diff --git a/benchmarks/benchmark-plotters/plot-perf-peakthroughput.py b/benchmarks/benchmark-plotters/plot-perf-peakthroughput.py
index a0c4bde..3cec68d 100644
--- a/benchmarks/benchmark-plotters/plot-perf-peakthroughput.py
+++ b/benchmarks/benchmark-plotters/plot-perf-peakthroughput.py
@@ -7,6 +7,8 @@ import matplotlib.pyplot as plt
 
 from common import calc_throughput
 
+folder_path = "benchmark-results/"
+
 runid = "Run ID"
 x_label = "Destination Node"
 y_label = "Source Node"
@@ -18,6 +20,8 @@ title_allnodes = \
 title_smartnodes = \
     """Copy Throughput in GiB/s tested for 1GiB Elements\n
     Using Cross-Copy for Intersocket and all 4 Chiplets of Socket for Intrasocket"""
+title_difference = \
+    """Gain in Copy Throughput in GiB/s of All-DSA vs. Smart Assignment"""
 
 description_smartnodes = \
     """Copy Throughput in GiB/s tested for 1GiB Elements\n
@@ -68,15 +72,23 @@ def process_file_to_dataset(file_path, src_node, dst_node):
         return
 
 
+def plot_heatmap(table,title,node_config):
+    plt.figure(figsize=(8, 6))
+
+    sns.heatmap(table, annot=True, cmap="YlGn", fmt=".0f")
+
+    plt.title(title)
+    plt.savefig(os.path.join(folder_path, f"plot-perf-{node_config}-throughput.png"), bbox_inches='tight')
+    plt.show()
+
+
 # loops over all possible configuration combinations and calls
 # process_file_to_dataset for them in order to build a dataframe
 # which is then displayed and saved
 def main(node_config,title):
-    folder_path = "benchmark-results/"
-
     for src_node in range(16):
         for dst_node in range(16):
-            size = "512mib" if src_node == dst_node and src_node >= 8 else "1gib" 
+            size = "512mib" if node_config == "allnodes" and src_node == dst_node and src_node >= 8 else "1gib" 
             file = os.path.join(folder_path, f"copy-n{src_node}ton{dst_node}-{size}-{node_config}-1e.json")
             process_file_to_dataset(file, src_node, dst_node)
 
@@ -85,15 +97,14 @@ def main(node_config,title):
     data.clear()
     df.set_index(index, inplace=True)
     data_pivot = df.pivot_table(index=y_label, columns=x_label, values=v_label)
-    plt.figure(figsize=(8, 6))
 
-    sns.heatmap(data_pivot, annot=True, cmap="rocket_r", fmt=".0f")
+    plot_heatmap(data_pivot, title, node_config)
 
-    plt.title(title)
-    plt.savefig(os.path.join(folder_path, f"plot-perf-{node_config}-throughput.png"), bbox_inches='tight')
-    plt.show()
+    return data_pivot
 
 
 if __name__ == "__main__":
-    main("allnodes", title_allnodes)
-    main("smart", title_smartnodes)
\ No newline at end of file
+    dall = main("allnodes", title_allnodes)
+    dsmart = main("smart", title_smartnodes)
+    ddiff = dall - dsmart
+    plot_heatmap(ddiff,title_difference,"diff")
\ No newline at end of file