hokeun · hokeun · Jun 12, 2024 · Jun 12, 2024 · Jun 13, 2024 · Jun 13, 2024
diff --git a/examples/app-pytorch/README.md b/examples/app-pytorch/README.md
@@ -73,3 +73,42 @@ Or, to try the custom server function example, run:
 ```bash
 flower-server-app server_custom:app --insecure
 ```
+
+## More customized commands for WPES paper experiments
+```bash
+HOKEUN_FLWR_NUM_ROUNDS=7 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 2'
+```
+
+To disable noise, assign 0 to `HOKEUN_FLWR_NOISE_ENABLED`:
+```bash
+HOKEUN_FLWR_NUM_ROUNDS=5 HOKEUN_FLWR_NOISE_ENABLED=0 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=0.1 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 3'
+```
+
+Example command with Gaussian noise:
+```bash
+HOKEUN_FLWR_NUM_ROUNDS=5 HOKEUN_FLWR_NOISE_ENABLED=1 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=0.1 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 3'
+```
+
+## Using shell script
+
+IMPORTANT! You must run `poetry shell` before running the shell script. For example:
+
+```bash
+poetry shell
+./run_experiments.sh &
+exit
+```
+
+After starting the script background using `%`, you can first `exit` to exit from poetry and check if the script still runs.
+
+## Killing experiments script running in the background
+
+Check out this page: [Killing a shell script running in background](https://unix.stackexchange.com/questions/174028/killing-a-shell-script-running-in-background).
+
+Find the process ID of the script like this:
+
+```
+ps -aux | grep run_experiments*
+```
+
+Then, kill the process.
diff --git a/...imental_results/2024_06_19_080607/2024_06_19_080607_results_50_R_10_C_0_NOISE_0_TRIAL.txt b/...imental_results/2024_06_19_080607/2024_06_19_080607_results_50_R_10_C_0_NOISE_0_TRIAL.txt
diff --git a/...imental_results/2024_06_19_080607/2024_06_19_080607_results_50_R_10_C_0_NOISE_1_TRIAL.txt b/...imental_results/2024_06_19_080607/2024_06_19_080607_results_50_R_10_C_0_NOISE_1_TRIAL.txt
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diff --git a/...ntal_results/2024_06_22_151514/2024_06_22_151514_results_50_R_20_C_0.02_NOISE_0_TRIAL.txt b/...ntal_results/2024_06_22_151514/2024_06_22_151514_results_50_R_20_C_0.02_NOISE_0_TRIAL.txt
diff --git a/...ntal_results/2024_06_22_151514/2024_06_22_151514_results_50_R_20_C_0.02_NOISE_1_TRIAL.txt b/...ntal_results/2024_06_22_151514/2024_06_22_151514_results_50_R_20_C_0.02_NOISE_1_TRIAL.txt
diff --git a/...ntal_results/2024_06_22_151514/2024_06_22_151514_results_50_R_20_C_0.02_NOISE_2_TRIAL.txt b/...ntal_results/2024_06_22_151514/2024_06_22_151514_results_50_R_20_C_0.02_NOISE_2_TRIAL.txt
diff --git a/...ntal_results/2024_06_22_151514/2024_06_22_151514_results_50_R_20_C_0.02_NOISE_3_TRIAL.txt b/...ntal_results/2024_06_22_151514/2024_06_22_151514_results_50_R_20_C_0.02_NOISE_3_TRIAL.txt
diff --git a/...ntal_results/2024_06_22_151514/2024_06_22_151514_results_50_R_20_C_0.02_NOISE_4_TRIAL.txt b/...ntal_results/2024_06_22_151514/2024_06_22_151514_results_50_R_20_C_0.02_NOISE_4_TRIAL.txt
diff --git a/...ental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_20_C_0.2_NOISE_0_TRIAL.txt b/...ental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_20_C_0.2_NOISE_0_TRIAL.txt
diff --git a/...ental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_20_C_0.2_NOISE_1_TRIAL.txt b/...ental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_20_C_0.2_NOISE_1_TRIAL.txt
diff --git a/...ental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_20_C_0.2_NOISE_2_TRIAL.txt b/...ental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_20_C_0.2_NOISE_2_TRIAL.txt
diff --git a/...ental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_20_C_0.2_NOISE_3_TRIAL.txt b/...ental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_20_C_0.2_NOISE_3_TRIAL.txt
diff --git a/...ental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_20_C_0.2_NOISE_4_TRIAL.txt b/...ental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_20_C_0.2_NOISE_4_TRIAL.txt
diff --git a/...ental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_5_C_0.02_NOISE_0_TRIAL.txt b/...ental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_5_C_0.02_NOISE_0_TRIAL.txt
