ADD: feedback edges have different datatype to avoid collision with not feedback edges

simulation/scripts/Detailed_gem5_results.ipynb

@@ -0,0 +1,105 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "f7776815",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "\n",
+    "folder = \"/home/sfischer/Documents/projects/wk_LinProg/simulation/results/log_raw\"\n",
+    "txt_files = [f for f in os.listdir(folder) if f.endswith('.txt')]\n",
+    "\n",
+    "if len(txt_files) == 0:\n",
+    "    raise FileNotFoundError(\"No .txt files found in the folder.\")\n",
+    "elif len(txt_files) > 1:\n",
+    "    raise RuntimeError(f\"Multiple .txt files found: {txt_files}\")\n",
+    "\n",
+    "    # Do something with 'content'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "63d802a8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "     timestamp  src_task  dst_task  compute_time  from_time  to_time\n",
+      "0    101981000        70         0             0     101981   101981\n",
+      "1    101981000        71        10             0     101981   101981\n",
+      "2    101981000        72        12             0     101981   101981\n",
+      "3    101981000        73        17             0     101981   101981\n",
+      "4    101981000        74        26             0     101981   101981\n",
+      "..         ...       ...       ...           ...        ...      ...\n",
+      "113  123135000        60        61           483     123135   123618\n",
+      "114  123188000        65        66           563     123188   123751\n",
+      "115  123618000        61        69           644     123618   124262\n",
+      "116  123751000        66        69           644     123751   124395\n",
+      "117  124403000        69        56           211     124403   124614\n",
+      "\n",
+      "[118 rows x 6 columns]\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "import pandas as pd\n",
+    "import re\n",
+    "data = []\n",
+    "file_path = os.path.join(folder, txt_files[0])\n",
+    "with open(file_path, 'r') as f:\n",
+    "\n",
+    "    for line in f:\n",
+    "        if \"compute time\" in line:\n",
+    "            numbers = re.findall(r'\\d+', line)\n",
+    "            # print(f\"Found numbers: {numbers}\")\n",
+    "\n",
+    "            # Assigning numbers to variables based on their position\n",
+    "            timestamp = int(numbers[0])\n",
+    "            src_task = int(numbers[2])\n",
+    "            dst_task = int(numbers[3])\n",
+    "            compute_time = int(numbers[4])\n",
+    "            from_time = int(numbers[5])\n",
+    "            to_time = int(numbers[6])\n",
+    "            print(line)\n",
+    "            print(f\"timestamp: {timestamp}\")\n",
+    "            print(f\"src_task: {src_task}\")\n",
+    "            print(f\"dst_task: {dst_task}\")\n",
+    "            print(f\"compute_time: {compute_time}\")\n",
+    "            print(f\"from_time: {from_time}\")\n",
+    "            print(f\"to_time: {to_time}\")\n",
+    "            data.append([timestamp, src_task, dst_task, compute_time, from_time, to_time])\n",
+    "\n",
+    "df = pd.DataFrame(data, columns=[\"timestamp\", \"src_task\", \"dst_task\", \"compute_time\", \"from_time\", \"to_time\"])\n",
+    "print(df)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "env",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

simulation/scripts/getResults.py

@@ -0,0 +1,30 @@
+import csv
+import sys
+
+def main(filename):
+    min_start = None
+    max_finish = None
+
+    with open(filename, newline='') as csvfile:
+        reader = csv.reader(csvfile)
+        header = next(reader)  # Skip header
+
+        for row in reader:
+            if len(row) < 3:
+                continue  # Skip malformed rows
+            start = int(row[1].strip())
+            finish = int(row[2].strip())
+
+            if min_start is None or start < min_start:
+                min_start = start
+            if max_finish is None or finish > max_finish:
+                max_finish = finish
+
+    print(f"Min start time: {min_start}")
+    print(f"Max finish time: {max_finish}")
+
+if __name__ == "__main__":
+    if len(sys.argv) != 2:
+        print("Usage: python getResults.py <csv_file>")
+    else:
+        main(sys.argv[1])