Add Qwen235 same-stack Frontier profiling campaign

runs/frontier-fidelity-envelope-v1/assemble_qwen235_v020_profiles.py

@@ -0,0 +1,93 @@
+#!/usr/bin/env python3
+"""Assemble immutable flat profiles for the Qwen235 Frontier runner."""
+
+from __future__ import annotations
+
+import argparse
+import csv
+import hashlib
+import json
+import shutil
+from pathlib import Path
+
+
+MODEL = "Qwen3-235B-A22B"
+
+
+def parse_args():
+    parser = argparse.ArgumentParser()
+    for name in ("cuda_common", "cuda_moe_tp4", "cuda_moe_ep8", "kernel_common", "kernel_moe_tp4", "kernel_moe_ep8"):
+        parser.add_argument(f"--{name.replace('_', '-')}", type=Path, required=True)
+    parser.add_argument("--output-root", type=Path, required=True)
+    return parser.parse_args()
+
+
+def digest(path: Path) -> str:
+    value = hashlib.sha256()
+    value.update(path.read_bytes())
+    return value.hexdigest()
+
+
+def model_file(root: Path, name: str) -> Path:
+    path = root / "compute" / "h20" / MODEL / name
+    if not path.is_file():
+        raise FileNotFoundError(path)
+    return path
+
+
+def merge_csv(inputs: list[Path], output: Path) -> None:
+    fields = None
+    rows = []
+    for path in inputs:
+        with path.open(newline="") as source:
+            reader = csv.DictReader(source)
+            if fields is None:
+                fields = reader.fieldnames
+            elif reader.fieldnames != fields:
+                raise ValueError(f"CSV schema mismatch: {path}")
+            rows.extend(reader)
+    if not fields or not rows:
+        raise ValueError("cannot merge empty profile CSV")
+    with output.open("w", newline="") as target:
+        writer = csv.DictWriter(target, fieldnames=fields, lineterminator="\n")
+        writer.writeheader()
+        writer.writerows(rows)
+
+
+def main() -> None:
+    args = parse_args()
+    output = args.output_root.resolve()
+    if output.exists():
+        raise FileExistsError(output)
+    output.mkdir(parents=True)
+    sources = {
+        "linear_op.csv": model_file(args.cuda_common, "linear_op.csv"),
+        "attention.csv": model_file(args.cuda_common, "attention.csv"),
+        "linear_op_kernel_only.csv": model_file(args.kernel_common, "linear_op_kernel_only.csv"),
+        "attention_kernel_only.csv": model_file(args.kernel_common, "attention_kernel_only.csv"),
+    }
+    for name, source in sources.items():
+        shutil.copy2(source, output / name)
+    merge_csv(
+        [model_file(args.cuda_moe_tp4, "moe.csv"), model_file(args.cuda_moe_ep8, "moe.csv")],
+        output / "moe.csv",
+    )
+    merge_csv(
+        [model_file(args.kernel_moe_tp4, "moe_kernel_only.csv"), model_file(args.kernel_moe_ep8, "moe_kernel_only.csv")],
+        output / "moe_kernel_only.csv",
+    )
+    outputs = {path.name: digest(path) for path in sorted(output.glob("*.csv"))}
+    manifest = {
+        "schema": "qwen235-v020-frontier-profile-v1",
+        "model": MODEL,
+        "measurement_families": ["CUDA_EVENT", "KERNEL_ONLY"],
+        "moe_runtime_paths": {"tp4_ep1": "TRITON", "tp8_ep8": "FLASHINFER_CUTLASS"},
+        "inputs": {name: str(getattr(args, name).resolve()) for name in ("cuda_common", "cuda_moe_tp4", "cuda_moe_ep8", "kernel_common", "kernel_moe_tp4", "kernel_moe_ep8")},
+        "outputs": outputs,
+    }
+    (output / "manifest.json").write_text(json.dumps(manifest, indent=2, sort_keys=True) + "\n")
+    print(json.dumps(manifest, sort_keys=True))
+
+
+if __name__ == "__main__":
+    main()