diff --git a/...ental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_5_C_0.02_NOISE_1_TRIAL.txt b/...ental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_5_C_0.02_NOISE_1_TRIAL.txt
diff --git a/...ental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_5_C_0.02_NOISE_2_TRIAL.txt b/...ental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_5_C_0.02_NOISE_2_TRIAL.txt
diff --git a/...ental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_5_C_0.02_NOISE_3_TRIAL.txt b/...ental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_5_C_0.02_NOISE_3_TRIAL.txt
diff --git a/...ental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_5_C_0.02_NOISE_4_TRIAL.txt b/...ental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_5_C_0.02_NOISE_4_TRIAL.txt
diff --git a/...mental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_5_C_0.2_NOISE_0_TRIAL.txt b/...mental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_5_C_0.2_NOISE_0_TRIAL.txt
diff --git a/...mental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_5_C_0.2_NOISE_1_TRIAL.txt b/...mental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_5_C_0.2_NOISE_1_TRIAL.txt
diff --git a/...mental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_5_C_0.2_NOISE_2_TRIAL.txt b/...mental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_5_C_0.2_NOISE_2_TRIAL.txt
diff --git a/...mental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_5_C_0.2_NOISE_3_TRIAL.txt b/...mental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_5_C_0.2_NOISE_3_TRIAL.txt
diff --git a/...mental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_5_C_0.2_NOISE_4_TRIAL.txt b/...mental_results/2024_06_22_151514/2024_06_22_151514_results_50_R_5_C_0.2_NOISE_4_TRIAL.txt
diff --git a/...rimental_results/old/2024_06_14_142018/2024_06_14_142018_results_20_R_10_C_0.01_NOISE.txt b/...rimental_results/old/2024_06_14_142018/2024_06_14_142018_results_20_R_10_C_0.01_NOISE.txt
diff --git a/...rimental_results/old/2024_06_14_142018/2024_06_14_142018_results_20_R_10_C_0.05_NOISE.txt b/...rimental_results/old/2024_06_14_142018/2024_06_14_142018_results_20_R_10_C_0.05_NOISE.txt
diff --git a/...erimental_results/old/2024_06_14_142018/2024_06_14_142018_results_20_R_10_C_0.1_NOISE.txt b/...erimental_results/old/2024_06_14_142018/2024_06_14_142018_results_20_R_10_C_0.1_NOISE.txt
diff --git a/...erimental_results/old/2024_06_14_142018/2024_06_14_142018_results_20_R_10_C_0.5_NOISE.txt b/...erimental_results/old/2024_06_14_142018/2024_06_14_142018_results_20_R_10_C_0.5_NOISE.txt
diff --git a/...xperimental_results/old/2024_06_14_142018/2024_06_14_142018_results_20_R_10_C_0_NOISE.txt b/...xperimental_results/old/2024_06_14_142018/2024_06_14_142018_results_20_R_10_C_0_NOISE.txt
diff --git a/...erimental_results/old/2024_06_14_142018/2024_06_14_142018_results_20_R_10_C_1.0_NOISE.txt b/...erimental_results/old/2024_06_14_142018/2024_06_14_142018_results_20_R_10_C_1.0_NOISE.txt
diff --git a/...erimental_results/old/2024_06_14_142018/2024_06_14_142018_results_20_R_5_C_0.01_NOISE.txt b/...erimental_results/old/2024_06_14_142018/2024_06_14_142018_results_20_R_5_C_0.01_NOISE.txt
diff --git a/...erimental_results/old/2024_06_14_142018/2024_06_14_142018_results_20_R_5_C_0.05_NOISE.txt b/...erimental_results/old/2024_06_14_142018/2024_06_14_142018_results_20_R_5_C_0.05_NOISE.txt
diff --git a/...perimental_results/old/2024_06_14_142018/2024_06_14_142018_results_20_R_5_C_0.1_NOISE.txt b/...perimental_results/old/2024_06_14_142018/2024_06_14_142018_results_20_R_5_C_0.1_NOISE.txt
diff --git a/...perimental_results/old/2024_06_14_142018/2024_06_14_142018_results_20_R_5_C_0.5_NOISE.txt b/...perimental_results/old/2024_06_14_142018/2024_06_14_142018_results_20_R_5_C_0.5_NOISE.txt
diff --git a/...experimental_results/old/2024_06_14_142018/2024_06_14_142018_results_20_R_5_C_0_NOISE.txt b/...experimental_results/old/2024_06_14_142018/2024_06_14_142018_results_20_R_5_C_0_NOISE.txt
