update full code and data of 3 experiments

0_mojitos.py

@@ -60,7 +60,6 @@ output_dir = os.path.join(mojitos_dir, "processed_files")
 os.makedirs(output_dir, exist_ok=True)
 
 for file_path in sorted(mojitos_file_list):
-
     filename = os.path.basename(file_path)
     identifier, last_number = filename.split("_flower_")
     identifier = identifier.split('.')[0]
@@ -68,15 +67,28 @@ for file_path in sorted(mojitos_file_list):
 
     df = pd.read_csv(file_path, sep="\s+")
 
-    energy_columns = [col for col in df.columns if col.startswith("package") or col.startswith("dram")]
+    energy_columns = [
+        col for col in df.columns 
+        if col.startswith("package") or col.startswith("dram")
+    ]
+    
+    power_columns = [
+        col for col in df.columns
+        if col.startswith("gpu") and col.endswith("_power")
+    ]
+
+    df["sum_package_dram"] = df[energy_columns].sum(axis=1) if energy_columns else 0
+    df["sum_gpu"] = df[power_columns].sum(axis=1) * 100 if power_columns else 0  # mW * 0.1s → µJ (mojit sap 0.1)
 
-    if energy_columns:
-        df["sum_package_dram_idle"] = df[energy_columns].sum(axis=1)  # Sum of package, dram and idle energy
+    # Luôn tạo cột sum_package_dram_gpu
+    df["sum_package_dram_gpu"] = df["sum_package_dram"] + df["sum_gpu"]
 
     mojitos_individual_frames[filename] = df
 
     output_file = os.path.join(output_dir, f"processed_{filename}")
     df.to_csv(output_file, index=False)
+
+
 print("Processed files in: ", output_dir)
 # # Merging all dataframes into one
 # merged_df = pd.concat(mojitos_individual_frames.values(), ignore_index=True)

1_mojitos_ana.py

-# cmd: python3 1_mojitos_ana.py --dir "Log/Flower_TetHoliday/Flower_instance_fedAvg_cifar10"
+# cmd: python3 1_mojitos_ana.py --input "Log/Flower_CPU/Flower_instance_fedAvg_cifar10_epoch1" --output CPU_fedAvg_cifar10_epoch1
 # output: merged_mojitos_{test_camp}_{test_case}.csv -> merged_mojitos_Flower_TetHoliday_Flower_instance_fedAvg_cifar10.csv
 
 import os 
@@ -12,10 +12,11 @@ current_dir = os.getcwd()
 parent_dir = os.path.abspath(os.path.join(current_dir))
 
 parser = argparse.ArgumentParser(description="Specify log directory with parsed values")
-parser.add_argument('--dir', required=True, help="Value of log directory")
+parser.add_argument('--input', required=True, help="Input directory")
+parser.add_argument('--output', required=True, help="Output file name")
 args = parser.parse_args()
 
-processing_str = args.dir
+processing_str = args.input
 processing_dir = os.path.join(parent_dir, processing_str)
 test_camp = os.path.basename(os.path.dirname(processing_dir))
 test_case = os.path.basename(processing_dir)
@@ -76,34 +77,42 @@ for file_path in sorted(mojitos_file_list):
     
     df = pd.read_csv(file_path, sep=",", engine='python')
     
-    # List of columns for energy consumption
-    energy_columns = [col for col in df.columns if col.startswith("package") or col.startswith("dram") or col.startswith("idle")]
-
-    # Check if necessary columns exist
-    if energy_columns:
-        # Calculate sum of package, dram, and idle at each timestamp
-        df["sum_package_dram_idle"] = df[energy_columns].sum(axis=1)
-        
-        # Compute statistics on the sum column
-        sum_stats = {
-            "median_sum_package_dram_idle": df["sum_package_dram_idle"].median(),
-            "mean_sum_package_dram_idle": df["sum_package_dram_idle"].mean(),
-            "std_sum_package_dram_idle": df["sum_package_dram_idle"].std(),
-            "min_sum_package_dram_idle": df["sum_package_dram_idle"].min(),
-            "max_sum_package_dram_idle": df["sum_package_dram_idle"].max(),
-            "q1_sum_package_dram_idle": df["sum_package_dram_idle"].quantile(0.25),
-            "q3_sum_package_dram_idle": df["sum_package_dram_idle"].quantile(0.75),
-            "sum_package_dram_idle": df["sum_package_dram_idle"].sum()
-        }
-    else:
-        sum_stats = {}  # No data available
-
-    # Calculate statistics for specific columns
+    # Tìm cột năng lượng (package, dram)
+    energy_columns = [
+        col for col in df.columns 
+        if col.startswith("package") or col.startswith("dram")
+    ]
+
+    # Tìm cột công suất GPU
+    power_columns = [
+        col for col in df.columns
+        if col.startswith("gpu") and col.endswith("_power")
+    ]
+
+    sum_stats = {}  # Khởi tạo stats
+
+    # Luôn tạo cột tổng thành phần
+    df["sum_package_dram"] = df[energy_columns].sum(axis=1) if energy_columns else 0
+    df["sum_gpu"] = df[power_columns].sum(axis=1) * 100 if power_columns else 0  # mW * 0.1s → µJ (mojitos samp 0.1s)
+
+    # Luôn tạo cột tổng năng lượng
+    df["sum_package_dram_gpu"] = df["sum_package_dram"] + df["sum_gpu"]
+    total_column = "sum_package_dram_gpu"
+
+    # Tính thống kê trên cột tổng năng lượng
+    sum_stats = {
+        f"median_{total_column}": df[total_column].median(),
+        f"mean_{total_column}": df[total_column].mean(),
+        f"std_{total_column}": df[total_column].std(),
+        f"sum_{total_column}": df[total_column].sum()
+    }
+    
+    # Tính thống kê cho các cột mạng
     columns_to_analyze = ["br0:rxp", "br0:rxb", "br0:txp", "br0:txb"]
     df_list = []
-    
+
     for column in columns_to_analyze:
-        if column in df.columns:  
+        if column in df.columns:
             stats = {
                 f"median_{column}": df[column].median(),
                 f"mean_{column}": df[column].mean(),
@@ -111,21 +120,20 @@ for file_path in sorted(mojitos_file_list):
             }
             df_list.append(pd.DataFrame([stats]))
     
-    # Convert sum stats to DataFrame
+    # Thêm thống kê năng lượng
     df_list.append(pd.DataFrame([sum_stats]))
 
-    # Concatenate all DataFrames for the current file
+    # Gộp tất cả lại
     concatenated_df = pd.concat(df_list, axis=1)
 
-    # Count number of data points
+    # Thêm thông tin mô tả
     concatenated_df["n_data"] = df.shape[0]
     concatenated_df["time (s)"] = df['#timestamp'].max() - df['#timestamp'].min()
     concatenated_df["source"] = identifier
     concatenated_df["file_number"] = last_number
     
-    # Append to final DataFrame list
+    # Lưu vào list kết quả
     mojitos_df_list.append(concatenated_df)
-
 # Combine all DataFrames
 mojitos_merged_df = pd.concat(mojitos_df_list, ignore_index=True)
 print(mojitos_merged_df)
@@ -133,7 +141,10 @@ print(mojitos_merged_df)
 # Save the single, merged DataFrame to a CSV file
 # Construct the full path
 mojitos_output_dir = os.path.join(parent_dir, "Data_analysis", "Output_level_1")
-mojitos_output_file = os.path.join(mojitos_output_dir, f"merged_mojitos_{test_camp}_{test_case}.csv")
+
+output_file_name = args.output
+mojitos_output_file = os.path.join(mojitos_output_dir, f"merged_mojitos_{output_file_name}.csv")
+# mojitos_output_file = os.path.join(mojitos_output_dir, f"merged_mojitos_{test_camp}_{test_case}.csv")
 
 
 # Ensure the directory exists

2_power_ana.py

@@ -13,10 +13,11 @@ current_dir = os.getcwd()
 parent_dir = os.path.abspath(os.path.join(current_dir))
 print(parent_dir)
 parser = argparse.ArgumentParser(description="Specify log directory with parsed values")
-parser.add_argument('--dir', required=True, help="Value of log directory")
+parser.add_argument('--input', required=True, help="Input directory")
+parser.add_argument('--output', required=True, help="Output file name")
 args = parser.parse_args()
 
-processing_str = args.dir
+processing_str = args.input
 processing_dir = os.path.join(parent_dir, processing_str)
 test_camp = os.path.basename(os.path.dirname(processing_dir))
 test_case = os.path.basename(processing_dir)
@@ -91,10 +92,10 @@ for file_path in sorted(power_file_list):
             "median_power": df['power'].median(),
             "mean_power": df['power'].mean(),
             "std_power": df['power'].std(),
-            "min_power": df["power"].min(),
-            "max_power": df["power"].max(),
-            "q1_power": df["power"].quantile(0.25),
-            "q3_power": df["power"].quantile(0.75),            
+            # "min_power": df["power"].min(),
+            # "max_power": df["power"].max(),
+            # "q1_power": df["power"].quantile(0.25),
+            # "q3_power": df["power"].quantile(0.75),            
             "n_data": len(df),
             "source": device,
             "time (s)": processing_time,
@@ -117,7 +118,11 @@ print(power_merged_df)
 
