or enroot.
 ```
-cd /proj/nsc/xuan/ngc/DeepLearningExamples/PyTorch/Segmentation/nnUNet
 mkdir sbatch_out
-bash benchmark_sbatch_submit.sh
+bash srtips/benchmark_sbatch_submit.sh
 ```
 
 ### Results  

scripts/benchmark_multi_node.sbatch

@@ -14,7 +14,7 @@ srun singularity exec --nv -B ${PWD}/data:/data -B ${PWD}/results:/results nvidi
 #rm -f results/benchmark_dim${1}_nodes${2}_gpus${3}_batchsize${4}_amp_iteration${5}.json
 #srun singularity exec --nv -B ${PWD}/data:/data -B ${PWD}/results:/results nvidia_nnu-net_for_pytorch.sif bash -c "cd /workspace/nnunet_pyt && python scripts/benchmark.py --mode train --gpus ${3} --dim ${1} --batch_size ${4} --nodes ${2} --amp --logname="benchmark_dim${1}_nodes${2}_gpus${3}_batchsize${4}_amp_iteration${5}.json"" 
 
-############## Running srun enroot ... stopped working at 20220220
+############## Running srun enroot ... stopped working at 20230220
 # For enroot 
 #rm -f results/benchmark_dim${1}_nodes${2}_gpus${3}_batchsize${4}_tf32_iteration${5}.json
 #srun enroot start --rw --mount ${PWD}/data:/data --mount ${PWD}/results:/results nnunet bash -c "cd /workspace/nnunet_pyt && python scripts/benchmark.py --mode train --gpus ${3} --dim ${1} --batch_size ${4} --nodes ${2} --logname="benchmark_dim${1}_nodes${2}_gpus${3}_batchsize${4}_tf32_iteration${5}.json""  

scripts/benchmark_sbatch_submit.sh

 cd /proj/nsc/users/xuan/ngc/DeepLearningExamples/PyTorch/Segmentation/nnUNet
 
 dim=2
+
 nodes=1
+for gpus in {1..8}; do
+    for batch_size in 128; do
+        for iteration in {1..100}; do  
 
-for gpus in 8; do
+            echo dim ${dim}, nodes ${nodes}, gpus ${gpus}, batch_size ${batch_size}, iteration ${iteration}
+	          # For single node
+            sbatch -o sbatch_out/benchmark_dim${dim}_nodes${nodes}_gpus${gpus}_batchsize${batch_size}_iteration${iteration}.out benchmark_single_node.sbatch ${dim} ${nodes} ${gpus} ${batch_size} ${iteration}     
 
-    for batch_size in 256; do
+            sleep 1 # pause to be kind to the scheduler
 
-        for iteration in {1..10}; do
-        
-            echo dim ${dim}, nodes ${nodes}, gpus ${gpus}, batch_size ${batch_size}, iteration ${iteration}
+        done
+    done
+done
+
+for nodes in {2..8}
+for gpus in {8}; do
+    for batch_size in 128; do
+        for iteration in {1..100}; do  
 
+            echo dim ${dim}, nodes ${nodes}, gpus ${gpus}, batch_size ${batch_size}, iteration ${iteration}
 	          # For single node
             sbatch -o sbatch_out/benchmark_dim${dim}_nodes${nodes}_gpus${gpus}_batchsize${batch_size}_iteration${iteration}.out benchmark_single_node.sbatch ${dim} ${nodes} ${gpus} ${batch_size} ${iteration}
             
@@ -20,7 +32,6 @@ for gpus in 8; do
             sleep 1 # pause to be kind to the scheduler
 
         done
-
     done
-
 done
+done
\ No newline at end of file