diff --git a/...perimental_results/old/2024_06_14_142018/2024_06_14_142018_results_20_R_5_C_1.0_NOISE.txt b/...perimental_results/old/2024_06_14_142018/2024_06_14_142018_results_20_R_5_C_1.0_NOISE.txt
diff --git a/...rimental_results/old/2024_06_18_160352/2024_06_18_160352_results_20_R_10_C_0.01_NOISE.txt b/...rimental_results/old/2024_06_18_160352/2024_06_18_160352_results_20_R_10_C_0.01_NOISE.txt
diff --git a/...rimental_results/old/2024_06_18_160352/2024_06_18_160352_results_20_R_10_C_0.05_NOISE.txt b/...rimental_results/old/2024_06_18_160352/2024_06_18_160352_results_20_R_10_C_0.05_NOISE.txt
diff --git a/...erimental_results/old/2024_06_18_160352/2024_06_18_160352_results_20_R_10_C_0.1_NOISE.txt b/...erimental_results/old/2024_06_18_160352/2024_06_18_160352_results_20_R_10_C_0.1_NOISE.txt
diff --git a/...erimental_results/old/2024_06_18_160352/2024_06_18_160352_results_20_R_10_C_0.5_NOISE.txt b/...erimental_results/old/2024_06_18_160352/2024_06_18_160352_results_20_R_10_C_0.5_NOISE.txt
diff --git a/...xperimental_results/old/2024_06_18_160352/2024_06_18_160352_results_20_R_10_C_0_NOISE.txt b/...xperimental_results/old/2024_06_18_160352/2024_06_18_160352_results_20_R_10_C_0_NOISE.txt
diff --git a/...erimental_results/old/2024_06_18_160352/2024_06_18_160352_results_20_R_10_C_1.0_NOISE.txt b/...erimental_results/old/2024_06_18_160352/2024_06_18_160352_results_20_R_10_C_1.0_NOISE.txt
diff --git a/...erimental_results/old/2024_06_18_160352/2024_06_18_160352_results_20_R_5_C_0.01_NOISE.txt b/...erimental_results/old/2024_06_18_160352/2024_06_18_160352_results_20_R_5_C_0.01_NOISE.txt
diff --git a/...erimental_results/old/2024_06_18_160352/2024_06_18_160352_results_20_R_5_C_0.05_NOISE.txt b/...erimental_results/old/2024_06_18_160352/2024_06_18_160352_results_20_R_5_C_0.05_NOISE.txt
diff --git a/...perimental_results/old/2024_06_18_160352/2024_06_18_160352_results_20_R_5_C_0.1_NOISE.txt b/...perimental_results/old/2024_06_18_160352/2024_06_18_160352_results_20_R_5_C_0.1_NOISE.txt
diff --git a/...perimental_results/old/2024_06_18_160352/2024_06_18_160352_results_20_R_5_C_0.5_NOISE.txt b/...perimental_results/old/2024_06_18_160352/2024_06_18_160352_results_20_R_5_C_0.5_NOISE.txt
diff --git a/...experimental_results/old/2024_06_18_160352/2024_06_18_160352_results_20_R_5_C_0_NOISE.txt b/...experimental_results/old/2024_06_18_160352/2024_06_18_160352_results_20_R_5_C_0_NOISE.txt
diff --git a/...perimental_results/old/2024_06_18_160352/2024_06_18_160352_results_20_R_5_C_1.0_NOISE.txt b/...perimental_results/old/2024_06_18_160352/2024_06_18_160352_results_20_R_5_C_1.0_NOISE.txt
diff --git a/...rimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_10_C_0.01_NOISE.txt b/...rimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_10_C_0.01_NOISE.txt
diff --git a/...rimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_10_C_0.05_NOISE.txt b/...rimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_10_C_0.05_NOISE.txt
diff --git a/...erimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_10_C_0.1_NOISE.txt b/...erimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_10_C_0.1_NOISE.txt
diff --git a/...erimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_10_C_0.5_NOISE.txt b/...erimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_10_C_0.5_NOISE.txt
diff --git a/...xperimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_10_C_0_NOISE.txt b/...xperimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_10_C_0_NOISE.txt
diff --git a/...erimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_10_C_1.0_NOISE.txt b/...erimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_10_C_1.0_NOISE.txt
diff --git a/...rimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_20_C_0.01_NOISE.txt b/...rimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_20_C_0.01_NOISE.txt
diff --git a/...rimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_20_C_0.05_NOISE.txt b/...rimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_20_C_0.05_NOISE.txt
diff --git a/...erimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_20_C_0.1_NOISE.txt b/...erimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_20_C_0.1_NOISE.txt
