Reland Cute-DSL FP4 dense GEMM (#23590)

Co-authored-by: b8zhong <b8zhong@users.noreply.github.com>
This commit is contained in:
Brayden Zhong
2026-05-09 02:20:58 -07:00
committed by GitHub
co-authored by b8zhong
parent d49fc092cb
commit 8f33bee31b
6 changed files with 106 additions and 12 deletions
+80 -3
View File
@@ -1,14 +1,18 @@
import argparse
import csv
import os
import logging
from functools import partial
from typing import List, Tuple
import torch
import triton
from flashinfer import mm_fp4
from flashinfer.autotuner import autotune
from flashinfer.jit.core import logger as flashinfer_logger
from flashinfer.testing import bench_gpu_time
flashinfer_logger.setLevel(logging.ERROR)
from sglang.jit_kernel.nvfp4 import cutlass_scaled_fp4_mm, scaled_fp4_quant
from sglang.srt.utils import (
get_device_capability,
@@ -150,9 +154,9 @@ def _run_mm_fp4(a_fp4, b_fp4_T, a_sf, b_sf_T, alpha, dtype, res_fi, backend):
x_log=False,
line_arg="provider",
line_vals=(
["sglang_cutlass", "cutlass", "cudnn", "trtllm", "auto"]
["sglang_cutlass", "cutlass", "cudnn", "trtllm", "cute-dsl", "auto"]
if is_sm100_supported()
else ["sglang_cutlass", "cutlass", "cudnn", "auto"]
else ["sglang_cutlass", "cutlass", "cudnn", "cute-dsl", "auto"]
),
line_names=(
[
@@ -160,6 +164,7 @@ def _run_mm_fp4(a_fp4, b_fp4_T, a_sf, b_sf_T, alpha, dtype, res_fi, backend):
"flashinfer cutlass fp4",
"cudnn fp4",
"trtllm fp4",
"cute-dsl fp4",
"auto fp4 (cudnn/cutlass)",
]
if is_sm100_supported()
@@ -167,6 +172,7 @@ def _run_mm_fp4(a_fp4, b_fp4_T, a_sf, b_sf_T, alpha, dtype, res_fi, backend):
"sglang cutlass fp4",
"flashinfer cutlass fp4",
"cudnn fp4",
"cute-dsl fp4",
"auto fp4",
]
),
@@ -176,6 +182,7 @@ def _run_mm_fp4(a_fp4, b_fp4_T, a_sf, b_sf_T, alpha, dtype, res_fi, backend):
("orange", "solid"),
("blue", "solid"),
("green", "solid"),
("brown", "solid"),
("purple", "solid"),
]
if is_sm100_supported()
@@ -183,6 +190,7 @@ def _run_mm_fp4(a_fp4, b_fp4_T, a_sf, b_sf_T, alpha, dtype, res_fi, backend):
("red", "solid"),
("orange", "solid"),
("blue", "solid"),
("brown", "solid"),
("purple", "solid"),
]
),
@@ -224,6 +232,17 @@ def benchmark(batch_size, provider, N, K, dtype, correctness, csv_file):
use_cuda_graph=True,
)
elif provider == "cutlass":
with autotune():
_run_mm_fp4(
a_fp4,
b_fp4_T,
a_scale_interleaved,
b_sf_T,
alpha,
dtype,
res_fi,
backend="cutlass",
)
times_ms = bench_gpu_time(
fn=partial(_run_mm_fp4, backend="cutlass"),
input_args=(
@@ -238,6 +257,17 @@ def benchmark(batch_size, provider, N, K, dtype, correctness, csv_file):
use_cuda_graph=True,
)
elif provider == "cudnn":
with autotune():
_run_mm_fp4(
a_fp4,
b_fp4_T,
a_scale_interleaved,
b_sf_T,
alpha,
dtype,
res_fi,
backend="cudnn",
)
times_ms = bench_gpu_time(
fn=partial(_run_mm_fp4, backend="cudnn"),
input_args=(
@@ -254,12 +284,59 @@ def benchmark(batch_size, provider, N, K, dtype, correctness, csv_file):
elif provider == "trtllm":
a_sf_u8 = a_scale_interleaved.to(torch.uint8)
b_sf_u8_T = b_sf_T.to(torch.uint8)
with autotune():
_run_mm_fp4(
a_fp4,
b_fp4_T,
a_sf_u8,
b_sf_u8_T,
alpha,
dtype,
res_fi,
backend="trtllm",
)
times_ms = bench_gpu_time(
fn=partial(_run_mm_fp4, backend="trtllm"),
input_args=(a_fp4, b_fp4_T, a_sf_u8, b_sf_u8_T, alpha, dtype, res_fi),
use_cuda_graph=True,
)
elif provider == "cute-dsl":
with autotune():
_run_mm_fp4(
a_fp4,
b_fp4_T,
a_scale_interleaved,
b_sf_T,
alpha,
dtype,
res_fi,
backend="cute-dsl",
)
times_ms = bench_gpu_time(
fn=partial(_run_mm_fp4, backend="cute-dsl"),
input_args=(
a_fp4,
b_fp4_T,
a_scale_interleaved,
b_sf_T,
alpha,
dtype,
res_fi,
),
use_cuda_graph=True,
)
elif provider == "auto":
with autotune():
_run_mm_fp4(
a_fp4,
b_fp4_T,
a_scale_interleaved,
b_sf_T,
alpha,
dtype,
res_fi,
backend="auto",
)
times_ms = bench_gpu_time(
fn=partial(_run_mm_fp4, backend="auto"),
input_args=(