CODEWITHSUNDEEP
pythondockertensorflow
Taako
Taako

Reputation: 607

Ignoring visible gpu device with compute capability 3.0. The minimum required Cuda capability is 3.5

I am running Tensorflow 1.5.0 on a docker container because i need to use a version that doesn't use the AVX bytecodes because the hardware i am running on is too old to support it.

I finally got tensorflow-gpu to import correctly (after downgrading the docker image to tf 1.5.0) but now when i run any code to detect the GPU it says the GPU is not there.

I looked at the docker log and Jupyter is spitting out this message

Ignoring visible gpu device (device: 0, name: GeForce GTX 760, 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.

The tensorflow website says that GPUs with compute capability of 3.0 is supported so why does it says it needs compute capability 3.5?

Is there any way to get a docker image for tensorflow and jupyter that uses tf 1.5.0 but supports GPUs with compute capability?

Upvotes: 5

Views: 11520

Answers (3)

boomkin
boomkin

Reputation: 362

I just spent a day trying to build this thing from source and what worked for me finally is quite surprising: the pre-built wheel for TF 1.5.0 does not complain about this anymore, while pre-built wheel for TF 1.14.0 does complain. It seems you have used the same version, so it's quite interesting, but I thought I would share, so if anyone struggles with this, there seems to be an easy way out.

Configs:

  • Visual Studio version: 2017
  • Cuda compute capabilitz: 3.0
  • GPU: two Geforce GPU 755M
  • OS: Windows 10
  • Python: 3.6.8
  • Cuda Toolkit: 9.0
  • CuDNN: 7.0 (the earliest available is needed from, but it will complain anyway)

Upvotes: 1

user2357112
user2357112

Reputation: 280227

The Tensorflow 1.5 docs say

The following NVIDIA hardware must be installed on your system:

  • GPU card with CUDA Compute Capability 3.5 or higher. See NVIDIA documentation for a list of supported GPU cards.

Other Tensorflow versions support GPUs with compute capability 3.0, including both older versions and later versions, but specifically not Tensorflow 1.5. Upgrade your hardware, or pick a different Tensorflow version.

Upvotes: 1

Dr. Snoopy
Dr. Snoopy

Reputation: 56347

You need to build TensorFlow from source, the typical wheels that you install using pip were built with the requirement of using Compute Capability 3.5, but TensorFlow does indeed support Compute Capability 3.0:

https://www.tensorflow.org/install/install_sources

GPU card with CUDA Compute Capability 3.0 or higher. See NVIDIA documentation for a list of supported GPU cards.

You can build the latest TF version as this will also auto-detect the capabilities of your CPU and should not use AVX.

Upvotes: 4

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