diff --git a/...erimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_20_C_0.5_NOISE.txt b/...erimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_20_C_0.5_NOISE.txt
diff --git a/...xperimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_20_C_0_NOISE.txt b/...xperimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_20_C_0_NOISE.txt
diff --git a/...erimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_20_C_1.0_NOISE.txt b/...erimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_20_C_1.0_NOISE.txt
diff --git a/...erimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_5_C_0.01_NOISE.txt b/...erimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_5_C_0.01_NOISE.txt
diff --git a/...erimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_5_C_0.05_NOISE.txt b/...erimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_5_C_0.05_NOISE.txt
diff --git a/...perimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_5_C_0.1_NOISE.txt b/...perimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_5_C_0.1_NOISE.txt
diff --git a/...perimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_5_C_0.5_NOISE.txt b/...perimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_5_C_0.5_NOISE.txt
diff --git a/...experimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_5_C_0_NOISE.txt b/...experimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_5_C_0_NOISE.txt
diff --git a/...perimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_5_C_1.0_NOISE.txt b/...perimental_results/old/2024_06_18_191929/2024_06_18_191929_results_50_R_5_C_1.0_NOISE.txt
diff --git a/examples/app-pytorch/experimental_results/preliminary_results_2024_0614_1347.txt b/examples/app-pytorch/experimental_results/preliminary_results_2024_0614_1347.txt
@@ -0,0 +1,115 @@
+(ClientAppActor pid=663694) INFO :      Starting training... [repeated 3x across cluster]
+INFO :      aggregate_fit: received 3 results and 0 failures
+INFO :      Hokeun! aggregate_fit: self.inplace
+INFO :      Hokeun! aggregate_inplace: beginning
+INFO :      Hokeun! aggregate_inplace: noise_enabled: False
+INFO :      Hokeun! aggregate_inplace: gauss_noise_sigma: 0.0
+INFO :      Hokeun! aggregate_inplace: len(ndarrays): 10
+INFO :      Hokeun! aggregate_inplace: len(ndarrays): 10
+INFO :      configure_evaluate: no clients selected, skipping evaluation
+INFO :
+INFO :      Hokeun! [SUMMARY]
+INFO :      Run finished 5 round(s) in 96.12s
+INFO :      	History (metrics, distributed, fit):
+INFO :      	{'train_accuracy': [(1, 0.2626266666666667),
+INFO :      	                    (2, 0.37656),
+INFO :      	                    (3, 0.43427333333333334),
+INFO :      	                    (4, 0.48339333333333334),
+INFO :      	                    (5, 0.5209533333333334)],
+INFO :      	 'train_loss': [(1, 3111.288763999939),
+INFO :      	                (2, 2636.2783563137054),
+INFO :      	                (3, 2432.4359317620597),
+INFO :      	                (4, 2231.099242488543),
+INFO :      	                (5, 2077.1603814164796)],
+INFO :      	 'val_accuracy': [(1, 0.2648),
+INFO :      	                  (2, 0.37516666666666665),
+INFO :      	                  (3, 0.43006666666666665),
+INFO :      	                  (4, 0.47583333333333333),
+INFO :      	                  (5, 0.5156666666666667)],
+INFO :      	 'val_loss': [(1, 19890.59807151556),
+INFO :      	              (2, 16862.849978710212),
+INFO :      	              (3, 15588.389818498554),
+INFO :      	              (4, 14355.181868209038),
+INFO :      	              (5, 13461.744302448738)]}
+
+
+-----------------------------------------------------------------------------------------
+
+
+(ClientAppActor pid=669727) INFO :      Starting training... [repeated 3x across cluster]
+INFO :      aggregate_fit: received 3 results and 0 failures
+INFO :      Hokeun! aggregate_fit: self.inplace
+INFO :      Hokeun! aggregate_inplace: beginning
+INFO :      Hokeun! aggregate_inplace: noise_enabled: True
+INFO :      Hokeun! aggregate_inplace: gauss_noise_sigma: 0.5
+INFO :      Hokeun! noise_factor: 0.804646
