[Performance]: Can we enable triton_kernels on sm120

[ijpq]

Proposal to improve performance

Since PR (triton-lang/triton#8498) had been merged, we may enable triton_kernels on sm120.

vllm/vllm/model_executor/layers/quantization/mxfp4.py

Lines 153 to 160 in 67475a6

	triton_kernels_supported = (
	has_triton_kernels()
	and is_torch_equal_or_newer("2.8.0")
	# NOTE: triton_kernels are only confirmed to work on SM90 and SM100
	# SM110 fails with this error: https://github.com/vllm-project/vllm/issues/29317
	# SM120 needs this fix: https://github.com/triton-lang/triton/pull/8498
	and (9, 0) <= current_platform.get_device_capability() < (11, 0)
	)

Although I haven't looked at the relevant code in detail yet, I think it should be sufficient to complete the unit tests(or vllm had already had, just skip on sm120, delete one line is enough) for all the kernels involved when triton_kernels is enabled and run them on sm120.

@zyongye Does this idea make sense?

Report of performance regression

No response

Misc discussion on performance

No response

Your current environment (if you think it is necessary)

The output of `python collect_env.py`

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[zyongye]

We pin the triton_kernels version based on the pytorch release. Right now we pin the source code on triton branch release/3.5.x since our supported pytorch version is 2.9. When we upgrade to pytorch 2.10, which will likely include this branch, we will change the code accordingly.

[ijpq]

We pin the triton_kernels version based on the pytorch release. Right now we pin the source code on triton branch release/3.5.x since our supported pytorch version is 2.9. When we upgrade to pytorch 2.10, which will likely include this branch, we will change the code accordingly.

fair enough.