From da29aa865bc8b8073d3f2ea341987361bdcb42e0 Mon Sep 17 00:00:00 2001
From: Derek Christ <christ.derek@gmail.com>
Date: Mon, 26 Feb 2024 19:19:14 +0100
Subject: [PATCH] First plot script

---
 configs/pim_config.py     |  5 +++-
 configs/pim_simulation.py |  2 +-
 pim_plots.py              | 35 ++++++++++++++++++++++++++
 simulation_script.py      | 53 +++++++++++++++++++++++++++++----------
 4 files changed, 80 insertions(+), 15 deletions(-)
 create mode 100644 pim_plots.py

diff --git a/configs/pim_config.py b/configs/pim_config.py
index e3c78e535e..ffda503e03 100644
--- a/configs/pim_config.py
+++ b/configs/pim_config.py
@@ -4,7 +4,10 @@ from pathlib import Path
 @dataclass(frozen=True)
 class Configuration:
     name: str
-    workload: Path
+    workload: str
+    executable: Path
+    pim: bool
+    level: str
     frequency: str = "3GHz"
 
 @dataclass(frozen=True)
diff --git a/configs/pim_simulation.py b/configs/pim_simulation.py
index 84201c925b..94ad3540cf 100644
--- a/configs/pim_simulation.py
+++ b/configs/pim_simulation.py
@@ -57,7 +57,7 @@ for core in processor.get_cores():
 workload = CustomWorkload(
     "set_baremetal_workload",
     {
-        "kernel": BinaryResource(configuration.workload),
+        "kernel": BinaryResource(configuration.executable),
     },
 )
 board.set_workload(workload)
diff --git a/pim_plots.py b/pim_plots.py
new file mode 100644
index 0000000000..40c8b6f70f
--- /dev/null
+++ b/pim_plots.py
@@ -0,0 +1,35 @@
+import matplotlib.pyplot as plt
+import pandas as pd
+import numpy as np
+
+df = pd.read_csv("pim_results.csv")
+
+frequency_filter = df["frequency"] == "3GHz"
+
+workloads = df["workload"].unique()
+
+fig, ax = plt.subplots()
+
+width = 0.25
+index = 0
+
+# for workload in workloads:
+for level in df["level"].unique():
+    level_filter = df["level"] == level
+
+    for pim in [False, True]:
+        workload_filter = df["workload"] == "vadd"
+
+        filtered_df = df[level_filter & workload_filter & frequency_filter]
+        print(filtered_df)
+
+        x = np.arange(len(filtered_df))
+
+        offset = 6*width * index
+        print(x+offset)
+        bars = ax.bar(x + offset, "ticks", width, data=filtered_df, label=level)
+        # ax.bar_label(bars, padding=2)
+        index += 1
+
+ax.legend(loc="upper left")
+plt.show()
diff --git a/simulation_script.py b/simulation_script.py
index 8364b5ac37..dec2d27899 100644
--- a/simulation_script.py
+++ b/simulation_script.py
@@ -3,6 +3,7 @@ import csv
 import copy
 import dataclasses
 import json
+import pandas as pd
 
 from threading import Thread
 from pathlib import Path
@@ -35,20 +36,15 @@ class Gem5Thread(Thread):
             ],
             capture_output=True,
         )
-        # print(out.stderr)
-        # print(out.stdout)
+
         output = out.stdout.splitlines()[-1]
         self.statistics = Statistics(**json.loads(output))
 
 
-workload_directory = Path("kernels")
+workload_base_directory = Path("kernels")
+workload_sub_directory = Path("aarch64-unknown-none/release")
 
 workloads = [
-    "classic_vadd",
-    "classic_vmul",
-    "classic_haxpy",
-    "classic_gemv",
-    # "classic_gemv_layers",
     "vadd",
     "vmul",
     "haxpy",
@@ -59,10 +55,34 @@ workloads = [
 configurations: list[Configuration] = []
 
 for frequency in ["3GHz", "100GHz"]:
-    for workload in workloads:
-        configurations.append(
-            Configuration(workload + "_" + frequency, (workload_directory / workload).as_posix(), frequency)
-        )
+    for level in ["X1", "X2", "X3", "X4"]:        
+        for pim in [False, True]:
+            for workload in workloads:
+                if workload == "gemv_layers" and level != "X4":
+                    continue
+                
+                executable = workload
+
+                if pim:
+                    executable = f"classic_{workload}"                
+
+                executable = (
+                    workload_base_directory
+                    / level
+                    / workload_sub_directory
+                    / executable
+                )
+
+                configurations.append(
+                    Configuration(
+                        f"{workload}_{level}_{frequency}",
+                        workload,
+                        executable.as_posix(),
+                        pim,
+                        level,
+                        frequency,
+                    )
+                )
 
 threads: list[Gem5Thread] = []
 
@@ -71,6 +91,13 @@ for configuration in configurations:
     thread.start()
     threads.append(thread)
 
+results: list[dict] = []
+
 for thread in threads:
     thread.join()
-    print(thread.configuration, thread.statistics)
+
+    result = dataclasses.asdict(thread.configuration) | dataclasses.asdict(thread.statistics)
+    results.append(result)
+
+dataframe = pd.DataFrame(results)
+dataframe.to_csv("pim_results.csv", index=False)