+INFO :      Hokeun! aggregate_inplace: len(ndarrays): 10
+INFO :      Hokeun! noise_factor: 0.861944
+INFO :      Hokeun! aggregate_inplace: len(ndarrays): 10
+INFO :      configure_evaluate: no clients selected, skipping evaluation
+INFO :
+INFO :      Hokeun! [SUMMARY]
+INFO :      Run finished 5 round(s) in 86.11s
+INFO :      	History (metrics, distributed, fit):
+INFO :      	{'train_accuracy': [(1, 0.29391333333333336),
+INFO :      	                    (2, 0.3678533333333333),
+INFO :      	                    (3, 0.41861333333333334),
+INFO :      	                    (4, 0.46557333333333334),
+INFO :      	                    (5, 0.5064866666666666)],
+INFO :      	 'train_loss': [(1, 3056.173280954361),
+INFO :      	                (2, 2692.5717417399087),
+INFO :      	                (3, 2502.7321223417916),
+INFO :      	                (4, 2305.85709019502),
+INFO :      	                (5, 2136.2207515239716)],
+INFO :      	 'val_accuracy': [(1, 0.29850000000000004),
+INFO :      	                  (2, 0.3683),
+INFO :      	                  (3, 0.4161666666666667),
+INFO :      	                  (4, 0.4692),
+INFO :      	                  (5, 0.5051333333333333)],
+INFO :      	 'val_loss': [(1, 19525.03346863389),
+INFO :      	              (2, 17186.626746791106),
+INFO :      	              (3, 15998.408485740423),
+INFO :      	              (4, 14755.69704998719),
+INFO :      	              (5, 13744.3956398579)]}
+
+
+-----------------------------------------------------------------------------------------
+
+
+(ClientAppActor pid=675422) INFO :      Starting training... [repeated 3x across cluster]
+INFO :      aggregate_fit: received 3 results and 0 failures
+INFO :      Hokeun! aggregate_fit: self.inplace
+INFO :      Hokeun! aggregate_inplace: beginning
+INFO :      Hokeun! aggregate_inplace: noise_enabled: True
+INFO :      Hokeun! aggregate_inplace: gauss_noise_sigma: 0.1
+INFO :      Hokeun! noise_factor: 1.056394
+INFO :      Hokeun! aggregate_inplace: len(ndarrays): 10
+INFO :      Hokeun! noise_factor: 0.949573
+INFO :      Hokeun! aggregate_inplace: len(ndarrays): 10
+INFO :      configure_evaluate: no clients selected, skipping evaluation
+INFO :
+INFO :      Hokeun! [SUMMARY]
+INFO :      Run finished 5 round(s) in 85.11s
+INFO :      	History (metrics, distributed, fit):
+INFO :      	{'train_accuracy': [(1, 0.26737333333333335),
+INFO :      	                    (2, 0.37349333333333334),
+INFO :      	                    (3, 0.43994666666666665),
+INFO :      	                    (4, 0.48291333333333336),
+INFO :      	                    (5, 0.5240666666666667)],
+INFO :      	 'train_loss': [(1, 3134.8707090616226),
+INFO :      	                (2, 2709.2759661277137),
+INFO :      	                (3, 2392.55160488685),
+INFO :      	                (4, 2242.929047127565),
+INFO :      	                (5, 2076.5026405652366)],
+INFO :      	 'val_accuracy': [(1, 0.27416666666666667),
+INFO :      	                  (2, 0.37496666666666667),
+INFO :      	                  (3, 0.44176666666666664),
+INFO :      	                  (4, 0.4823),
+INFO :      	                  (5, 0.5159666666666667)],
+INFO :      	 'val_loss': [(1, 19931.76632917424),
+INFO :      	              (2, 17240.421862681706),
+INFO :      	              (3, 15239.038378457848),
+INFO :      	              (4, 14358.611958074382),
+INFO :      	              (5, 13401.850687815033)]}
+
+
diff --git a/examples/app-pytorch/experimental_results/summarize_results.py b/examples/app-pytorch/experimental_results/summarize_results.py
@@ -0,0 +1,136 @@
+#!/usr/bin/env python3
+
+import argparse
+import os
+
+from enum import Enum
+import re
+
+class SummaryState(Enum):
+    NONE = 1
+    TRAIN_ACCURACY = 2
+    TRAIN_LOSS = 3
+    VAL_ACCURACY = 4
+    VAL_LOSS = 5
+
+class Summary:
+    def __init__(self):
+        self.file_name = ""
+        self.trial_count = 0
+        self.num_clients = 0
+        self.num_rounds = 0
+        self.noise_enabled = False
+        self.gauss_noise_sigma = 0.0
+        self.param_count = 0
