bug: RuntimeError("GPU compute capability 8.0 (Ampere) or higher is required to use Kernl")

[Oxi84]

Description

Thanks for the software. but you should mention in the description that it does not work on RTX 2xxx cards. This would save some time.

Most people do not have 3xxx cards, making this speedup not applicable to most GPUs. I tried with using my rtx 2080 and on runpod rtx 3070 where it cannot be installed and google colab that only gave me T4 card which is not Ampere.

Also what i have noticed is that cuda that comes with the install of the software, is around 2x slower on RTX 2080 that cuda 10.1 or 10.0 that I use.

Thanks.

Steps to reproduce

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Expected Behavior

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Actual Behavior

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Your environment

• Operating system and version (e.g. Ubuntu 20.04.2 LTS):
• Python version (e.g. Python 3.8.10):
• Python package manager (e.g. pip 21.1.2):
• etc.

Self-service

• I would be willing to help fix this bug myself.

Code of Conduct

• I agree to follow this project's Code of Conduct

[jonathlela]

Thank you for reporting this. Even though when loading the library we check that the GPU is compatible, we forgot to indicate it in the README.
However, we hope that in the next releases of triton we can have at least the compatibility with Turing GPUs.