diff --git a/lang/fr/gklearn/experiments/papers/PRL_2020/runtimes_28cores.py b/lang/fr/gklearn/experiments/papers/PRL_2020/runtimes_28cores.py
new file mode 100644
index 0000000..4c827ce
--- /dev/null
+++ b/lang/fr/gklearn/experiments/papers/PRL_2020/runtimes_28cores.py
@@ -0,0 +1,57 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Mon Sep 21 10:34:26 2020
+
+@author: ljia
+"""
+from utils import Graph_Kernel_List, Dataset_List, compute_graph_kernel
+from gklearn.utils.graphdataset import load_predefined_dataset
+import logging
+
+
+def xp_runtimes_of_all_28cores():
+		
+	# Run and save.
+	import pickle
+	import os
+	save_dir = 'outputs/runtimes_of_all_28cores/'
+	if not os.path.exists(save_dir):
+		os.makedirs(save_dir)
+
+	run_times = {}
+	
+	for kernel_name in Graph_Kernel_List:
+		print()
+		print('Kernel:', kernel_name)
+		
+		run_times[kernel_name] = []
+		for ds_name in Dataset_List:
+			print()
+			print('Dataset:', ds_name)
+			
+			# get graphs.
+			graphs, _ = load_predefined_dataset(ds_name)
+
+			# Compute Gram matrix.
+			run_time = 'error'
+			try:
+				gram_matrix, run_time = compute_graph_kernel(graphs, kernel_name, n_jobs=28)
+			except Exception as exp:
+				print('An exception occured when running this experiment:')
+				LOG_FILENAME = save_dir + 'error.txt'
+				logging.basicConfig(filename=LOG_FILENAME, level=logging.DEBUG)
+				logging.exception('')
+				print(repr(exp))
+			run_times[kernel_name].append(run_time)
+			
+			pickle.dump(run_time, open(save_dir + 'run_time.' + kernel_name + '.' + ds_name + '.pkl', 'wb'))
+		
+	# Save all.	
+	pickle.dump(run_times, open(save_dir + 'run_times.pkl', 'wb'))	
+	
+	return
+
+
+if __name__ == '__main__':
+	xp_runtimes_of_all_28cores()