+        self.mult_count = 0
+        self.train_accuracy = []
+        self.train_loss = []
+        self.val_accuracy = []
+        self.val_loss = []
+
+    def __str__(self):
+        return f"""----------------------
+file_name: {self.file_name}
+trial_count: {self.trial_count}
+num_clients: {self.num_clients}
+num_rounds: {self.num_rounds}
+noise_enabled: {self.noise_enabled}
+gauss_noise_sigma: {self.gauss_noise_sigma}
+param_count: {self.param_count}
+mult_count: {self.mult_count}
+train_accuracy: {self.train_accuracy}
+
+train_loss: {self.train_loss}
+
+val_accuracy: {self.val_accuracy}
+
+val_loss: {self.val_loss}
+----------------------"""
+
+
+def get_summary(file_path: str):
+    result_file = open(file_path, 'r')
+    result_lines = result_file.readlines()
+
+    state = SummaryState.NONE
+
+    summary = Summary()
+
+    summary.file_name = os.path.basename(file_path)
+    summary.trial_count = int(re.search("_(?P<count>[0-9]+)_TRIAL", summary.file_name).group("count"))
+
+    for line in result_lines:
+        if state == SummaryState.NONE:
+            if "'train_accuracy'" in line:
+                state = SummaryState.TRAIN_ACCURACY
+            if "'train_loss'" in line:
+                state = SummaryState.TRAIN_LOSS
+            if "'val_accuracy'" in line:
+                state = SummaryState.VAL_ACCURACY
+            if "'val_loss'" in line:
+                state = SummaryState.VAL_LOSS
+
+        if state == SummaryState.NONE:
+            tokens = line.split(":")
+            if "configure_fit: strategy sampled" in line:
+                summary.num_clients = int(re.search("sampled (?P<count>[0-9]+) clients", line).group("count"))
+            if "env_var_num_rounds:" in line:
+                summary.num_rounds = int(tokens[-1])
+            if "aggregate_inplace: noise_enabled:" in line:
+                summary.noise_enabled = tokens[-1] == "True"
+            if "aggregate_inplace: gauss_noise_sigma:" in line:
+                summary.gauss_noise_sigma = float(tokens[-1])
+            if "aggregate_inplace: hokeun_deep_count_float32(params):" in line:
+                summary.param_count = int(tokens[-1])
+            if "aggregate_inplace: mult_count:" in line:
+                summary.mult_count = int(tokens[-1])
+
+        # Get data
+        if state != SummaryState.NONE:
+            tuple_str = re.findall(r"\(.*?\)", line)
+            tuple_str = re.sub("[()]", "", tuple_str[0])
+            tuple = [x.strip() for x in tuple_str.split(",")]
+            tuple = [int(tuple[0]), float(tuple[1])]
+
+            if state == SummaryState.TRAIN_ACCURACY:
+                summary.train_accuracy.append(tuple)
+            if state == SummaryState.TRAIN_LOSS:
+                summary.train_loss.append(tuple)
+            if state == SummaryState.VAL_ACCURACY:
+                summary.val_accuracy.append(tuple)
+            if state == SummaryState.VAL_LOSS:
+                summary.val_loss.append(tuple)
+
+            if "]" in line:
+                state = SummaryState.NONE
+
+    return summary
+
+    # print("Hokeun! train_accuracy: ", summary.train_accuracy)
+    # print("Hokeun! train_loss: ", summary.train_loss)
+    # print("Hokeun! val_accuracy: ", summary.val_accuracy)
+    # print("Hokeun! val_loss: ", summary.val_loss)
+        # count += 1
+        # print("Line {}: {}".format(count, line.strip()))
+        # if count > 10:
+        #     break
+
+
+parser = argparse.ArgumentParser(description = "Summarize experimental results in directory.")
+
+parser.add_argument("-d", "--dir",
+                    required = True, dest ="target_dir", 
+                    action = "store", 
+                    help = "The directory including the experimental result files.")
+
+args = parser.parse_args()
+
+file_list = os.listdir(args.target_dir)
+file_list.sort()
+# print("Hokeun! " + str(file_list))
+
+print("num_clients\tgauss_noise_sigma\ttrial_count\ttrain_accuracy\tval_accuracy")
+for file in file_list:
+    summary = get_summary(os.path.join(args.target_dir, file))
+    # print(summary) # For debugging.
