GPU Support for RTX 4090

Question

Abdalla Rashed 2022-10-14

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https://ww2.mathworks.cn/matlabcentral/answers/1825838-gpu-support-for-rtx-4090

编辑： Walter Roberson 2022-10-24

The GPU Computing Requirements documentations states that 3.5 to 8.x CUDA capability is supported.

Since the recently released RTX 4090 has a CUDA capability of 8.9, does that mean it is supported by default?

If not, when do we get support for the Ada Lovelace architecture?

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Answer 1

Joss Knight 2022-10-24

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https://ww2.mathworks.cn/matlabcentral/answers/1825838-gpu-support-for-rtx-4090#answer_1082478

Forgive me for needing to correct Walter, but the last three versions of MATLAB will natively support the 4000 series because, as you say, they are within the 8.x architecture series. Hopper (H100) will not be supported natively.

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Answer 2

Walter Roberson 2022-10-14

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No, the last few versions of MATLAB will not support the new RTX 40x0 architecture -- not by default.

You need to use parallel.gpu.enableCUDAForwardCompatibility to give MATLAB permission to use NVIDIA's backwards-compatibility feature. When enabled, each GPU kernel will be automatically recompiled for use with the new device. Sometimes the operations work fine, just not as fast as they might have executed if up-to-date code had been used. Other times, however, the recompiling will introduce bugs... in which case you are fortunate if the code bombs, as at least that tells you your code failed (worse is if the bugs give you wrong answers without telling you something went wrong.)

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Walter Roberson 2022-10-14

See https://www.mathworks.com/matlabcentral/answers/1814255-gpu-coder-basic-code-generation-failed?s_tid=srchtitle for someone with an RTX 3090 who could not use R2021b.

Joss Knight 2022-10-24

编辑：Walter Roberson 2022-10-24

The Ampere series including the 30x0 have indeed been supported since R2021a, see https://uk.mathworks.com/matlabcentral/answers/592198-does-matlab-support-nvidia-ampere-cards-for-gpu-computation .

That GPU Coder problem is I believe because by default Coder tries to compile native binary for your card's specified compute capability, e.g. sm_86, which isn't supported by the compiler shipped with MATLAB. The user would either need to change their settings to compile for sm_80, or install a newer CUDA toolkit.

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