 # Construct the full path
 power_output_dir = os.path.join(parent_dir, "Data_analysis", "Output_level_1")
-power_output_file = os.path.join(power_output_dir, f"merged_power_{test_camp}_{test_case}.csv")
+
+output_file_name = args.output
+power_output_file = os.path.join(power_output_dir, f"merged_power_{output_file_name}.csv")
+
+# power_output_file = os.path.join(power_output_dir, f"merged_power_{test_camp}_{test_case}.csv")
 
 # Ensure the directory exists
 os.makedirs(power_output_dir, exist_ok=True)

3_mean_energy.py

@@ -13,6 +13,7 @@ parent_dir = os.path.abspath(os.path.join(current_dir))
 parser = argparse.ArgumentParser(description="Specify files with parsed values")
 parser.add_argument('--power', required=True, help="Value of power file")
 parser.add_argument('--mojitos', required=True, help="Value of mojitos file")
+parser.add_argument('--output', required=True, help="Output file name")
 args = parser.parse_args()
 
 # Load the CSV files into DataFrames
@@ -26,7 +27,7 @@ df_mojitos = pd.read_csv(mojitos_file)
 
 # Group by 'file_number' and calculate the mean of the respective columns
 mean_power_by_file_number = df_power.groupby("file_number")["mean_power"].mean()
-mean_mojitos_by_file_number = df_mojitos.groupby("file_number")["mean_sum_package_dram_idle"].mean()
+mean_mojitos_by_file_number = df_mojitos.groupby("file_number")["mean_sum_package_dram_gpu"].mean()
 
 # std by file_number
 def combined_std(df_group, std_col, n_col):
@@ -36,7 +37,7 @@ def combined_std(df_group, std_col, n_col):
 
 # combined std by file_number
 std_power_by_file = df_power.groupby("file_number").apply(lambda x: combined_std(x, "std_power", "n_data"), include_groups=False)
-std_mojitos_by_file = df_mojitos.groupby("file_number").apply(lambda x: combined_std(x, "std_sum_package_dram_idle", "n_data"), include_groups=False)
+std_mojitos_by_file = df_mojitos.groupby("file_number").apply(lambda x: combined_std(x, "std_sum_package_dram_gpu", "n_data"), include_groups=False)
 
 # # Combine the two Series into a single DataFrame
 # combined_df = pd.DataFrame({
@@ -53,9 +54,9 @@ combined_df = pd.DataFrame({
     "std_mojitos_combined": std_mojitos_by_file.values,
     # "min_power": df_power.groupby("file_number")["min_power"].min().values,
     # "max_power": df_power.groupby("file_number")["max_power"].max().values,
-    # "min_mojitos": df_mojitos.groupby("file_number")["min_package_dram_idle"].min().values,
-    # "max_mojitos": df_mojitos.groupby("file_number")["max_package_dram_idle"].max().values,
-    "sum_mojitos": df_mojitos.groupby("file_number")["sum_package_dram_idle"].sum().values,
+    # "min_mojitos": df_mojitos.groupby("file_number")["min_package_dram"].min().values,
+    # "max_mojitos": df_mojitos.groupby("file_number")["max_package_dram"].max().values,
+    "sum_mojitos": df_mojitos.groupby("file_number")["sum_sum_package_dram_gpu"].sum().values,
     "n_data_mojitos": df_power.groupby("file_number")["n_data"].sum().values,
     "n_data_power": df_mojitos.groupby("file_number")["n_data"].sum().values
 })
@@ -68,7 +69,9 @@ print(combined_df)
 # E_output_file = os.path.join(E_output_dir, "mean_E_fedAvg2Clients.csv")
 
 E_output_dir = os.path.join(parent_dir, "Data_analysis", "Output_level_2")
-E_output_file = os.path.join(E_output_dir, f"mean_energy_{extracted}.csv")
+output_file_name = args.output
+E_output_file = os.path.join(E_output_dir, f"mean_energy_{output_file_name}.csv")
+# E_output_file = os.path.join(E_output_dir, f"mean_energy_{extracted}.csv")
 
 # Ensure the directory exists
 os.makedirs(E_output_dir, exist_ok=True)

4_flower_ana.py

 # cmd python3 4_flower_ana.py --dir
 # output: flower_<pattern>_accuracy_time.csv -> flower_fedAvg_accuracy_time.csv
 
-# import os, glob
-# import pandas as pd
-# import argparse
-
-# parser = argparse.ArgumentParser(description="Specify pattern with parsed values")
-# parser.add_argument('--pattern', required=True, help="String of pattern")
-# parser.add_argument('--dir', required=False, help="Path to the directory containing log files")
-# args = parser.parse_args()
-
-# current_dir = os.getcwd()
-# parent_dir = os.path.abspath(os.path.join(current_dir))
-# flower_dir = os.path.join(parent_dir, "Log_autres")
-
-# # flower_dir = "/home/hdomai/Documents/RepoLab/Data/Log_autres"
-# # File pattern to match all relevant files
-# flower_file_pattern = os.path.join(flower_dir, f"*_*_{args.pattern}_*")
-# flower_file_list = glob.glob(flower_file_pattern)
-
-# # Initialize an empty list to store the data
-# data_list = []
-
-# # Loop over all files
-# for file in flower_file_list:
-#     with open(file, "r") as f:
-#         data = pd.read_csv(f)
-#         df = pd.DataFrame(data)
-#         max_round = df["round"].max()
-#         accuracy = df.loc[df["round"] == max_round, "accuracy"].values[0] 
-#         # can replace max_round with the specific round number to get the accuracy at that round
-#         #time = df.loc[df["round"] == max_round, "time"].values[0]
-#         time = df["time"].sum()
-#         # Append the data to the list
-#         data_list.append({"filepath": file, "accuracy": accuracy, "time": time})
-
-# # Create a DataFrame from the list
-# flower_data = pd.DataFrame(data_list)
-
-# output_dir = os.path.join(parent_dir, "Data_analysis", "Output_level_2")
-# output_file = os.path.join(output_dir, f"flower_{args.pattern}_accuracy_time.csv")
-
-# # Ensure the directory exists
-# os.makedirs(output_dir, exist_ok=True)
-
-# # Save the DataFrame to a CSV file
-# flower_data.to_csv(output_file, index=False)
-# print(f"Data saved to {output_file}")
-
 import os
 import glob
 import pandas as pd
@@ -55,6 +8,7 @@ import argparse
 
 parser = argparse.ArgumentParser(description="Specify instance directory and pattern")
 parser.add_argument('--dir', required=True, help="Path to the instance directory")
+parser.add_argument('--output', required=True, help="Output file name")
 args = parser.parse_args()
 
 instance_dir = args.dir  # Instance directory (vd: Flower_instance_fedAvg2Clients_cifar10_epoch1)
@@ -77,7 +31,7 @@ for flwr_dir in flwr_dirs:
 
 # Kiểm tra có file nào không
 if not flower_file_list:
-    print(f" Không tìm thấy file training_results_... trong {instance_dir}")
+    print(f" No file training_results_... in {instance_dir}")
     exit()
 
 # Initialize list to store data
@@ -101,7 +55,10 @@ flower_data = pd.DataFrame(data_list)
 # Lưu output
 
 output_dir = os.path.join(parent_dir, "Data_analysis", "Output_level_2")
-output_file = os.path.join(output_dir, f"flower_{identifier}_accuracy_time.csv")
+
+output_file_name = args.output
+output_file = os.path.join(output_dir, f"flower_{output_file_name}_accuracy_time.csv")
+# output_file = os.path.join(output_dir, f"flower_{identifier}_accuracy_time.csv")
 
 # Ensure the directory exists
 os.makedirs(output_dir, exist_ok=True)

5_combine_energy_fl.py

@@ -10,6 +10,7 @@ parser = argparse.ArgumentParser(description="Specify pattern with parsed values
 parser.add_argument('-a','--accuracy', required=True, help="Accuracy file path")
 parser.add_argument('-e','--energy', required=True, help="Energy file path")
 parser.add_argument('-m','--meta', required=True, help="Meta data file path")
+parser.add_argument('-o','--output', required=True, help="Output file name")
 args = parser.parse_args()
  
 current_dir = os.getcwd()
@@ -77,7 +78,9 @@ print(df_combined)
 
 # Construct the full path
 output_dir = os.path.join(parent_dir, "Data_analysis", "Output_level_3")
-output_file = os.path.join(output_dir, f"combine_{extracted}.csv")
+output_file_name = args.output
+output_file = os.path.join(output_dir, f"combine_{output_file_name}.csv")
+# output_file = os.path.join(output_dir, f"combine_{extracted}.csv")
 
