I'll try to answer. CUDA is the Nvidia GPU compute infrastructure and runtime. The native language is a variant of C++, but there are lots of ways to use CUDA

I'll try to answer. CUDA is the Nvidia GPU compute infrastructure and runtime. The native language is a variant of C++, but there are lots of ways to use CUDA from Python (very popular in the machine learning world), Julia, etc. It is an extremely mature and polished way to get access to high performance compute. The biggest downside is that it's Nvidia proprietary. OpenCL is the older non-Nvidia standard infrastructure for GPU compute. It's languishing though. It is traditionally programmed in OpenCL C, but it does support other languages such as SYCL (another C++ dialect, similar in scope to CUDA C++). HLSL is similar in that it's a language for programming GPU code, also derived from C (with some C++ sprinkled in), but it's different than CUDA and OpenCL in that it's primarily for graphics applications rather than general purpose compute. The line blurs a bit with the concept of "compute shader," which can be seen as a cut-down CUDA or OpenCL that runs inside the GPU graphics API. Compute shaders are becoming more powerful in each generation. That said, HLSL is overwhelmingly popular for game development, because the tools are so good. This stuff is confusing. I haven't even touched on the different intermediate representations and the tools for converting between the different languages, of which there is an increasingly dense matrix.