Игнорирование видимого устройства графического процессора с вычислительными возможностями Cuda 3.0. Минимальная требуема ⇐ Python

[Anonymous]

I tried to install tensorflow GPU in an anaconda enviorement, my hardware and software resources are:

• GPU: Quadro K1100M
• python: 3.10.13
• cudatoolkit: 11.2
• cudnn: 8.1.0
• OS: Windows 11
• Tensorflow: 2.10

Everything goes well, but when I test if tensorflow detects my GPU with tf.config.list_physical_devices('GPU') it prints this error:

I tensorflow/core/common_runtime/gpu/gpu_device.cc:1976] Ignoring visible gpu device (device: 0, name: Quadro K1100M, pci bus id: 0000:01:00.0, compute capability: 3.0) with Cuda compute capability 3.0. The minimum required Cuda capability is 3.5. []

I saw this answer: Ignoring visible gpu device with compute capability 3.0. The minimum required Cuda capability is 3.5

But I don't know if it will solve my problem because I am in Windows 11, the doccumentation says:

• Install GPU support (optional) See the Windows GPU support guide to install the drivers and additional software required to run TensorFlow on a GPU.

Then in the the Windows GPU support guide says:

• The following GPU-enabled devices are supported: NVIDIA® GPU card with CUDA® architectures 3.5, 5.0, 6.0, 7.0, 7.5, 8.0 and higher. See the list of CUDA®-enabled GPU cards.
• For GPUs with unsupported CUDA® architectures, or to avoid JIT compilation from PTX, or to use different versions of the NVIDIA® libraries, see the Linux build from source guide. (My case)

Because it says to look on the Linux build from source guide, I don't think that the answer will work on Windows.

So anyone knows if this works or another way to solve the problem or may I change my GPU.


Источник: https://stackoverflow.com/questions/781 ... mum-requir