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bench/bench_vector_add.py

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+from __future__ import annotations
+
+import argparse
+import statistics
+import sys
+import time
+from pathlib import Path
+
+ROOT = Path(__file__).resolve().parents[1]
+if str(ROOT) not in sys.path:
+    sys.path.insert(0, str(ROOT))
+
+import torch
+
+from kernels.triton.vector_add import triton_vector_add
+from reference.torch_vector_add import torch_vector_add
+from tools.lab_extension import build_extension
+
+
+def benchmark(fn, *args, warmup: int = 5, reps: int = 30) -> float:
+    for _ in range(warmup):
+        fn(*args)
+    if args[0].is_cuda:
+        torch.cuda.synchronize()
+    times_ms = []
+    for _ in range(reps):
+        if args[0].is_cuda:
+            torch.cuda.synchronize()
+        start = time.perf_counter()
+        fn(*args)
+        if args[0].is_cuda:
+            torch.cuda.synchronize()
+        times_ms.append((time.perf_counter() - start) * 1e3)
+    return statistics.median(times_ms)
+
+
+def report(name: str, elapsed_ms: float, x: torch.Tensor) -> None:
+    bytes_moved = 3 * x.numel() * x.element_size()
+    gbps = bytes_moved / (elapsed_ms * 1e-3) / 1e9
+    print(f"{name}: {elapsed_ms:.3f} ms | effective bandwidth {gbps:.2f} GB/s")
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--device", default="cuda" if torch.cuda.is_available() else "cpu")
+    parser.add_argument("--mode", choices=["all", "torch", "triton", "cuda"], default="all")
+    parser.add_argument("--numel", type=int, default=1 << 24)
+    args = parser.parse_args()
+
+    x = torch.randn(args.numel, device=args.device)
+    y = torch.randn(args.numel, device=args.device)
+
+    if args.mode in {"all", "torch"}:
+        report("torch", benchmark(torch_vector_add, x, y), x)
+
+    if args.device == "cuda" and args.mode in {"all", "triton"}:
+        try:
+            report("triton", benchmark(triton_vector_add, x, y), x)
+        except (NotImplementedError, RuntimeError) as exc:
+            print(f"triton: skipped ({exc})")
+
+    if args.device == "cuda" and args.mode in {"all", "cuda"}:
+        ext = build_extension(verbose=False)
+        if ext is None or not hasattr(torch.ops, "kernel_lab"):
+            print("cuda: skipped (extension unavailable)")
+        else:
+            try:
+                report("cuda", benchmark(torch.ops.kernel_lab.vector_add, x, y), x)
+            except Exception as exc:
+                print(f"cuda: skipped ({exc})")
+
+
+if __name__ == "__main__":
+    main()