NVIDIA® GPU drivers —CUDA® 11.0 requires 450.x or higher., (optional) tensor RT 6.0 to improve latency and throughput for inference on some models., and linux setup.
Which tensorflow version supports cuda 10.2?
You have to roll back to cuda 10.1 in order to use TF 2.1 binary. For using cuda 10.2 you have to install TF from sources. Tensorflow pip package (TF 2.1) now includes GPU support by default (same as tensorflow-gpu) for both Linux and Windows.
For tensorflow-gpu==1.12.0 and cuda==9.0, the compatible cu. DNN version is 7.1.4, which can be downloaded from here after registration. UPDATE: Since tensorflow 2.0, has been released, I will share the compatible cuda and cu. DNN versions for it as well (for Ubuntu 18.04).
One way to consider this is in as far as there are dependencies of other products on the CUDA version, the productive way forward is to make feature requests of the Py. Torch and Tensorflow creators to support the latest CUDA version.
Our current plan is to use move TF 2.4 to CUDA 11. Sorry, something went wrong. Managed to install tensorflow-gpu 2.3 with cudatoolkit 10.1 on my cuda 10.2 driver (Jan 19th,2021).
What versions of CUDA are supported by cupti?
, ( optional) tensor RT 6.0 to improve latency and throughput for inference on some models.
Moreover, what are the software requirements for CUDA and cuDNN?
, and software requirements . 1 NVIDIA® GPU drivers —CUDA® 11.2 requires 450.80.02 or higher., 4 cu DNN SDK 8.1.0 cu. DNN versions ). 5 (Optional) Tensor. RT 6.0 to improve latency and throughput for inference on some models.
Does TensorFlow utilize GPU?
Bookmark this question. Show activity on this post. The tensorflow which I was using, is not utilizing gpu now, after it has been changed accidentally by other person. I remember that i installed my tensorflow using wheel. Currently, the version of Cuda is 10.2, python version is 3.7 and tensorflow version is 2.6.0.