I don't think performance is the achilles heel of OpenCL. There are other problems that I have when working with: The implementations ended up becoming a "write

I don't think performance is the achilles heel of OpenCL. There are other problems that I have when working with: The implementations ended up becoming a "write once, debug everywhere" ecosystem. Making the compiler a part of the driver meant that OpenCL kernels that worked on platform A wouldn't even compile on platform B. SPIR-V should have been part of OpenCL from version 1.0. Profiling OpenCL kernels is a stumbling block too - IMHO, you shouldn't ship a toolkit without a profiler and claim it's intended for HPC. IEE 754 compliance should also have been part of 1.0 and not an afterthought. Without it, it's harder to verify that your kernel works correctly, since it's permitted to deliver different results than a C reference implementation. With CUDA, at least you're guaranteed* that your code that runs on your CUDA equipped machine, also runs on any other machine that supports CUDA - regardless of OS, regardless of GPU. With OpenCL, not so much. * Within the same restrictions as CPU code - instruction set, RAM and compiler bugs.