 # Ensure the directory exists
 os.makedirs(output_dir, exist_ok=True)

6_final.py

@@ -36,11 +36,10 @@ print(df)
 
 parser = argparse.ArgumentParser(description="Specify pattern with parsed values")
 parser.add_argument('-f', '--files', nargs='+', required=True, help="List of file paths")
-parser.add_argument('-c', '--campaign', required=True, help="Text of campaign")
+parser.add_argument('-o', '--output', required=True, help="Output file name")
 args = parser.parse_args()
 
 file_paths = args.files
-campaign = args.campaign
 
 # Initialize an empty list to hold dataframes
 dataframes = []
@@ -49,7 +48,7 @@ dataframes = []
 for i, file_path in enumerate(file_paths):
     df = pd.read_csv(file_path)
     
-    indentifier = os.path.basename(file_path).split("_instance_")[1].split(".csv")[0]
+    indentifier = os.path.basename(file_path).split("combine_")[1].split(".csv")[0]
     df["instance"] = indentifier
     dataframes.append(df)
 
@@ -59,7 +58,9 @@ print(combined_df)
 
 # Construct the full path
 output_dir = os.path.join(parent_dir, "Data_analysis", "Output_level_4")
-output_file = os.path.join(output_dir, f"combine_{campaign}.csv")
+output_file_name = args.output
+output_file = os.path.join(output_dir, f"combine_{output_file_name}.csv")
+# output_file = os.path.join(output_dir, f"combine_{campaign}.csv")
 
 # Ensure the directory exists
 os.makedirs(output_dir, exist_ok=True)

Data_analysis/Output_level_1/merged_mojitos_CPU_fedAvg2Clients_cifar10_epoch1.csv

+median_br0:rxp,mean_br0:rxp,std_br0:rxp,median_br0:rxb,mean_br0:rxb,std_br0:rxb,median_br0:txp,mean_br0:txp,std_br0:txp,median_br0:txb,mean_br0:txb,std_br0:txb,median_sum_package_dram_gpu,mean_sum_package_dram_gpu,std_sum_package_dram_gpu,sum_sum_package_dram_gpu,n_data,time (s),source,file_number
+1.0,2.701145552560647,17.328115920557096,320.0,19526.72446091644,434842.10019086016,1.0,2.5485175202156336,17.758628813161128,66.0,46750.13039083558,850326.3734267085,2724361.5,2880259.1559973047,666269.6031791639,42743045875,14840,1483.8204520880008,taurus-1,1740657023
+2.0,4.093643490115883,21.5899582257876,366.0,24724.802743694614,463002.0299459187,1.0,3.076772324471711,20.13842980940622,66.0,58989.47920927062,976598.5676265118,2704992.0,2850714.593047035,737769.0778373101,33455986464,11736,1173.4806070449995,taurus-1,1740658525
+2.0,4.816354026323971,24.909668020194708,640.0,30038.001761840605,514283.3704968076,2.0,3.7255674163125714,23.012351806526198,132.0,71719.76163332988,1119638.2591886795,2758922.0,2915020.520261167,790981.0531114227,28127033000,9649,964.7695306729984,taurus-1,1740659716
+2.0,5.337445739090701,27.308627421472067,640.0,33118.510052547404,538413.391189081,2.0,4.381539867489148,25.59955277630684,132.0,79065.84932602239,1185213.3470918173,2905847.5,3073095.886794608,826908.4052930484,26901881393,8754,875.2985441479977,taurus-1,1740660698
+1.0,3.459573370032685,21.48267518929938,320.0,24912.892568381216,463407.94511410646,1.0,3.0981420953036296,21.35605581535957,66.0,59545.23111990366,1066358.2161715243,2664146.0,2813175.69396181,747953.8717781461,32705980618,11626,1162.4503471040007,taurus-1,1740663090
+2.0,4.304464377770905,25.744581020423343,640.0,29854.708939065884,510504.91502694524,2.0,3.692236313021961,23.269459788678294,132.0,71348.88235900608,1125636.503251979,2760676.0,2925671.90483555,775572.349043527,28376091805,9699,969.749727997998,taurus-1,1740664269
+2.0,4.952653903473576,28.113504190513133,640.0,33213.66376246704,547068.0126945036,2.0,4.242691734495013,24.78594724125789,132.0,79331.7631548779,1196131.9272919113,2724819.0,2902957.7833314226,859116.2111822648,25322500744,8723,872.169843128002,taurus-1,1740665257
+1.0,2.74609375,16.306426966445965,320.0,19537.035358297413,401522.6410867256,1.0,2.492389547413793,16.46585388958776,66.0,46680.08425377155,792641.2846473008,2722988.0,2891288.7413119613,640794.6182391682,42929855231,14848,1484.6807563910006,taurus-1,1740667836
+0.0,1.5593368825392546,14.46873707687505,0.0,13097.927960105128,329270.6569948023,0.0,1.0390188018060516,9.695548814230277,0.0,4645.282229260732,191558.49376853585,4744186.0,4534640.452928095,1492684.2717384046,67289529681,14839,1483.8002768530005,taurus-13,1740657023
+1.0,2.829839809134288,18.18679573191392,52.0,20479.74241649625,413213.08327881113,0.0,1.4847477845944104,11.785713730363604,0.0,8990.997955010225,274692.59688886954,6684003.0,5938370.8138207225,1722157.972188636,69692719871,11736,1173.4609519449987,taurus-13,1740658525
+1.0,3.152865581925588,21.452354558256413,52.0,24873.12892527723,469878.8211969447,1.0,1.8797802881127579,14.445415879044612,84.0,11854.048398797802,316353.81760295795,7623752.0,6745331.769406156,2174929.4475042317,65085706243,9649,964.750171454998,taurus-13,1740659716
+1.0,3.4671616219303254,23.617088828527454,52.0,26386.544260422615,486028.4666642711,0.0,2.138206739006282,16.306784302382205,0.0,10973.080868075385,305201.8301419171,8357204.0,7112930.227755568,2773726.4370876253,62273704144,8755,875.379782865999,taurus-13,1740660698
+0.0,2.0992602786857044,18.143877675049893,0.0,19841.913641837262,415913.34442907583,0.0,1.4619817650094615,12.134442921993095,0.0,8279.84835713057,256849.3200027945,6557895.5,5757114.761740926,1802248.1732336923,66932216220,11626,1162.4313208780004,taurus-13,1740663090
