The Nvidia CUDA toolkit is an extension of the GPU parallel computing platform and programming model. The Nvidia CUDA installation consists of inclusion of the official Nvidia CUDA repository followed by the installation of relevant meta package and configuring path the the executable CUDA binaries. In this tutorial, you will see how to install CUDA on Ubuntu 20.04 Focal Fossa Linux. This will get your video graphics running with the latest drivers and software available.
The methods covered below will include installing CUDA from either the default Ubuntu repository or from the (slightly more up to date) CUDA repository. At the end, you will also see how to compile an example CUDA C program to test the installation.
In this tutorial you will learn:
- How to install CUDA toolkit from Ubuntu Repository
- How to install CUDA toolkit from CUDA repository
- How to compile example CUDA C code and execute program
- How to Check CUDA version
Software Requirements and Conventions Used
| Category | Requirements, Conventions or Software Version Used |
|---|---|
| System | Installed Ubuntu 20.04 or upgraded Ubuntu 20.04 Focal Fossa |
| Software | CUDA |
| Other | Privileged access to your Linux system as root or via the sudo command. |
| Conventions | # – requires given linux commands to be executed with root privileges either directly as a root user or by use of sudo command$ – requires given linux commands to be executed as a regular non-privileged user |
How to install CUDA on Ubuntu 20.04 step by step instructions
How to install CUDA toolkit from Ubuntu Repository
- Although you might not end up witht he latest CUDA toolkit version, the easiest way to install CUDA on Ubuntu 20.04 is to perform the installation from Ubuntu’s standard repositories.To install CUDA execute the following commands:
$ sudo apt update $ sudo apt install nvidia-cuda-toolkit
- All should be ready now. Check your CUDA version:
$ nvcc --version nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2019 NVIDIA Corporation Built on Sun_Jul_28_19:07:16_PDT_2019 Cuda compilation tools, release 10.1, V10.1.243
NOTE
To install latest and more up to date CUDA version see below How to install CUDA toolkit from CUDA repository section. - Confirm the CUDA toolkit installation by sample CUDA C code compilation. See the bellow Compile a Sample CUDA code section.
How to install CUDA toolkit from CUDA repository
- In case you have not done so yet, make sure that you have installed the Nvdia driver for your VGA. To do so follow our guide on How to install the NVIDIA drivers on Ubuntu 20.04 Focal Fossa Linux.
- Setup Nvida CUDA repository. Execute the following commands to enable CUDA repository.
$ sudo wget -O /etc/apt/preferences.d/cuda-repository-pin-600 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-ubuntu2004.pin $ sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/7fa2af80.pub $ sudo add-apt-repository "deb http://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/ /"
- At this stage all should be ready to install CUDA. Execute the two following
aptcommands:$ sudo apt update $ sudo apt install cuda
- Once ready, set your path to point to CUDA binaries:
$ echo 'export PATH=/usr/local/cuda/bin${PATH:+:${PATH}}' >> ~/.bashrc - Check CUDA version to confirm the installation:
$ nvcc --version nvcc: NVIDIA (R) Cuda compiler driver Copyright (c) 2005-2019 NVIDIA Corporation Built on Wed_Oct_23_19:24:38_PDT_2019 Cuda compilation tools, release 10.2, V10.2.89
Compile a Sample CUDA code
Confirm the installation by compiling an example CUDA C code. Save the following code into a file named eg. hello.cu:
#include <stdio.h>
__global__
void saxpy(int n, float a, float *x, float *y)
{
int i = blockIdx.x*blockDim.x + threadIdx.x;
if (i < n) y[i] = a*x[i] + y[i];
}
int main(void)
{
int N = 1<<20;
float *x, *y, *d_x, *d_y;
x = (float*)malloc(N*sizeof(float));
y = (float*)malloc(N*sizeof(float));
cudaMalloc(&d_x, N*sizeof(float));
cudaMalloc(&d_y, N*sizeof(float));
for (int i = 0; i < N; i++) {
x[i] = 1.0f;
y[i] = 2.0f;
}
cudaMemcpy(d_x, x, N*sizeof(float), cudaMemcpyHostToDevice);
cudaMemcpy(d_y, y, N*sizeof(float), cudaMemcpyHostToDevice);
// Perform SAXPY on 1M elements
saxpy<<<(N+255)/256, 256>>>(N, 2.0f, d_x, d_y);
cudaMemcpy(y, d_y, N*sizeof(float), cudaMemcpyDeviceToHost);
float maxError = 0.0f;
for (int i = 0; i < N; i++)
maxError = max(maxError, abs(y[i]-4.0f));
printf("Max error: %f\n", maxError);
cudaFree(d_x);
cudaFree(d_y);
free(x);
free(y);
}
Next, use nvcc the Nvidia CUDA compiler to compile the code and run the newly compiled binary:
$ nvcc -o hello hello.cu $ ./hello Max error: 0.000000
Troubleshooting
At the moment CUDA does not support GCC compiler higher then version 8 when installed from CUDA Ubuntu 18.04 sources. As a result upon the code compilation with the Nvidia CUDA compiler you might receive the following error:
In file included from /usr/local/cuda-10.2/bin/../targets/x86_64-linux/include/cuda_runtime.h:83,
from :
/usr/local/cuda-10.2/bin/../targets/x86_64-linux/include/crt/host_config.h:138:2: error: #error -- unsupported GNU version! gcc versions later than 8 are not supported!
138 | #error -- unsupported GNU version! gcc versions later than 8 are not supported!
| ^~~~~
To comply with the CUDA compiler requirements switch your default GCC compiler to version 8 or lower.
Closing Thoughts
In this tutorial, we saw how to install CUDA on Ubuntu 20.04 Focal Fossa Linux. It’s possible to install the CUDA toolkit through several different methods, which we’ve shown here. The most bleeding edge CUDA software can be installed from PPA, although the most convenient installation method is via official package manager download.