I realize the size of the ecosystem is important, but if you're writing all the GPU code yourself, I wouldn't say OpenCL is dead. I recently had a chance to le

I realize the size of the ecosystem is important, but if you're writing all the GPU code yourself, I wouldn't say OpenCL is dead. I recently had a chance to learn the basics for a work project, never having touched the field before. I picked OpenCL, because I knew I was writing all my non-BLAS code myself, and there's no way in hell I'll voluntarily lock myself into a closed ecosystem. (PS: CLBlast, which is different from CLblas, is a joy!) I was pleasantly surprised. I found OpenCL very nice to work with indeed! And my code runs on any modern GPU out there. I've tested it on Intel integrated GPUs, AMD GPUs, and Nvidia's fancy datacenter devices. And even CPUs. Seamlessly, through a runtime switch fully controlled by the application itself! Now, could I have gotten more performance out of CUDA? Yeah, I estimate about a factor 2. For the cost of tying myself to a proprietary, locked in technology from a hostile vendor, throwing out two major classes of devices, and losing the ability to test out code anywhere. Not worth it. I hope OpenCL has life in it still. The stuff I keep reading that CUDA is far easier to approach definitely did not ring true to this beginner.