Introduce powerful simulation script and provide an example

scripts/simulation/example_ddr3_simulations.py

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+#!/usr/bin/env python3
+
+import os
+import matplotlib.pyplot as plt
+
+from dataclasses import dataclass
+from simulation import (
+    Simulation,
+    Configuration,
+    get_options_from_args,
+    simulation_results,
+)
+
+script_directory = os.path.dirname(os.path.abspath(__file__))
+base_config = os.path.join(script_directory, "example_ddr3_simulations.json")
+
+simulations: list[Simulation] = []
+
+
+@dataclass(frozen=True)
+class SchedulerBuffer:
+    buffer: str
+    size: int
+
+
+refresh_policies = ["NoRefresh", "AllBank"]
+patterns = ["sequential", "random"]
+scheduler_buffers = [
+    SchedulerBuffer("Bankwise", 8),
+    SchedulerBuffer("Bankwise", 16),
+]
+
+for refresh_policy in refresh_policies:
+    for scheduler_buffer in scheduler_buffers:
+        for pattern in patterns:
+            PAGE_POLICY = "Open" if pattern == "sequential" else "Closed"
+
+            config = Configuration(
+                f"{refresh_policy}_{scheduler_buffer.buffer}_{scheduler_buffer.size}_{pattern}",
+                {
+                    "refresh_policy": refresh_policy,
+                    "pattern": pattern,
+                    "page_policy": PAGE_POLICY,
+                    "scheduler_buffer": scheduler_buffer.buffer,
+                    "scheduler_buffer_size": scheduler_buffer.size,
+                },
+            )
+
+            simulations.append(Simulation(config))
+
+
+options = get_options_from_args()
+
+if options.base_config is None:
+    options.base_config = base_config
+
+dataframe = simulation_results(options, simulations)
+
+# Generate interesting plots!
+for refresh_policy in refresh_policies:
+    refresh_policy_filter = dataframe["refresh_policy"] == refresh_policy
+
+    for scheduler_buffer in scheduler_buffers:
+        scheduler_buffer_filter = (
+            dataframe["scheduler_buffer"] == scheduler_buffer.buffer
+        )
+        scheduler_buffer_size_filter = (
+            dataframe["scheduler_buffer_size"] == scheduler_buffer.size
+        )
+
+        filters = (
+            refresh_policy_filter
+            & scheduler_buffer_filter
+            & scheduler_buffer_size_filter
+        )
+
+        TEMP_DATAFRAME = dataframe[filters]
+
+        for pattern in patterns:
+            pattern_filter = dataframe["pattern"] == pattern
+
+            plt.figure(figsize=(8.0, 12.0))
+
+            filters = (
+                refresh_policy_filter
+                & scheduler_buffer_filter
+                & scheduler_buffer_size_filter
+            )
+
+            TEMP_DATAFRAME = dataframe[filters]
+
+            plt.bar(
+                "pattern",
+                "bandwidth",
+                data=TEMP_DATAFRAME,
+            )
+
+        # Plot MAX line
+        plt.bar(
+            "MAX",
+            "max_bandwidth",
+            data=TEMP_DATAFRAME,
+            color="darkgray",
+        )
+
+        title = f"{refresh_policy} {scheduler_buffer.buffer} {scheduler_buffer.size}"
+
+        plt.title(title)
+        plt.axis(ymin=0, ymax=120)
+        plt.xlabel("Access Pattern")
+        plt.ylabel("Bandwidth [Gb/s]")
+
+        plt.savefig(f"{options.out_dir}/{title}.png")
+        plt.close()