Extract acceleration data from perf tests table

Author: aobolensk

scoreboard/main.py

@@ -2,6 +2,7 @@
 from collections import defaultdict
 import argparse
 import yaml
+import csv
 
 task_types = ['all', 'mpi', 'omp', 'seq', 'stl', 'tbb']
 
@@ -64,6 +65,27 @@
         </tr>
 """
 
+
+perf_stat_file_path = Path(__file__).parent.parent / "build" / "perf_stat_dir" / "task_run_perf_table.csv"
+
+# Read and parse performance statistics CSV
+perf_stats = dict()
+if perf_stat_file_path.exists():
+    with open(perf_stat_file_path, 'r', newline='') as csvfile:
+        reader = csv.DictReader(csvfile)
+        for row in reader:
+            perf_stats[row[0]] = {
+                "seq": row[1],
+                "omp": row[2],
+                "tbb": row[3],
+                "stl": row[4],
+                "all": row[5],
+                "mpi": "N/A",
+            }
+else:
+    print(f"Warning: Performance stats CSV not found at {perf_stat_file_path}")
+
+
 for dir in sorted(directories.keys()):
     html_content += f"<tr><td>{dir}</td>"
     total_count = 0
@@ -78,7 +100,12 @@
             task_count += max_sol_points
         else:
             html_content += '<td style="text-align: center;">0</td>'
-        html_content += '<td style="text-align: center;background-color: lavender;">0</td>'
+        html_content += '<td style="text-align: center;background-color: lavender;">'
+        if row[0] in perf_stats.keys():
+            html_content += perf_stats[row[0]][task_type]
+        else:
+            html_content += '?'
+        html_content += '</td>'
         html_content += '<td style="text-align: center;background-color: lavender;">0</td>'
         html_content += '<td style="text-align: center;">0</td>'
         is_cheated = \

scripts/create_perf_table.py

@@ -2,6 +2,7 @@
 import os
 import re
 import xlsxwriter
+import csv
 
 parser = argparse.ArgumentParser()
 parser.add_argument('-i', '--input', help='Input file path (logs of perf tests, .txt)', required=True)
@@ -102,3 +103,20 @@
         it_i = 1
         it_j += 1
     workbook.close()
+    # Dump CSV for performance times
+    csv_file = os.path.join(xlsx_path, table_name + '_perf_table.csv')
+    with open(csv_file, 'w', newline='') as csvfile:
+        writer = csv.writer(csvfile)
+        # Write header: Task, SEQ, OMP, TBB, STL, ALL
+        writer.writerow(['Task', 'SEQ', 'OMP', 'TBB', 'STL', 'ALL'])
+        for task_name in sorted(result_tables[table_name].keys()):
+            seq_time = result_tables[table_name][task_name]['seq']
+            row = [
+                task_name,
+                1.0 if seq_time != 0 else '?',
+                (result_tables[table_name][task_name]['omp'] / seq_time) if seq_time != 0 else '?',
+                (result_tables[table_name][task_name]['tbb'] / seq_time) if seq_time != 0 else '?',
+                (result_tables[table_name][task_name]['stl'] / seq_time) if seq_time != 0 else '?',
+                (result_tables[table_name][task_name]['all'] / seq_time) if seq_time != 0 else '?',
+            ]
+            writer.writerow(row)