CUDA - definition

Compute Unified Device Architecture is what CUDA stands for. For usage with their graphics processing units (GPUs), NVIDIA created a parallel computing platform and programming methodology for it. Instead of simply for graphics processing, CUDA enables programmers to harness the capabilities of GPUs for general-purpose computation.
With CUDA, programmers can create code in C, C++, or Fortran and run it on a GPU. This makes it possible for programs to make use of the GPUs' enormous parallel processing capacity, which can carry out thousands of tasks at once. This is especially helpful for programs like scientific simulations, machine learning, and image and video processing that need to analyze massive volumes of data.
In order to help programmers, create and optimize their applications for GPUs, CUDA offers a software development kit (SDK) that consists of libraries, tools, and compilers. The CUDA Runtime, which offers a programming interface for interfacing with the GPU, and the CUDA Toolkit, which offers a compiler and libraries for creating CUDA programs, are both included in the SDK.
Because it enables researchers and developers to create applications that can carry out complex computations much more quickly than on conventional CPUs, CUDA has emerged as a key technology for high-performance computing. It has been widely used in a variety of domains, including machine learning, financial modeling, and science.