75 lines
2.4 KiB
Python
75 lines
2.4 KiB
Python
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()
|