CUDA: Difference between revisions
(→Linux) |
(→Linux) |
||
Line 11: | Line 11: | ||
** TensorRT | ** TensorRT | ||
; | ;Adapted from tensorflow | ||
<pre> | <pre> | ||
# Add NVIDIA package repositories | # Add NVIDIA package repositories | ||
Line 23: | Line 23: | ||
# Install NVIDIA driver | # Install NVIDIA driver | ||
sudo apt-get install --no-install-recommends nvidia-driver- | sudo apt-get install --no-install-recommends nvidia-driver-440 | ||
# Reboot. Check that GPUs are visible using the command: nvidia-smi | # Reboot. Check that GPUs are visible using the command: nvidia-smi | ||
Revision as of 19:04, 8 June 2020
Installation
Linux
- Install the latest nvidia drivers from the standard repo, e.g.
nvidia-drivers-440
- Install Cuda Toolkit separately without the drivers.
- Use one of the deb install options.
- You may also want to install the following:
- cuDnn
- TensorRT
- cuDnn
- Adapted from tensorflow
# Add NVIDIA package repositories wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-repo-ubuntu1804_10.1.243-1_amd64.deb sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub sudo dpkg -i cuda-repo-ubuntu1804_10.1.243-1_amd64.deb sudo apt-get update wget http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb sudo apt install ./nvidia-machine-learning-repo-ubuntu1804_1.0.0-1_amd64.deb sudo apt-get update # Install NVIDIA driver sudo apt-get install --no-install-recommends nvidia-driver-440 # Reboot. Check that GPUs are visible using the command: nvidia-smi # Install development and runtime libraries (~4GB) sudo apt-get install --no-install-recommends \ cuda-10-1 \ libcudnn7=7.6.4.38-1+cuda10.1 \ libcudnn7-dev=7.6.4.38-1+cuda10.1 # Install TensorRT. Requires that libcudnn7 is installed above. sudo apt-get install -y --no-install-recommends libnvinfer6=6.0.1-1+cuda10.1 \ libnvinfer-dev=6.0.1-1+cuda10.1 \ libnvinfer-plugin6=6.0.1-1+cuda10.1
For tensorflow and pytorch, you may need to add LD_LIBRARY_PATH=/usr/local/cuda/lib64
to your environment variables.
You can also do this in PyCharm.