NVIDIA CUDA Runtime 12.1

CUDA is a parallel computing platform and API model created by NVIDIA. It enables dramatic increases in computing performance by harnessing the power of the graphics processing unit (GPU).

CUDA Runtime is a C/C++ library that provides a simple interface for initializing, allocating memory for, and launching CUDA kernels on the GPU.

CUDA programming can be done in C/C++, Fortran, Python, and other languages using libraries such as PyCUDA or Thrust.

CUDA allows for massive parallelism that can be employed to accelerate computations. It provides access to the power of GPUs, which have many more cores than CPUs and can perform many operations in parallel. This can greatly speed up certain computations, such as those used in deep learning and scientific simulations.

CUDA can be used for machine learning, scientific simulations, image and video processing, signal processing, financial modeling, and more.

Yes, you need an NVIDIA GPU that supports CUDA computing. You also need to have the CUDA Toolkit installed on your system.

As of August 2021, the latest version of CUDA Runtime is version 11.4.

Yes, NVIDIA provides cloud-based GPU instances that support CUDA computing. You can also use services like Amazon Web Services and Microsoft Azure that offer CUDA-capable GPU instances.

Yes, NVIDIA provides extensive documentation and support for developers who are new to CUDA. There are also many online resources and communities where developers can ask questions and get help.

OpenCL is a cross-platform alternative to CUDA that allows developers to write GPU-accelerated code that can run on both NVIDIA and AMD GPUs. However, it may not perform as well as CUDA on NVIDIA GPUs.