Sync from v0.13

benchmarks/disagg_benchmarks/visualize_benchmark_results.py

@@ -0,0 +1,47 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+import json
+
+import matplotlib.pyplot as plt
+import pandas as pd
+
+if __name__ == "__main__":
+    data = []
+    for name in ["disagg_prefill", "chunked_prefill"]:
+        for qps in [2, 4, 6, 8]:
+            with open(f"results/{name}-qps-{qps}.json") as f:
+                x = json.load(f)
+                x["name"] = name
+                x["qps"] = qps
+                data.append(x)
+
+    df = pd.DataFrame.from_dict(data)
+    dis_df = df[df["name"] == "disagg_prefill"]
+    chu_df = df[df["name"] == "chunked_prefill"]
+
+    plt.style.use("bmh")
+    plt.rcParams["font.size"] = 20
+
+    for key in [
+        "mean_ttft_ms",
+        "median_ttft_ms",
+        "p99_ttft_ms",
+        "mean_itl_ms",
+        "median_itl_ms",
+        "p99_itl_ms",
+    ]:
+        fig, ax = plt.subplots(figsize=(11, 7))
+        plt.plot(
+            dis_df["qps"], dis_df[key], label="disagg_prefill", marker="o", linewidth=4
+        )
+        plt.plot(
+            chu_df["qps"], chu_df[key], label="chunked_prefill", marker="o", linewidth=4
+        )
+        ax.legend()
+
+        ax.set_xlabel("QPS")
+        ax.set_ylabel(key)
+        ax.set_ylim(bottom=0)
+        fig.savefig(f"results/{key}.png")
+        plt.close(fig)