finally fast googlenet with correct latency artifacts for fair comparison

validation/raptor_validation/pimsim_nn.py

@@ -0,0 +1,73 @@
+import json
+import re
+import shutil
+from pathlib import Path
+
+
+_METRIC_PATTERNS = {
+    "output_count": r"output count:\s+([0-9]+)\s+samples",
+    "throughput": r"throughput:\s+([0-9.eE+-]+)\s+samples/s",
+    "average_latency_ms": r"average latency:\s+([0-9.eE+-]+)\s+ms",
+    "latency_ms": r"latency:\s+([0-9.eE+-]+)\s+ms",
+    "average_power_mw": r"average power:\s+([0-9.eE+-]+)\s+mW",
+    "average_energy_pj": r"average energy:\s+([0-9.eE+-]+)\s+pJ(?:/it)?",
+}
+
+
+def parse_pimsim_nn_metrics(output):
+    metrics = {"raw_output": output}
+    for name, pattern in _METRIC_PATTERNS.items():
+        match = re.search(pattern, output)
+        if match:
+            value = match.group(1)
+            metrics[name] = int(value) if name == "output_count" else float(value)
+    return metrics
+
+
+def export_raptor_latency_artifact(pim_dir, output_dir):
+    pim_dir = Path(pim_dir)
+    output_dir = Path(output_dir)
+    if output_dir.exists():
+        shutil.rmtree(output_dir)
+    output_dir.mkdir(parents=True)
+
+    def int8_bytes(value, field):
+        if value % 4:
+            raise ValueError(f"Raptor {field}={value} is not aligned to its fp32 element width")
+        return value // 4
+
+    with open(pim_dir / "config.json", encoding="utf-8") as f:
+        config = json.load(f)
+    for field in ("inputs_addresses", "outputs_addresses"):
+        if field in config:
+            config[field] = [int8_bytes(value, field) for value in config[field]]
+    with open(output_dir / "config.json", "w", encoding="utf-8") as f:
+        json.dump(config, f, separators=(",", ":"))
+        f.write("\n")
+
+    byte_size_fields = {
+        "ld": "size",
+        "st": "size",
+        "lldi": "len",
+        "lmv": "len",
+        "send": "size",
+        "recv": "size",
+    }
+    for source in sorted(pim_dir.glob("core_*.json"), key=lambda path: int(path.stem.split("_")[1])):
+        with open(source, encoding="utf-8") as f:
+            instructions = json.load(f)
+        for instruction in instructions:
+            op = instruction["op"]
+            if op == "setbw":
+                instruction["ibiw"] = 8
+                instruction["obiw"] = 8
+            elif op == "sldi":
+                instruction["imm"] = int8_bytes(instruction["imm"], "address")
+            if field := byte_size_fields.get(op):
+                instruction[field] = int8_bytes(instruction[field], f"{op} {field}")
+                if offset := instruction.get("offset"):
+                    offset["offset_value"] = int8_bytes(offset["offset_value"], f"{op} offset")
+        with open(output_dir / source.name, "w", encoding="utf-8") as f:
+            json.dump(instructions, f, separators=(",", ":"))
+            f.write("\n")
+    return output_dir