+1.0,2.414536082474227,20.09091653844122,48.0,22822.913402061855,437571.8075672179,0.0,1.7268041237113403,14.252231357318246,0.0,9877.889175257733,273936.09486392484,7439198.0,6179812.159484536,2399264.770992566,59944177947,9700,969.8307628990005,taurus-13,1740664269
+1.0,3.077037716381979,22.768931487332054,52.0,28546.61469677863,497277.1928152548,1.0,2.3172073827811532,16.273929472010394,326.0,14188.012151782643,340605.8053503399,9316855.0,7740230.459704231,2481251.524193473,67518030300,8723,872.1506882909998,taurus-13,1740665257
+0.0,1.7728313577586208,14.539255882604067,0.0,15569.960870150862,367107.82889063796,0.0,1.1173895474137931,9.65464256143536,0.0,7126.0188577586205,248405.62937161463,5786771.5,5128268.94995959,1407208.755290975,76144537369,14848,1484.660889409999,taurus-13,1740667836
+0.0,1.813531909158299,14.704308086071553,0.0,16775.883078374554,365715.8459850448,0.0,1.2458386683738796,10.012255532749082,0.0,7776.688590875396,254389.3207085428,5578020.0,4925666.799177842,1222616.6487433547,73091969633,14839,1483.7411957240001,taurus-8,1740657023
+1.0,2.778885480572597,18.74103838176891,50.0,19701.95884458078,414568.87975756725,0.0,1.4317484662576687,11.939512838073492,0.0,8201.91436605317,252721.18903458043,6013918.5,5253160.97963531,1738993.1979871846,61651097257,11736,1173.5004691799986,taurus-8,1740658525
+1.0,2.8893149549176083,20.129251166551228,46.0,22026.22551559747,435637.1195041838,0.0,1.6193387915846202,13.572134043317934,0.0,8027.162089335682,262054.25632462534,6809356.0,5454789.788993678,2362975.29969303,52633266674,9649,964.790052231001,taurus-8,1740659716
+1.0,3.430839520274129,22.534097924326588,52.0,26384.346887492862,475352.16782786744,0.0,2.105653912050257,15.87860645040589,0.0,12012.782295830953,323411.3882274882,7763530.0,6580857.422272987,2716860.382529822,57615406732,8755,875.318658152999,taurus-8,1740660698
+1.0,2.1586236559139786,18.116097970480777,48.0,20631.740043010752,423017.3588654152,0.0,1.5088172043010752,11.979131840071872,0.0,9078.571870967742,273629.65120075643,6081350.0,5436135.213333333,1703206.0987494343,63195071855,11625,1162.372031977,taurus-8,1740663090
+0.0,2.358387462625013,20.072492474349126,0.0,21881.48303948861,419818.35734435695,0.0,1.679039076193422,14.315141198893413,0.0,7987.991751726982,262139.96973529604,6816527.0,5459942.455201567,2346140.8596033617,52955981873,9699,969.7701328419971,taurus-8,1740664269
+0.0,2.4327639573541213,20.690580657857264,0.0,21197.552676831365,424554.91043707536,0.0,1.7261263326837097,14.949769584105226,0.0,5696.913447208529,215297.5349859281,3824646.0,5027737.373839276,2838832.312623067,43856953112,8723,872.1904052129976,taurus-8,1740665257
+0.0,1.8258468583743013,15.191791202281316,0.0,15567.610478820123,358636.02644946653,0.0,1.1597413967270522,9.767016171278534,0.0,6521.14075021887,230308.42186219204,5245931.0,4651301.545962691,1320329.8702361793,69067176656,14849,1484.7009381870012,taurus-8,1740667836
+0.0,1.8485073118134645,15.754171638281125,0.0,16764.364984163352,383524.1042802626,0.0,1.2534537367747154,9.892935964548213,0.0,7776.853359390794,244496.36287311412,5959409.0,5328910.549363164,1170586.1548532476,79075703642,14839,1483.7708219659999,taurus-9,1740657023
+0.0,2.7407123381049763,18.902138458824226,0.0,18922.20969665985,406032.6782828614,0.0,1.4011588275391957,12.096872671881176,0.0,8194.583844580777,260603.03617080976,6340539.0,5356890.160276074,1866663.9001635318,62868462921,11736,1173.430413547001,taurus-9,1740658525
+1.0,3.153575129533679,21.593735157144494,52.0,24873.02580310881,465316.88864545216,1.0,1.8946113989637305,14.769131606091333,84.0,10914.102590673576,301893.30559751217,7466166.5,6537262.912227979,2203756.2225055154,63084587103,9650,964.8213043489995,taurus-9,1740659716
+1.0,3.394288977727013,22.669872321789406,52.0,26382.508623643633,484004.3081587353,0.0,2.071387778412336,15.772342214043363,0.0,10968.432552826956,307794.62907896977,8157721.0,6971378.659394632,2695088.048775141,61034420163,8755,875.3505131599995,taurus-9,1740660698
+0.0,2.0168587648374334,17.407116813464523,0.0,19054.634956132806,398090.34138318844,0.0,1.4234474453810424,12.210196226533055,0.0,8268.675812833304,261072.6930102664,6366798.0,5435351.325563393,1812922.9553006208,63191394511,11626,1162.4016219289988,taurus-9,1740663090
+1.0,2.765979381443299,21.55324578039364,52.0,26602.38670103093,474866.61893426825,1.0,2.0054639175257734,14.858506139676058,334.0,12765.199484536082,327677.90549314476,8156720.5,7042507.62113402,1894977.972401701,68312323925,9700,969.8006260559996,taurus-9,1740664269
+1.0,3.165424739195231,23.06494696509816,52.0,29597.25897053766,510991.5123024237,1.0,2.372348962512897,16.043396671774822,326.0,14205.240972142612,345292.3115615993,9174376.0,7865225.258626619,2239295.61652067,68608359931,8723,872.1204872130002,taurus-9,1740665257
+0.0,1.7978178879310345,14.974910089714303,0.0,15569.135573814656,367029.5763931015,0.0,1.123046875,9.638065910674703,0.0,6532.188644935345,221265.35117556667,5635763.5,4983071.07421875,1391048.0214707062,73988639310,14848,1484.6315204109997,taurus-9,1740667836

