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bench/bench_softmax.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.online_softmax import triton_online_softmax
+from kernels.triton.row_softmax import triton_row_softmax
+from reference.torch_online_softmax import torch_online_softmax
+from reference.torch_row_softmax import torch_row_softmax
+from tools.lab_extension import build_extension
+
+
+def benchmark(fn, *args, warmup: int = 5, reps: int = 25) -> 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:
+    logical_bytes = 3 * x.numel() * x.element_size()
+    gbps = logical_bytes / (elapsed_ms * 1e-3) / 1e9
+    print(f"{name}: {elapsed_ms:.3f} ms | logical 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("--variant", choices=["row", "online"], default="row")
+    parser.add_argument("--rows", type=int, default=4096)
+    parser.add_argument("--cols", type=int, default=1024)
+    args = parser.parse_args()
+
+    x = torch.randn(args.rows, args.cols, device=args.device)
+
+    ref_fn = torch_row_softmax if args.variant == "row" else torch_online_softmax
+    triton_fn = triton_row_softmax if args.variant == "row" else triton_online_softmax
+    cuda_name = "row_softmax" if args.variant == "row" else "online_softmax"
+
+    if args.mode in {"all", "torch"}:
+        report(f"torch_{args.variant}_softmax", benchmark(ref_fn, x), x)
+
+    if args.device == "cuda" and args.mode in {"all", "triton"}:
+        try:
+            report(f"triton_{args.variant}_softmax", benchmark(triton_fn, x), x)
+        except (NotImplementedError, RuntimeError) as exc:
+            print(f"triton_{args.variant}_softmax: 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(f"cuda_{args.variant}_softmax: skipped (extension unavailable)")
+        else:
+            try:
+                cuda_fn = getattr(torch.ops.kernel_lab, cuda_name)
+                report(f"cuda_{args.variant}_softmax", benchmark(cuda_fn, x), x)
+            except Exception as exc:
+                print(f"cuda_{args.variant}_softmax: skipped ({exc})")
+
+
+if __name__ == "__main__":
+    main()