NVIDIA's CUDA (Compute Unified Device Architecture) technology has been a pivotal factor in the company's ascent to dominance in the GPU market. Introduced in 2006, CUDA is a parallel computing platform and application programming interface (API) model created by NVIDIA. It allows software developers and software engineers to use a CUDA-enabled graphics processing unit (GPU) for general purpose processing – an approach known as GPGPU (General-Purpose computing on Graphics Processing Units). CUDA has been instrumental in enabling the development of applications in areas such as deep learning, scientific simulations, and video rendering. Its ability to harness the power of GPUs for non-graphical tasks has given NVIDIA a significant edge over competitors. The technology's success can be attributed to its ability to provide a scalable and efficient way to perform complex computations, which has been crucial in the era of big data and artificial intelligence. CUDA's integration into various software frameworks and its support for multiple programming languages have further solidified its position as a key technology in the computing industry.