This is an untrue, yet often repeated statement. For example Hashcat migrated their CUDA code to OpenCL some time ago, with zero performance hits. What is true is that Nvidia's OpenCL stack is less mature than CUDA. But you can write OpenCL code that performs just as well as CUDA.

Hi, I'm one of the developers of the open-source CUDA compiler.

It's not actually a separate compiler, despite what that paper says. It's just plain, vanilla, open-source clang. Download or build the latest version of clang, give it a CUDA file, and away you go. That's all there is to it.

In terms of compiling CUDA on other GPUs, that's not something I've worked on, but judging from the commits going by to clang and LLVM, other people are quite interested in making this work.

http://llvm.org/docs/CompileCudaWithLLVM.html

But it still targets NVIDIA GPUs and uses NVIDIA libraries so not that universal yet.

Nowadays our CUDA compiler is just clang

Incorrect. Our kernels (GROMACS molecular simulation package) are 2-3x slower implemented in OpenCL vs CUDA.

> On the other hand, I believe Google is working on a CUDA compiler

They were. It's upstream clang by now.