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triton/python/bench/bench_matmul.py

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import triton
import torch
import os
def rounded_linspace(low, high, steps, div):
ret = torch.linspace(low, high, steps)
ret = (ret.int() + div - 1) // div * div
ret = torch.unique(ret)
return list(map(int, ret))
# Square benchmarks
nt = {False: "n", True: "t"}
square_confs = [
triton.testing.Benchmark(
x_names=["M", "N", "K"],
x_vals=rounded_linspace(512, 8192, 32, 128),
y_name="provider",
y_vals=["cublas", "triton", "cutlass"],
y_lines=["cuBLAS", "Triton", "CUTLASS"],
ylabel="TFLOPS",
plot_name=f"matmul-square-{nt[AT]}{nt[BT]}",
args={"AT": AT, "BT": BT, "dtype": torch.float16},
) for AT in [False] for BT in [False]
]
# Transformer training benchmarks
transformer_confs = [
triton.testing.Benchmark(
x_names=[x],
x_vals = rounded_linspace(NK//16, NK, 32, 128),
y_name="provider",
y_vals=["cublas", "triton", "cutlass"],
y_lines=["cuBLAS", "Triton", "CUTLASS"],
ylabel="TFLOPS",
plot_name=f"matmul-M{M}-{'NK'.replace(x, '')}{NK}",
args= {"M": M, 'NK'.replace(x,''): NK, "AT": False, "BT": False, "dtype": torch.float16}
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) for NK in [12288]\
for i, x in enumerate(["N", "K"])\
for M in [2048]
]
@triton.testing.perf_report(square_confs)
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def bench_op(M, N, K, AT, BT, dtype, provider, warmup=25, rep=75):
a = torch.rand((K, M) if AT else (M, K), device="cuda", dtype=dtype)
b = torch.rand((N, K) if BT else (K, N), device="cuda", dtype=dtype)
if AT: a = a.t()
if BT: b = b.t()
num_flops = 2 * M * N * K
tflops = lambda ms: 2. * M * N * K / ms * 1e-9
if provider == "cublas":
ms, min_ms, max_ms = triton.testing.do_bench(lambda: torch.matmul(a, b), warmup=warmup, rep=rep)
return tflops(ms), tflops(max_ms), tflops(min_ms)
if provider == "triton":
ms, min_ms, max_ms = triton.testing.do_bench(lambda: triton.ops.matmul(a, b), warmup=warmup, rep=rep)
return tflops(ms), tflops(max_ms), tflops(min_ms)
if provider == "cutlass":
cutlass_matmul = triton.testing.cutlass_matmul
try:
ms, min_ms, max_ms = triton.testing.do_bench(lambda: cutlass_matmul(a, b), warmup=warmup, rep=rep)
return tflops(ms), tflops(max_ms), tflops(min_ms)
except:
return None
return None