Data_analysis/Output_level_1/merged_mojitos_CPU_fedAvg2Clients_cifar10_epoch2.csv

+median_br0:rxp,mean_br0:rxp,std_br0:rxp,median_br0:rxb,mean_br0:rxb,std_br0:rxb,median_br0:txp,mean_br0:txp,std_br0:txp,median_br0:txb,mean_br0:txb,std_br0:txb,median_sum_package_dram_gpu,mean_sum_package_dram_gpu,std_sum_package_dram_gpu,sum_sum_package_dram_gpu,n_data,time (s),source,file_number
+1.0,2.2158233597977643,13.173923076152656,320.0,11631.111269107714,313473.30844870216,1.0,2.044199549709681,13.315643032617377,66.0,27604.713315163724,638988.0850051383,2732677.0,2867364.669826599,645692.0663839603,72593071346,25317,2531.5239593270016,taurus-1,1740614809
+2.0,3.004854368932039,17.521671866350342,624.0,14735.659893904514,367949.39859513915,2.0,2.50625563006706,15.221834808738048,132.0,34904.729806826144,745947.6182685541,2763559.5,2896104.2315083575,694949.0042239872,57869954754,19982,1998.0069508609995,taurus-1,1740617359
+2.0,3.356971442284617,19.104569649784693,640.0,17647.83945284377,390190.2241190755,2.0,2.9775617950563955,17.020430740302356,132.0,41809.75281977442,828991.2361160873,2765879.5,2909608.768178546,755321.5936424817,48497358948,16668,1666.6171998309983,taurus-1,1740619411
+2.0,3.727989311957248,21.447838547831775,640.0,19593.863994655978,427074.4303517899,2.0,3.3818971275885104,19.308739548423823,132.0,46533.41763527054,900578.2043873757,2826803.0,2959356.22004008,800325.1285808898,44301562614,14970,1496.8758792459994,taurus-1,1740621095
+1.0,2.1834916864608074,13.472619704089151,320.0,11650.82478226445,325143.70613094646,1.0,2.0366191607284243,12.824936749312636,66.0,27671.68903404592,617650.4765116507,2746302.5,2892915.0519002373,628071.3381492818,73075034211,25260,2525.8868231829983,taurus-1,1740622608
+2.0,2.8600520364254978,16.880761189918463,624.0,14729.919743820674,372903.1006742203,2.0,2.576903832682878,15.311382817149084,132.0,34955.09971980386,755733.4768458023,2736743.5,2865624.8438406885,704413.5908716493,57272378129,19986,1998.4668048079984,taurus-1,1740625153
+2.0,3.392343345572744,19.377478645852058,640.0,17711.625173057244,397979.02239126764,2.0,3.0592909167519413,17.725467166701453,132.0,41966.18816589418,845729.261047158,2762965.0,2911088.488412689,743212.2684044207,48361913058,16613,1661.1037117319975,taurus-1,1740627169
+2.0,5.111170497060396,22.523724546677286,640.0,19695.425440940675,432471.4257879962,2.0,3.326362907536077,18.98721269224592,132.0,46534.14290486371,906332.5305954132,2846768.5,2993207.168158739,795150.365801855,44802324893,14968,1496.603889623,taurus-1,1740639013
+0.0,1.2422578606414916,11.305841474800346,0.0,8782.734476220572,279481.3483813907,0.0,0.8160451888133986,7.398625092989429,0.0,3565.6000553009953,166705.08791591378,5796789.0,4995018.101872333,1515016.1966784233,126453878267,25316,2531.4898719269986,taurus-13,1740614809
+1.0,1.7520268241417276,14.342699956270957,52.0,11592.117205484936,314557.1355699233,0.0,1.1191572415173656,9.511535637060069,0.0,4951.0999399459515,202498.06953568655,7013576.0,5835246.576568912,1835423.9876619056,116599897093,19982,1998.0736686439996,taurus-13,1740617359
+1.0,1.8988420231595369,16.201867388648072,52.0,14432.631367372653,358217.29630947957,1.0,1.3990520189596207,11.17746535358456,334.0,6471.655786884262,234467.70233216917,8315564.0,6848539.74296514,2226357.0368346013,114144611896,16667,1666.5837924200023,taurus-13,1740619411
+1.0,2.1753507014028055,17.201378266971524,52.0,16628.709886439545,376954.02877057943,1.0,1.601068804275217,11.946547346961916,326.0,7810.965397461589,258383.41730993203,9377841.0,7930035.558917835,2495690.564136454,118712632317,14970,1496.8425170269984,taurus-13,1740621095
+0.0,1.330364212193191,11.736490280802691,0.0,9533.725653206651,284969.4537315273,0.0,0.9197941409342835,7.6176222204608575,0.0,4680.597189231988,187054.1275779646,6135616.0,5384850.90344418,1319806.1916269043,136021333821,25260,2525.8522862829996,taurus-13,1740622608
+0.0,1.5047533273291305,13.844827982611278,0.0,11119.541128790153,309057.4749753683,0.0,1.0467327128990294,9.131848694417847,0.0,4478.024617232062,193702.77663621452,6580692.0,5574988.529920945,1964779.4500100017,111421720759,19986,1998.433080742001,taurus-13,1740625153
+1.0,1.899590657356128,15.64848214720252,52.0,14480.308993498677,348223.5194929172,1.0,1.399048880327474,11.19340245151282,334.0,6491.45659764026,234870.12088727547,8358684.0,6820238.3419817,2297331.3387211408,113297799337,16612,1661.0696144190006,taurus-13,1740627169
+1.0,3.5193425536179594,19.03266383226039,52.0,16114.867241264114,378259.42838370294,1.0,1.5528161956303868,12.04840675047951,326.0,7224.255629050578,246115.98042800862,9354313.0,7570053.748446583,2693747.5268209744,113300994453,14967,1496.551525623,taurus-13,1740639013
+1.0,1.386830462948333,11.754313498024874,46.0,9882.615658081846,293011.6732575146,0.0,0.9673724127034287,7.874913477606617,0.0,5050.229459630274,206964.9359600238,5637717.0,4996236.305696002,1253098.9241146715,126484718315,25316,2531.484267836002,taurus-8,1740614809
+1.0,1.8402562306075467,14.004696706739509,52.0,12511.590781703533,326398.9971302605,1.0,1.2340606545891302,9.614881099501648,326.0,6351.687068361525,232794.69768110182,6570262.5,5732724.914823341,1614415.9967947449,114551309248,19982,1998.0687065129969,taurus-8,1740617359
+1.0,1.80819534437245,15.603785389083896,52.0,13878.885469162467,346504.27403430926,1.0,1.3479721622270218,10.825954076288694,326.0,6454.511219102472,219504.51599203984,7707465.0,5981535.546736261,2380340.285596422,99700234493,16668,1666.6781424619985,taurus-8,1740619411
+1.0,1.8992651970607883,16.527714537911596,52.0,14785.421309285237,359137.107904196,0.0,1.370741482965932,11.84718648858057,0.0,5926.628056112225,223800.54407950476,7802727.0,6379835.365731463,2893590.1684326236,95506135425,14970,1496.8365157000007,taurus-8,1740621095
+0.0,1.11298495645289,10.457622704843274,0.0,8072.70126682502,255935.36292938874,0.0,0.7463578780680918,7.265926914571757,0.0,2833.6237133808395,152189.776658346,4333143.0,4170808.525415677,1497692.1280891597,105354623352,25260,2525.8473350629974,taurus-8,1740622608
+1.0,1.61548083658561,13.756254010622282,52.0,12038.616531572101,311673.1902394839,0.0,1.1711197838486942,9.588299647724972,0.0,5880.35334734314,220765.87460534976,6534985.5,5503359.921445011,1765434.3586125076,109990151390,19986,1998.4280597610014,taurus-8,1740625153
+1.0,1.8425836744522033,15.748392967578189,52.0,13927.964363111005,347846.7288001317,1.0,1.3371057067180352,10.700092321158651,326.0,5928.368348182037,215069.22919297384,7704412.5,6014219.900794607,2338271.6318934564,99908220992,16612,1661.0648968429996,taurus-8,1740627169
+1.0,3.565711231375693,18.901669076558385,52.0,16726.19342553618,383947.0783067774,1.0,1.5999198236119463,12.167157077119054,326.0,7815.574530634061,258426.47781582846,8813632.0,7393630.193024654,2449701.884135601,110660463099,14967,1496.531739201,taurus-8,1740639013
+0.0,1.2414583086463642,11.099079355686037,0.0,8789.14855630604,267846.24939716706,0.0,0.8279416992534661,7.269099354194751,0.0,3567.8478887703914,167718.31327042545,5662273.0,4913289.651261997,1421560.2409701084,124389754101,25317,2531.5042575879997,taurus-9,1740614809
+0.0,1.6073770081577499,13.423014600021945,0.0,10672.405034783043,299689.04012771556,0.0,0.9960462439317351,8.985575939116043,0.0,4009.704219008058,182664.15439484775,6342491.0,5228148.104299084,1935422.8369934834,104463627272,19981,1997.98806263,taurus-9,1740617359
+1.0,1.751544969100618,15.207020056585144,52.0,13330.945041099178,329569.3499478821,0.0,1.2853542929141417,10.790207988843946,0.0,5344.660406791864,207705.6844905198,7348572.0,6136144.3354532905,2382124.15944156,102271117639,16667,1666.5975916129973,taurus-9,1740619411
+1.0,1.919505678022712,16.771188508920233,52.0,14788.99953239813,358310.89503694215,0.0,1.4268537074148298,12.093447814666828,0.0,6539.056112224449,232434.52391707915,8175419.5,6747339.910688043,2882502.8340023044,101007678463,14970,1496.8565976469981,taurus-9,1740621095
+1.0,1.3463182897862234,11.156531974276682,46.0,9905.770110847188,287193.95492446836,0.0,0.9560174188440221,7.613745811112403,0.0,4694.37181314331,194011.69791768212,6020654.0,5376228.625138559,1250325.2016714178,135803535071,25260,2525.865668221999,taurus-9,1740622608
+1.0,1.5515360752526768,13.78601507146962,50.0,11577.892925047534,319068.8585078996,0.0,1.1156809766836786,9.269885401698115,0.0,4952.6373461423,204133.2548361942,6849453.0,5682824.372310617,1812647.7739011594,113576927905,19986,1998.4482572670022,taurus-9,1740625153
+1.0,1.760654948230195,15.652320774596236,52.0,13374.290332289911,336397.94250978733,0.0,1.2952684806164219,11.070096185892035,0.0,5909.796532627017,223843.74370264442,7341165.0,6157453.2900915,2359772.6970425583,102287614055,16612,1661.0841772109998,taurus-9,1740627169
+1.0,3.155007683570522,18.224160635859363,50.0,13658.350504443108,350011.4065516234,0.0,1.2516870448319637,12.07835264537734,0.0,5280.384713035344,211023.16090424254,5579455.0,6058811.592971203,2923473.5182884983,90682233112,14967,1496.5385113739999,taurus-9,1740639013