+    print(f"{summary.num_clients}\t{summary.gauss_noise_sigma}\t{summary.trial_count}\t{summary.train_accuracy[-1][1]}\t{summary.val_accuracy[-1][1]}")
diff --git a/examples/app-pytorch/pyproject.toml b/examples/app-pytorch/pyproject.toml
@@ -11,6 +11,6 @@ authors = ["The Flower Authors <[email protected]>"]
 [tool.poetry.dependencies]
 python = "^3.8"
 # Mandatory dependencies
-flwr = { version = "^1.8.0", extras = ["simulation"] }
+flwr = { path = "../../", develop = true, extras = ["simulation"] }
 torch = "2.2.1"
 torchvision = "0.17.1"
diff --git a/examples/app-pytorch/run_experiments_20_rounds.sh b/examples/app-pytorch/run_experiments_20_rounds.sh
@@ -0,0 +1,34 @@
+#!/bin/bash
+
+# Make sure to run poetry shell first!
+
+date_time=$(date '+%Y_%m_%d_%H%M%S');
+
+HOKEUN_FLWR_NUM_ROUNDS=20 HOKEUN_FLWR_NOISE_ENABLED=0 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=0.0 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 5' 2>&1 | tee "$date_time"_results_20_R_5_C_0_NOISE.txt
+
+HOKEUN_FLWR_NUM_ROUNDS=20 HOKEUN_FLWR_NOISE_ENABLED=1 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=1.0 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 5' 2>&1 | tee "$date_time"_results_20_R_5_C_1.0_NOISE.txt
+
+HOKEUN_FLWR_NUM_ROUNDS=20 HOKEUN_FLWR_NOISE_ENABLED=1 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=0.5 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 5' 2>&1 | tee "$date_time"_results_20_R_5_C_0.5_NOISE.txt
+
+HOKEUN_FLWR_NUM_ROUNDS=20 HOKEUN_FLWR_NOISE_ENABLED=1 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=0.1 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 5' 2>&1 | tee "$date_time"_results_20_R_5_C_0.1_NOISE.txt
+
+HOKEUN_FLWR_NUM_ROUNDS=20 HOKEUN_FLWR_NOISE_ENABLED=1 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=0.05 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 5' 2>&1 | tee "$date_time"_results_20_R_5_C_0.05_NOISE.txt
+
+HOKEUN_FLWR_NUM_ROUNDS=20 HOKEUN_FLWR_NOISE_ENABLED=1 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=0.01 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 5' 2>&1 | tee "$date_time"_results_20_R_5_C_0.01_NOISE.txt
+
+
+
+
+
+HOKEUN_FLWR_NUM_ROUNDS=20 HOKEUN_FLWR_NOISE_ENABLED=0 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=0.0 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 10' 2>&1 | tee "$date_time"_results_20_R_10_C_0_NOISE.txt
+
+HOKEUN_FLWR_NUM_ROUNDS=20 HOKEUN_FLWR_NOISE_ENABLED=1 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=1.0 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 10' 2>&1 | tee "$date_time"_results_20_R_10_C_1.0_NOISE.txt
+
+HOKEUN_FLWR_NUM_ROUNDS=20 HOKEUN_FLWR_NOISE_ENABLED=1 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=0.5 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 10' 2>&1 | tee "$date_time"_results_20_R_10_C_0.5_NOISE.txt
+
+HOKEUN_FLWR_NUM_ROUNDS=20 HOKEUN_FLWR_NOISE_ENABLED=1 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=0.1 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 10' 2>&1 | tee "$date_time"_results_20_R_10_C_0.1_NOISE.txt
+
+HOKEUN_FLWR_NUM_ROUNDS=20 HOKEUN_FLWR_NOISE_ENABLED=1 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=0.05 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 10' 2>&1 | tee "$date_time"_results_20_R_10_C_0.05_NOISE.txt
+
+HOKEUN_FLWR_NUM_ROUNDS=20 HOKEUN_FLWR_NOISE_ENABLED=1 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=0.01 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 10' 2>&1 | tee "$date_time"_results_20_R_10_C_0.01_NOISE.txt
+
diff --git a/examples/app-pytorch/run_experiments_50_rounds.sh b/examples/app-pytorch/run_experiments_50_rounds.sh
@@ -0,0 +1,47 @@
+#!/bin/bash
+
+# Make sure to run poetry shell first!
