GPU Computing
GPU computing refers to the use of graphics processing units (GPUs) for general-purpose computation beyond traditional graphics rendering. It leverages the massively parallel architecture of GPUs to accelerate computationally intensive tasks in fields like scientific simulations, machine learning, and data analysis. This approach contrasts with CPU-based computing by offering higher throughput for parallelizable workloads.
Developers should learn GPU computing when working on applications that require high-performance parallel processing, such as training deep learning models, running complex simulations in physics or finance, or processing large datasets in real-time. It is essential for optimizing performance in domains like artificial intelligence, video processing, and scientific computing where traditional CPUs may be a bottleneck.