Data_analysis/Output_level_1/merged_mojitos_CPU_fedAvg_cifar10_epoch1.csv

+median_br0:rxp,mean_br0:rxp,std_br0:rxp,median_br0:rxb,mean_br0:rxb,std_br0:rxb,median_br0:txp,mean_br0:txp,std_br0:txp,median_br0:txb,mean_br0:txb,std_br0:txb,median_sum_package_dram_gpu,mean_sum_package_dram_gpu,std_sum_package_dram_gpu,sum_sum_package_dram_gpu,n_data,time (s),source,file_number
+2.0,5.53448397323001,33.51453459581311,640.0,59148.0457907714,799651.5879323581,2.0,4.762522014793942,29.896732297444963,132.0,58966.055723846424,974693.728807338,2732037.0,2880891.7438534694,680525.1874910897,40894258304,14195,1419.3582625729996,taurus-1,1740648154
+2.0,4.75423197492163,27.069707136886738,640.0,38382.357008508734,633457.5912834388,2.0,4.1016569637259295,23.188522971002065,132.0,74467.93927451859,1166703.3251224856,2722072.0,2872768.0174652934,741841.8422835195,32074454915,11165,1116.3701770100006,taurus-1,1740649591
+3.0,5.719722825524873,29.240815384070903,960.0,43408.967111386904,684321.8958122374,3.0,4.692005378012204,24.313726608958905,198.0,85017.21532733478,1204310.70314925,2731897.0,2897251.039404282,787558.1195783843,28013520300,9669,966.7319621960005,taurus-1,1740650725
+3.0,6.605239179954442,31.968816248410054,960.0,47791.88735763098,674951.1290367256,3.0,5.137585421412301,26.28293700973111,198.0,93584.32072892938,1284903.2574564111,2856969.5,3012470.7564920275,844593.4802104111,26449493242,8780,877.8539180079988,taurus-1,1740651708
+2.0,4.1274226513496375,19.35924822802301,640.0,30374.667418422723,507837.6125852043,2.0,3.261540630065544,19.108640668667277,132.0,58662.44604975685,964104.3863206434,2720242.0,2858444.879836493,676783.6466107641,40558474400,14189,1418.7135488250005,taurus-1,1740652602
+3.0,5.9400664929463565,27.625153132272185,640.0,38725.145655494656,657636.1284366132,2.0,4.1225626740947074,22.079562573549786,132.0,74728.31808787852,1106919.381026506,2769724.0,2909452.803216821,730813.7297909246,32379300247,11129,1112.7494310309994,taurus-1,1740654039
+3.0,7.079975328947368,30.282009182125122,960.0,43221.27168996711,686377.2431466129,3.0,4.602796052631579,24.43103814732474,198.0,84475.56722861843,1217387.8238255493,2827993.0,2991570.8307976974,758331.6651786086,29102001042,9728,972.6986093270007,taurus-1,1740655170
+3.0,7.3606186793575255,30.787645265552307,960.0,51135.634146341465,683943.4718133908,3.0,5.434146341463415,27.357168341878218,198.0,98831.21475312315,1360118.3311766444,2834784.0,3010278.5112433075,839055.2245659683,25301390887,8405,840.3905075429993,taurus-1,1740656160
+1.0,4.848608665022895,38.38565827819016,52.0,75623.44564987671,974449.6950594313,0.0,3.2700246565692144,26.371288090051433,0.0,10985.900457907714,297193.8358677538,6203246.0,6003347.18090877,635042.9233709001,85217513233,14195,1419.3379249650006,taurus-13,1740648154
+1.0,2.553963278101209,18.955299056900238,52.0,24742.884191670397,454225.42532879236,1.0,1.77474249888043,12.42411028711641,334.0,13581.4381549485,334658.0836614778,7182139.0,6884413.369189431,833630.9376553295,76864475267,11165,1116.3500228619996,taurus-13,1740649591
+1.0,3.2750025855827904,21.596393127645268,52.0,28618.87010032061,500088.7361151009,1.0,2.0495397662633157,14.487119492883034,334.0,14715.223084083153,357519.08576054295,8380914.0,7701905.526838349,1397564.686938529,74469724539,9669,966.7134389740004,taurus-13,1740650725
+1.0,3.7396355353075172,24.37643055132777,52.0,31500.961275626425,533207.1701549651,1.0,2.3648063781321182,16.563609969153966,334.0,16192.18507972665,370930.1064740744,9396258.5,8550843.88929385,1814685.9711485226,75076409348,8780,877.8357446639984,taurus-13,1740651708
+1.0,2.6438539610938823,17.569668980004177,52.0,19605.34825204398,409319.6641664786,0.0,1.425359458697491,10.388044335709056,0.0,10126.584719481252,290869.53391799226,6191322.5,5984306.920848604,653771.4039116913,84905346593,14188,1418.6956305550011,taurus-13,1740652602
+1.0,3.804312668463612,20.291057165604425,52.0,25038.698652291107,464774.2088837962,1.0,1.8101527403414195,12.885506909797211,334.0,13626.045552560647,337628.3304674172,7172107.0,6893543.558490566,786661.8794995626,76725139806,11130,1112.829667893,taurus-13,1740654039
+1.0,4.694387335526316,23.707017104057822,52.0,28536.811060855263,501351.66900708346,1.0,2.086348684210526,14.834162483654866,334.0,14632.600637335527,358221.8318326011,8371355.0,7693321.444695723,1418150.0545813227,74840631014,9728,972.679988807,taurus-13,1740655170
+1.0,4.430339083878644,24.137921919163464,52.0,32945.35502676978,544865.5672718467,1.0,2.4105889351576444,16.12836735106342,334.0,16990.163712076144,376776.6499694326,9426118.0,8809835.209280191,1424940.1161014023,74046664934,8405,840.3723669349984,taurus-13,1740656160
+1.0,4.912357334084825,38.60632484008617,52.0,75613.3328166831,979185.4526491363,0.0,3.2846977596167393,26.43099268860851,0.0,10345.73214034099,293782.91319176974,5643149.0,5491302.621389319,527840.2956244576,77943549408,14194,1419.277612455001,taurus-8,1740648154
+1.0,2.5708527409530633,19.7671497494285,52.0,24745.343067001075,470157.08674038283,1.0,1.7903081332855608,12.509389508833953,334.0,12767.535112862774,316817.497780811,6610414.5,6359300.095933357,726257.7806334582,70995226271,11164,1116.2901734980005,taurus-8,1740649591
+1.0,3.227554820024824,20.852859967928485,52.0,27683.757964418703,472987.39927539957,1.0,2.0495448903599502,14.081606384111199,334.0,13763.821162598262,334796.0225986697,7802483.5,6940234.794993794,1631807.553744756,67098189998,9668,966.6530802799989,taurus-8,1740650725
+1.0,3.635990888382688,23.01012477140418,52.0,30457.450455580867,508901.6406394727,1.0,2.265148063781321,15.597543826707959,326.0,15135.6215261959,364256.4468531059,8796877.5,7760685.840888383,1995147.6084690716,68138821683,8780,877.875113258,taurus-8,1740651708
+1.0,2.5972936782014235,16.540436939080394,52.0,19660.793642962857,408249.5560218505,0.0,1.3959405173021355,10.137932319099352,0.0,10078.423497075199,291879.6331892237,5633484.0,5492163.439777292,518840.6438951562,77928307047,14189,1418.7352905349999,taurus-8,1740652602
+1.0,3.8224458621619193,20.74364937296179,52.0,25017.32985892713,462925.43975430215,1.0,1.797106658280169,12.79658173922624,334.0,12806.944649114925,318964.9347788608,6619820.0,6363713.951208554,748262.9971745874,70821772563,11129,1112.7700527460001,taurus-8,1740654039
+1.0,4.648268064549286,22.629780075604785,52.0,28535.012539829375,483840.7069791572,1.0,2.071230342275671,14.661278515987465,334.0,15567.250693802036,359179.16665671906,7843191.0,7143909.1104943985,1444749.4431293204,69503091736,9729,972.7198729510001,taurus-8,1740655170
+1.0,4.451820128479658,24.225006099928777,52.0,32944.05769688318,541483.0418945701,1.0,2.40756602426838,15.839016423416446,334.0,16909.509279086367,371008.70289550937,8843636.5,8328280.60206995,1177938.044878209,70007526741,8406,840.4114954839988,taurus-8,1740656160
+1.0,4.8970059880239525,38.66001956878257,52.0,75607.52441000352,971360.3963997678,0.0,3.250651637900669,25.855093344872753,0.0,10345.868122578373,282079.5073778094,6028970.0,5865716.605988024,561579.4656696152,83263847222,14195,1419.3083515850003,taurus-9,1740648154
+1.0,2.640752351097179,20.521148256580673,52.0,24745.573130317956,464198.83263675607,1.0,1.839319301388267,13.168300301184228,334.0,12770.159695476937,328163.78062291903,6990957.0,6710285.364084192,795159.4502727122,74920336090,11165,1116.3215785030006,taurus-9,1740649591
+1.0,3.3499172527927183,21.502272006737396,52.0,28635.530409598676,489450.53655508056,1.0,2.1151220521307406,14.89543870633775,334.0,15667.800268928424,357130.0621313397,8211482.5,7520312.791994208,1429450.8149754528,72706384073,9668,966.6840179009996,taurus-9,1740650725
+1.0,3.7199316628701595,24.300174850690265,52.0,31500.46298405467,533202.7803470228,1.0,2.352391799544419,16.54068392868988,334.0,17231.866628701595,383157.205890854,9210545.0,8391378.511731207,1725773.9908057563,73676303333,8780,877.8051079939996,taurus-9,1740651708
+1.0,2.5917676910064844,16.391870479286577,52.0,19648.684592613477,401188.3171946751,0.0,1.4055539892867213,10.514958422505906,0.0,10721.72610656893,306391.46706006996,6013689.0,5856122.264730758,559160.4111032072,83086662692,14188,1418.6655914910007,taurus-9,1740652602
+1.0,3.784097035040431,20.255866642800356,52.0,25012.91078167116,466208.5444839929,1.0,1.7718778077268644,12.641243693562371,334.0,12804.275831087152,330273.7753662446,6983145.0,6717945.106469003,766300.8956257717,74770729035,11130,1112.8006764210004,taurus-9,1740654039
+1.0,4.602487664473684,22.629592798297757,52.0,27601.275287828947,477538.8837406704,1.0,2.0704152960526314,14.483310962800378,334.0,13684.159539473685,335104.957975624,8151312.0,7304307.035773027,1605233.7750071897,71056298844,9728,972.6502847289994,taurus-9,1740655170
+1.0,4.457346817370612,24.14537312144851,52.0,32948.74039262344,531581.0190705499,1.0,2.4378346222486615,16.265514574489565,334.0,17997.04556811422,395592.0106105163,9215389.0,8620169.412135633,1369375.6531071002,72452523909,8405,840.3422266060006,taurus-9,1740656160

