We initially went with OpenCL to maximize optionality, e.g., back then, GPUs were just getting into the cloud, and we were thinking of eventually getting Graphi

We initially went with OpenCL to maximize optionality, e.g., back then, GPUs were just getting into the cloud, and we were thinking of eventually getting Graphistry running on FPGAs as well. However, we had to bring a bunch of stuff to the JS world, and ultimately, we wasted a ton of time & money here and with minuscule eco-system support. Intel & AMD's SW arms are very narrow in what they actually support, so if you aren't doing some precise deep learning thing or legacy fortran whatever, sorry. Back then, the case was unclear because so little stuff existed outside of the MPI & graphics worlds. Today, for most engineering leaders today, the CUDA ecosystem, and emerging productivity layers like RAPIDS is quite rich. They make OpenCL a niche & risky call. The goal should be writing ~100X more code than the OpenCL ecosystem is giving you, it's just surface level.