Welcome to your first step towards mastering GPU programming with NVIDIA's CUDA on Ubuntu. This guide is to ensure a smooth setup process, making it as straightforward as possible. By following this tutorial, you'll be well on your way to leveraging the immense power of NVIDIA GPUs for computing tasks.
This repository is divided into four main sections, designed to get you up and running with CUDA on Ubuntu:
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Starting your journey requires setting up Ubuntu alongside your current operating system. This section guides you through creating a bootable USB drive and installing Ubuntu in a dual-boot configuration.
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Once Ubuntu is up and running, the next step is to install the CUDA Toolkit. This toolkit provides the necessary libraries and tools needed to start developing CUDA applications.
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After installing the CUDA Toolkit, the next component you'll need is CuDNN (CUDA Deep Neural Network library). CuDNN is a GPU-accelerated library for deep neural networks. It provides highly optimized implementations of standard deep learning operations
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To harness the power of GPU acceleration in image processing, we'll guide you through installing OpenCV with CUDA support. This enables you to perform complex image processing tasks at significantly higher speeds.
Before diving into the world of GPU programming, ensure you have the following:
- An empty USB with at least 8GB of storage.
- A laptop or a desktop with an NVIDIA GPU compatible with CUDA.