+
+date_time=$(date '+%Y_%m_%d_%H%M%S');
+
+HOKEUN_FLWR_NUM_ROUNDS=50 HOKEUN_FLWR_NOISE_ENABLED=0 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=0.0 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 5' 2>&1 | tee "$date_time"_results_50_R_5_C_0_NOISE.txt
+
+HOKEUN_FLWR_NUM_ROUNDS=50 HOKEUN_FLWR_NOISE_ENABLED=1 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=1.0 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 5' 2>&1 | tee "$date_time"_results_50_R_5_C_1.0_NOISE.txt
+
+HOKEUN_FLWR_NUM_ROUNDS=50 HOKEUN_FLWR_NOISE_ENABLED=1 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=0.5 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 5' 2>&1 | tee "$date_time"_results_50_R_5_C_0.5_NOISE.txt
+
+HOKEUN_FLWR_NUM_ROUNDS=50 HOKEUN_FLWR_NOISE_ENABLED=1 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=0.1 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 5' 2>&1 | tee "$date_time"_results_50_R_5_C_0.1_NOISE.txt
+
+HOKEUN_FLWR_NUM_ROUNDS=50 HOKEUN_FLWR_NOISE_ENABLED=1 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=0.05 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 5' 2>&1 | tee "$date_time"_results_50_R_5_C_0.05_NOISE.txt
+
+HOKEUN_FLWR_NUM_ROUNDS=50 HOKEUN_FLWR_NOISE_ENABLED=1 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=0.01 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 5' 2>&1 | tee "$date_time"_results_50_R_5_C_0.01_NOISE.txt
+
+
+
+
+HOKEUN_FLWR_NUM_ROUNDS=50 HOKEUN_FLWR_NOISE_ENABLED=0 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=0.0 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 10' 2>&1 | tee "$date_time"_results_50_R_10_C_0_NOISE.txt
+
+HOKEUN_FLWR_NUM_ROUNDS=50 HOKEUN_FLWR_NOISE_ENABLED=1 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=1.0 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 10' 2>&1 | tee "$date_time"_results_50_R_10_C_1.0_NOISE.txt
+
+HOKEUN_FLWR_NUM_ROUNDS=50 HOKEUN_FLWR_NOISE_ENABLED=1 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=0.5 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 10' 2>&1 | tee "$date_time"_results_50_R_10_C_0.5_NOISE.txt
+
+HOKEUN_FLWR_NUM_ROUNDS=50 HOKEUN_FLWR_NOISE_ENABLED=1 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=0.1 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 10' 2>&1 | tee "$date_time"_results_50_R_10_C_0.1_NOISE.txt
+
+HOKEUN_FLWR_NUM_ROUNDS=50 HOKEUN_FLWR_NOISE_ENABLED=1 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=0.05 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 10' 2>&1 | tee "$date_time"_results_50_R_10_C_0.05_NOISE.txt
+
+HOKEUN_FLWR_NUM_ROUNDS=50 HOKEUN_FLWR_NOISE_ENABLED=1 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=0.01 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 10' 2>&1 | tee "$date_time"_results_50_R_10_C_0.01_NOISE.txt
+
+
+
+
+HOKEUN_FLWR_NUM_ROUNDS=50 HOKEUN_FLWR_NOISE_ENABLED=0 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=0.0 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 20' 2>&1 | tee "$date_time"_results_50_R_20_C_0_NOISE.txt
+
+HOKEUN_FLWR_NUM_ROUNDS=50 HOKEUN_FLWR_NOISE_ENABLED=1 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=1.0 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 20' 2>&1 | tee "$date_time"_results_50_R_20_C_1.0_NOISE.txt
+
+HOKEUN_FLWR_NUM_ROUNDS=50 HOKEUN_FLWR_NOISE_ENABLED=1 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=0.5 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 20' 2>&1 | tee "$date_time"_results_50_R_20_C_0.5_NOISE.txt
+
+HOKEUN_FLWR_NUM_ROUNDS=50 HOKEUN_FLWR_NOISE_ENABLED=1 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=0.1 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 20' 2>&1 | tee "$date_time"_results_50_R_20_C_0.1_NOISE.txt
+
+HOKEUN_FLWR_NUM_ROUNDS=50 HOKEUN_FLWR_NOISE_ENABLED=1 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=0.05 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 20' 2>&1 | tee "$date_time"_results_50_R_20_C_0.05_NOISE.txt
+
+HOKEUN_FLWR_NUM_ROUNDS=50 HOKEUN_FLWR_NOISE_ENABLED=1 HOKEUN_FLWR_GAUSS_NOISE_SIGMA=0.01 bash -c 'flower-simulation --server-app server:app --client-app client:app --num-supernodes 20' 2>&1 | tee "$date_time"_results_50_R_20_C_0.01_NOISE.txt