cuda-intro

This repo contains a simple program that adds two vectors in parallel using cuda. The original source material can be found here https://developer.nvidia.com/blog/even-easier-introduction-cuda/.

Tools and requirements

To compile the code in this repo, you will need a c/c++ compiler like gcc or g++ along with cuda and nvidia-cuda-toolkit. Information about setting up and configuring CUDA to work on your machine can be found here:

• Installation Guide for Linux
• CUDA Quick Start Guide

You will need an Nvidia gpu to run the CUDA code, however you dont need one to compile and install the toolkit.

On Ubuntu 20.04 (x86) install cuda & the toolkit by running the following commands

wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2004/x86_64/cuda-ubuntu2004.pin
sudo mv cuda-ubuntu2004.pin /etc/apt/preferences.d/cuda-repository-pin-600
wget https://developer.download.nvidia.com/compute/cuda/12.0.0/local_installers/cuda-repo-ubuntu2004-12-0-local_12.0.0-525.60.13-1_amd64.deb
sudo dpkg -i cuda-repo-ubuntu2004-12-0-local_12.0.0-525.60.13-1_amd64.deb
sudo cp /var/cuda-repo-ubuntu2004-12-0-local/cuda-*-keyring.gpg /usr/share/keyrings/
sudo apt-get update
sudo apt-get -y install cuda

sudo apt install nvidia-cuda-toolkit

Instructions to download versions for other systems, like WSL, can be found here: https://developer.nvidia.com/cuda-downloads

Code Notes

More information about grid-stride loops can be found here: https://developer.nvidia.com/blog/cuda-pro-tip-write-flexible-kernels-grid-stride-loops/

Compiling, Running, & Benchmarking

Now that you have the cuda toolkit installed, you can compile, run, and benchmark the code

Single threaded c++

Compile:

 g++ add.cpp -o add

Run the code:

./add

Time its execution:

time ./add

CUDA

Compile:

nvcc add.cu -o add_cuda

Run the code:

./add_cuda

Time its execution:

time ./add_cuda

Benchmark and profile using Nvidia's profiling tool:

nvprof ./add_cuda