Installing NVIDIA CUDA Toolkit 9.0 on Ubuntu

The process of installing NVIDIA CUDA Toolkit 9.0 on Ubuntu requires several steps and careful attention to detail. In this article, we will walk you through each step, ensuring that your installation is successful and efficient.

Firstly, check if CUDA is correctly installed by running the command `nvcc -V`. This will indicate whether CUDA is properly configured on your system.

To verify the installation and ensure everything is correct, run the following commands:

```

sudo dpkg -i libcudnn7-doc_7.1.4.18-1_cuda9.0_amd64

```

After downloading the necessary files, you will be prompted to install cuDNN v7.1.4 for CUDA 9.0 and its associated files.

To do this, create an account on the official NVIDIA website, log in, and visit the download page again. Once logged in, you can access the link to download cuDNN-7.1.4.

Additionally, if you have any patches that require installation, execute the following commands:

```

sudo dpkg -i

```

Following the installation of CUDA 9.0, don't forget to add the CUDA PATH to your `~/.bashrc` file by running the command:

```

sudo vim ~/.bashrc

```

Then, add the two lines at the end of the file:

```

export PATH=/usr/local/cuda-9.0/bin$

```

This will enable you to access the CUDA commands and utilities.

To install CUDA Toolkit 9.0, execute the following command:

```

sudo apt install nvidia-390

```

Before installing CUDA-9.0, add the repository by running the command:

```

sudo add-apt-repository ppa:graphics-drivers/ppa

```

In this blog post, we will use the `nvidia-390` driver.

To ensure that you can utilize Cuda and cuDNN effectively, it is essential to have a NVIDIA graphics card installed on your system. With CUDA installed, you can experience significant performance improvements in tasks such as deep learning and computer vision.

For instance, TensorFlow took 10 to 15 seconds to perform recognition tasks when running on CPU, whereas the same task took only 2 to 5 seconds when running on a GPU with Cuda installed. Based on my limited experience in this field, I can attest that CUDA is an essential tool for anyone looking to explore computer vision, deep learning, and machine learning using GPUs.

In conclusion, installing NVIDIA CUDA Toolkit 9.0 on Ubuntu requires careful attention to detail and adherence to the specified steps. By following these instructions, you can ensure a successful installation and take advantage of the significant performance improvements offered by Cuda and cuDNN.

Nvidia cuda toolkit 9.0 ubuntu