[tombert]

Thanks for answering my question so quickly!

That seems like a pretty good reason...I have been looking to learn some GPU programming to optimize some matrix math that I've been doing for a pet project, and while my first instinct was telling me OpenCL since it's portable, if people who actually know what they're talking about are saying that CUDA is simpler to start with, it might be worth it to me to pick up a cheap Nvidia GPU/Jetson Nano and do some processing that way.

[felipe_aramburu]

The collab link below let's you use a gpu for free on Google cloud

[rrss]

> OpenCL since it's portable

Even if you choose OpenCL, the tools (profiler, debugger, etc) are usually platform specific. In addition, my experience with opencl across platforms was that each of the vendors' compilers had distinct issues and that performance was not portable.

I get the appeal for an open API, but opencl never grew a development ecosystem or any libraries. IMO it is dying and isn't worth the effort. AMD is implementing CUDA with hip - maybe roll with that.

[shaklee3]

You definitely do not want to use opencl for matrix multiplies on Nvidia cards. That's the most highly optimized task on GPUs, so much so that they have dedicated hardware units for it. Opencl cannot take advantage of those.