Data_analysis/Output_level_1/merged_mojitos_CPU_fedAvg_cifar10_epoch2.csv

+median_br0:rxp,mean_br0:rxp,std_br0:rxp,median_br0:rxb,mean_br0:rxb,std_br0:rxb,median_br0:txp,mean_br0:txp,std_br0:txp,median_br0:txb,mean_br0:txb,std_br0:txb,median_sum_package_dram_gpu,mean_sum_package_dram_gpu,std_sum_package_dram_gpu,sum_sum_package_dram_gpu,n_data,time (s),source,file_number
+2.0,3.8244670409485297,24.168637823953038,640.0,32931.89576380982,573078.7094264233,2.0,3.4577755094028504,22.550382745692865,132.0,32785.57143418005,704626.7734599726,2748912.0,2885638.8041301873,643444.3029302896,73500105980,25471,2546.9359785009997,taurus-1,1740599436
+2.0,3.7495012532610366,17.74063171624066,640.0,22266.178986137398,433227.15449027164,2.0,3.3508619366719525,16.77678239596953,132.0,42884.76305693386,842645.2782605692,2778923.0,2909639.3940355005,696008.1314032808,56880540514,19549,1954.750604148,taurus-1,1740602002
+3.0,4.41645182564902,21.3974283870018,960.0,25549.01546855327,469783.92361883086,3.0,3.9686432040290187,19.69206001181787,198.0,49691.17908747527,960623.2768695961,2788186.0,2931650.516997422,751733.6484888885,48896998973,16679,1667.728586395,taurus-1,1740603975
+3.0,4.962525977073138,25.269361507598255,960.0,28494.325534624924,538454.4684006227,3.0,4.3410873500033516,20.906774625278263,198.0,55510.60957297044,1022645.9079623341,2853521.0,3000744.3146745325,784700.8160223875,44762102942,14917,1491.5792600800005,taurus-1,1740605660
+2.0,3.005788594023888,15.8049582466432,640.0,17811.526354408707,397253.45215213386,2.0,2.761037055154702,14.85660114574128,132.0,34238.85683420978,734812.3771728764,2771449.0,2896843.650483062,635411.2469782182,71062471590,24531,2452.926396263001,taurus-1,1740607169
+2.0,3.605437797147385,18.63291321964332,640.0,21091.45963748019,436294.7508842577,2.0,3.213698494453249,16.74516702340686,132.0,41052.69978209192,837680.9709980398,2771699.5,2903406.4800911252,691386.4420920644,58625583646,20192,2019.0810878889988,taurus-1,1740609641
+3.0,4.512332801570745,21.958167848119142,960.0,26702.708798625597,488251.6796037418,3.0,3.99668671002577,19.29486834876262,198.0,51391.95361394036,971352.3104471535,2823174.0,2972995.3694318323,725908.9818582875,48453878531,16298,1629.6092822249993,taurus-1,1740611679
+3.0,5.03117719610799,24.281319122479232,960.0,29762.606002466768,548967.9138792179,3.0,4.584007126216253,21.626878824830847,198.0,57375.50280937371,1050897.350406317,2899660.5,3054905.042414691,778016.4052331271,44583284189,14594,1459.2962910450005,taurus-1,1740613326
+1.0,3.0196686557788945,29.51856323067415,52.0,42216.076515389446,739714.2825744735,1.0,2.1177371231155777,20.195335903534676,326.0,6298.001256281407,223183.45576017658,6218384.0,6052924.672620917,676644.7839244473,154180097261,25472,2547.001483815,taurus-13,1740599436
+1.0,1.9164705882352941,14.874186496518844,52.0,14190.471969309463,354933.47038444725,1.0,1.400153452685422,9.677760141667184,334.0,7929.125063938619,253351.52174700375,7228370.5,7048095.340255754,627129.9373665968,137790263902,19550,1954.817601137,taurus-13,1740602002
+1.0,2.2614665147790634,16.94636252456053,52.0,16632.771269260746,376057.7362046017,1.0,1.7122129624078182,11.861708192782478,334.0,9284.751124168115,278657.97514903435,8447744.0,8004225.881407758,1166524.3231149549,133502483476,16679,1667.7958132820004,taurus-13,1740603975
+1.0,2.4715425353623384,18.262531505046017,52.0,18535.543742039285,404804.93879901303,1.0,1.829858550646913,12.720836013374253,334.0,10343.129047395589,291223.40417826595,9485990.0,8993037.142052691,1407047.4388659992,134149135048,14917,1491.5479005809993,taurus-13,1740605660
+1.0,1.5566018507194979,12.342737868120523,52.0,11307.646488117076,313578.06150461035,1.0,1.1202967673555908,8.048213876741212,326.0,6367.593860829155,225875.12616356206,6231367.0,6130286.117320941,512095.22999744915,150382048744,24531,2452.992475039,taurus-13,1740607169
+1.0,1.8624702852614896,15.057749727388407,52.0,13736.746830427892,345610.81620099384,1.0,1.3640550713153725,9.692618281412075,334.0,7231.577852614897,241365.11988310405,7217048.5,6923592.998761886,927550.50379287,139801189831,20192,2019.048338523,taurus-13,1740609641
+1.0,2.231024114867767,16.938779849109647,52.0,17013.833895809046,381889.8896233007,1.0,1.6949131742038412,11.6526261372632,334.0,8926.234337608148,274359.3084076378,8432516.0,8110258.935202798,893053.6585443255,132172889867,16297,1629.5762546859987,taurus-13,1740611679
+1.0,2.4702295306611854,18.613024757084954,52.0,18940.91291538198,412666.7342859388,1.0,1.8605686879068175,12.74632923450345,334.0,9944.686125385406,292021.4239199468,9477173.0,9115015.741007194,1102261.2835223684,133033654740,14595,1459.3638350619985,taurus-13,1740613326
+1.0,2.9714981155778895,28.370150293017147,52.0,42149.74250157035,726363.8874696736,1.0,2.0949277638190953,19.719829517694734,326.0,5913.267313128141,214242.07840053603,5671421.5,5506634.769590138,686249.0098939148,140265000851,25472,2547.008503356,taurus-8,1740599436
+1.0,1.9093606138107417,14.786220894967855,52.0,14189.202250639386,356423.6991648086,1.0,1.403222506393862,9.585235539299953,334.0,7502.579130434782,245556.9848548439,6672576.0,6484287.988235294,641171.3990367145,126767830170,19550,1954.8116429950005,taurus-8,1740602002
+1.0,2.246957251633791,16.58903413910336,52.0,16632.422927033997,373184.57759316504,1.0,1.678757719287727,11.354846230100097,334.0,8733.701241081599,268470.4816288214,7884359.0,7433316.683314348,1189423.7123327074,123980288961,16679,1667.7897644619998,taurus-8,1740603975
+1.0,2.4644365489039353,18.051333909503448,52.0,18535.152443520816,398161.34342096833,1.0,1.8078031775826238,12.317071167150107,334.0,9731.715492391231,289344.03741965676,8913724.0,8446394.887712006,1339303.0687118724,125994872540,14917,1491.5408788700006,taurus-8,1740605660
+1.0,1.5430271900860135,12.360526137353867,52.0,11310.421099832865,319322.0351879048,1.0,1.1107578166401695,7.879633815536489,326.0,6016.13277077983,223735.63344342608,5672177.0,5594926.162162162,437525.82349229313,137249133684,24531,2452.9865006969994,taurus-8,1740607169
+1.0,1.786648177496038,14.306065410189161,52.0,13281.122226624406,333120.6008220914,1.0,1.3012083993660857,9.402247653291987,334.0,6766.0231279714735,238002.89897937299,6601739.5,6147963.40625,1220575.5348141128,124139677099,20192,2019.0434779860007,taurus-8,1740609641
+1.0,2.2098545744615574,16.620648849353,52.0,17009.42952690679,384535.69832260493,1.0,1.68319322574707,11.32959847411708,334.0,9484.444498987543,285909.7108435579,7851477.0,7569219.59888323,776545.4584071952,123355571803,16297,1629.571087395001,taurus-8,1740611679
+1.0,2.4672833162041794,18.08252580062035,52.0,18941.1892428914,404052.5824612288,1.0,1.8607057211373759,12.662743013381112,334.0,10570.020075368277,302104.87028997845,8907940.0,8580996.978280233,985050.4677243296,125239650898,14595,1459.3563501139997,taurus-8,1740613326
+1.0,2.980880216717051,28.966525288775706,52.0,41795.1792626909,722866.9650123473,0.0,2.102783557771583,19.819145891810518,0.0,5548.170743198147,210369.17186977877,6044380.0,5707761.261238271,947594.4362653604,145382387085,25471,2546.92455972,taurus-9,1740599436
+1.0,1.9067519181585677,14.579984150729773,52.0,14187.077340153453,350040.2241099685,1.0,1.376777493606138,9.430151308167085,334.0,7461.560255754475,239344.75132477895,7060717.0,6853939.915703325,699441.1643769611,133994525352,19550,1954.8309366189997,taurus-9,1740602002
+1.0,2.2012589928057555,16.631522865467815,52.0,16084.682074340528,372894.04337436456,1.0,1.6417865707434052,11.535581864188384,334.0,8244.07170263789,264699.1319416775,8215456.0,7509749.461870504,1595809.7139113348,125262621024,16680,1667.809705775,taurus-9,1740603975
+1.0,2.4049741905208823,18.53382995235487,52.0,17923.64992961051,401363.30901376315,1.0,1.7639605818864383,12.458388516822588,334.0,9103.039217000738,274652.6382660044,9256449.0,8462112.586444996,1859629.2069618409,126229333452,14917,1491.5610425570003,taurus-9,1740605660
+1.0,1.5406220700338347,12.128548240991108,52.0,11325.127797480738,310245.87833176844,1.0,1.119929884635767,8.106328566769648,326.0,5991.194610900493,225300.59240316146,6060966.0,5961098.812115283,509773.05148983473,146231714960,24531,2452.9069978919997,taurus-9,1740607169
+1.0,1.8591521394611727,14.76327229108632,52.0,13734.44388866878,337433.4486510534,1.0,1.3631141045958794,9.500072719419885,334.0,7684.1329239302695,245271.54119592436,7040170.5,6720951.65104992,980690.5625065151,135709455738,20192,2019.0621020229992,taurus-9,1740609641
+1.0,2.2069092471006932,16.764925687575822,52.0,17010.475547646805,385749.545063475,1.0,1.6655212615818862,11.281770054686412,334.0,8924.445603485305,272756.951616049,8255448.0,7888459.206050193,1004952.520604111,128558219681,16297,1629.5899190149994,taurus-9,1740611679
+1.0,2.4552243919150394,17.879485346086696,52.0,18941.772730387118,401269.0537048071,1.0,1.850702295306612,12.434660476409992,334.0,9944.898937992462,281751.59258028626,9273828.0,8921474.240767386,1064920.4452283015,130208916544,14595,1459.3776444750001,taurus-9,1740613326

