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bench/bench_matmul.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.tiled_matmul import triton_tiled_matmul
+from reference.torch_matmul import torch_matmul
+from tools.lab_extension import build_extension
+
+
+def benchmark(fn, *args, warmup: int = 5, reps: int = 20) -> 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, m: int, n: int, k: int) -> None:
+    tflops = (2.0 * m * n * k) / (elapsed_ms * 1e-3) / 1e12
+    print(f"{name}: {elapsed_ms:.3f} ms | throughput {tflops:.3f} TFLOP/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("--m", type=int, default=1024)
+    parser.add_argument("--n", type=int, default=1024)
+    parser.add_argument("--k", type=int, default=1024)
+    args = parser.parse_args()
+
+    a = torch.randn(args.m, args.k, device=args.device)
+    b = torch.randn(args.k, args.n, device=args.device)
+
+    if args.mode in {"all", "torch"}:
+        report("torch", benchmark(torch_matmul, a, b), args.m, args.n, args.k)
+
+    if args.device == "cuda" and args.mode in {"all", "triton"}:
+        try:
+            report("triton", benchmark(triton_tiled_matmul, a, b), args.m, args.n, args.k)
+        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.tiled_matmul, a, b),
+                    args.m,
+                    args.n,
+                    args.k,
+                )
+            except Exception as exc:
+                print(f"cuda: skipped ({exc})")
+
+
+if __name__ == "__main__":
+    main()