<ul><li>Parallel programming is a powerful technique that allows us to take full advantage of the capabilities of modern computing systems, particularly GPUs.</li><li>Tasks can be parallelized by breaking them down into smaller sub-tasks and running them concurrently, resulting in higher performance and more efficient problem-solving.</li><li>GPUs, designed to handle thousands of threads simultaneously, are ideal for parallel programming and have become essential for accelerating non-graphical tasks.</li><li>To get started with GPU parallel programming, tools such as CUDA, OpenCL, TensorFlow, PyTorch, and cuDNN can be used for different applications and frameworks.</li></ul>

Introduction to Parallel Programming: Unlocking the Power of GPUs(Part 1)

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