Data_analysis/Output_level_1/merged_mojitos_GPU_fedAvg_cifar10_1ep.csv

+median_br0:rxp,mean_br0:rxp,std_br0:rxp,median_br0:rxb,mean_br0:rxb,std_br0:rxb,median_br0:txp,mean_br0:txp,std_br0:txp,median_br0:txb,mean_br0:txb,std_br0:txb,median_sum_package_dram_gpu,mean_sum_package_dram_gpu,std_sum_package_dram_gpu,sum_sum_package_dram_gpu,n_data,time (s),source,file_number
+1.0,14.103631532329494,58.91054079423121,84.0,183550.4539415412,1446944.1692600143,0.0,13.104517271922054,56.816190093733965,0.0,361758.47829938,2737153.259944118,9666834.5,10563156.515943313,2019366.0773153293,23851607413,2258,225.63197398400007,chifflot-3,1745614548
+1.0,12.95837023914969,81.05480974562059,46.0,191304.4171833481,1923058.7216902256,0.0,9.574844995571302,53.80772745190242,0.0,144790.94641275465,1684141.1771233152,19597046.0,17742305.928697962,3830293.160085361,40062126787,2258,225.65121245900082,chifflot-4,1745614548
+1.0,12.992471213463242,81.6607603674402,46.0,191722.72852081488,1951263.573425421,0.0,9.696634189548273,54.62331309405958,0.0,148817.99291408327,1766508.5325936382,19282643.5,19348562.801151462,1216572.4513092958,43689054805,2258,225.68102416999864,chifflot-5,1745614548
+1.0,15.130203720106289,74.32176784131397,46.0,194555.4769707706,1354631.226687757,0.0,11.854295837023916,60.39185680482295,0.0,141053.9016829052,1745517.4615506686,18352938.0,16676219.638618246,3785847.784582731,37654903944,2258,225.60727545999907,chifflot-6,1745614548

Data_analysis/Output_level_1/merged_mojitos_GPU_fedAvg_cifar10_2ep.csv

+median_br0:rxp,mean_br0:rxp,std_br0:rxp,median_br0:rxb,mean_br0:rxb,std_br0:rxb,median_br0:txp,mean_br0:txp,std_br0:txp,median_br0:txb,mean_br0:txb,std_br0:txb,median_sum_package_dram_gpu,mean_sum_package_dram_gpu,std_sum_package_dram_gpu,sum_sum_package_dram_gpu,n_data,time (s),source,file_number
+4.0,12.75224646983312,57.22978586204317,1248.0,134175.11392811296,1255193.9048849207,4.0,11.769897304236201,52.03816359888062,264.0,262819.83793324773,2402006.9001791864,9672189.0,10571371.541078305,2075933.0480438648,32940393722,3116,311.50308402099836,chifflot-3,1745616801
+1.0,10.602823227462304,73.48779359304818,80.0,138595.81488610845,1670413.2031094485,1.0,7.913057427013154,48.80480836125993,326.0,108368.3429579724,1466121.1536690597,20244531.0,18710489.609881297,3472212.876860607,58320596114,3117,311.53598861700084,chifflot-4,1745616801
+1.0,14.061276868784088,96.863125668579,52.0,203623.63811357075,2093854.4159676265,1.0,9.691369906961823,61.06604596488249,326.0,105739.93455245429,1444228.1283335113,19561848.0,18074420.07603465,3205157.3214724497,56337967377,3117,311.55587410299995,chifflot-5,1745616801
+1.0,8.454924606993904,48.349454415412616,52.0,95804.40744305422,1039046.4304033855,1.0,6.907924286172602,40.810288471713335,326.0,102164.60410651268,1479296.0486572746,19168983.0,17342308.61533526,3618071.7383206096,54055975954,3117,311.59863300899815,chifflot-6,1745616801

Data_analysis/Output_level_1/merged_power_CPU_fedAvg2Clients_cifar10_epoch1.csv

+median_power,mean_power,std_power,n_data,source,time (s),file_number
+88.28891941391942,89.11319865011129,3.31956915870957,1486,taurus-1,1485.0,1740657023
+83.8720099667774,85.72578408580384,10.112710712600247,1486,taurus-13,1485.0,1740657023
+117.81708494208496,113.3494308204125,10.03826720645656,1486,taurus-8,1485.0,1740657023
+118.24557692307688,114.36777154132545,9.835618268367092,1486,taurus-9,1485.0,1740657023
+87.95833806012479,89.01708526780601,3.971917734109138,1176,taurus-1,1175.0,1740658525
+101.7917877906977,96.33376524932488,12.653334927204432,1176,taurus-13,1175.0,1740658525
+123.54022727272726,117.32059371775149,14.981830090722173,1176,taurus-8,1175.0,1740658525
+123.63934252386002,115.83992747279262,16.002849210543474,1176,taurus-9,1175.0,1740658525
+88.41136363636363,89.61634007423639,4.425932671005863,967,taurus-1,966.0,1740659716
+109.27555555555557,102.5194728169787,16.274782818959384,967,taurus-13,966.0,1740659716
+129.71499999999997,119.79545352984917,20.78470015812876,967,taurus-8,966.0,1740659716
+134.54500000000002,127.06859099446226,19.74334943746459,967,taurus-9,966.0,1740659716
+89.24069264069266,90.6337145525615,4.499065511928424,876,taurus-1,875.0,1740660698
+115.40163285502229,106.38526550023565,21.22300893821943,876,taurus-13,875.0,1740660698
+139.6640873015873,130.87189229022255,24.733505287687954,876,taurus-8,875.0,1740660698
+140.69,131.8129094189385,24.781439730616412,876,taurus-9,875.0,1740660698
+87.79230769230767,88.8942121951908,3.7466841305347227,1165,taurus-1,1164.0,1740663090
+99.91500000000002,94.90231721265255,12.924919202356177,1165,taurus-13,1164.0,1740663090
+123.82222222222224,118.2538629849265,14.742273845989912,1165,taurus-8,1164.0,1740663090
+123.54146341463414,116.34957550888468,15.698191089661206,1165,taurus-9,1164.0,1740663090
+88.41052631578948,89.68377427134811,4.045268976300711,973,taurus-1,972.0,1740664269
+105.2913043478261,98.96352628015055,17.64288232631305,973,taurus-13,972.0,1740664269
+128.36222222222221,118.94268470188682,20.745255515338464,973,taurus-8,972.0,1740664269
+142.13829787234044,131.5458377475236,17.086760330909442,973,taurus-9,972.0,1740664269
+88.2861111111111,89.47810642786952,4.512911177591982,873,taurus-1,872.0,1740665257
+118.25,110.18241534060873,19.045573462638124,873,taurus-13,872.0,1740665257
+100.85000000000004,115.71942094670052,25.30419208904311,873,taurus-8,872.0,1740665257
+153.5190476190476,140.19289373228992,20.88110346657317,873,taurus-9,872.0,1740665257
+87.80967365967366,88.73194993516177,3.176323875050475,1486,taurus-1,1486.0,1740667836
+92.73820346320343,89.23946166710557,9.607651979208953,1486,taurus-13,1486.0,1740667836
+114.6601291989664,110.50929856662268,10.724358035149283,1486,taurus-8,1486.0,1740667836
+116.45611111111111,111.6266842904531,11.238498765702198,1486,taurus-9,1486.0,1740667836