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> For CUDA there is an immense body of examples, support, and documentation that makes creating your first CUDA program dead simple. Isn't it dead simple only
by cesarb 7y ago
> For CUDA there is an immense body of examples, support, and documentation that makes creating your first CUDA program dead simple.
Isn't it dead simple only if you have compatible hardware? OpenCL works everywhere, even in the worst case on the CPU through pocl.
- retrac 7y agoI'm surprised this isn't more of an advantage. Sometimes you just need to test if your code runs and in my experience, a CPU on my netbook is fine for that purpose. With CUDA I have to upload the code to a VM and test it there. Both expensive and a bit awkward.
- tyoma 7y agoI originally wanted to do just that, but my laptop is a MacBook and OpenCL is deprecated there. With CUDA I could just ssh to an old box under my desk.
- tyoma 7y agoI know, that was one of the reasons I wanted to use OpenCL. My time for this was limited, and I saw I could get a basic implementation working much faster in CUDA. All the major cloud providers offer (only) NVIDIA cards too, so it was not a hindrance for the end goal of running it on cloud.
- pjmlp 7y agoTry to use OpenCL on Android.
- llukas 7y agoDifferent subsets of OpenCL with different extensions work everywhere. If you want to use C++ then it definitely doesn't work everywhere. Precompiled kernels (SPIR-V) also do not work (anywhere?). Writing a GPU C program that only gets compiled when you run your program is extra overhead on productivity.