Well, to provide my own experience bringing GPU acceleration to scientific computation software, AMD got passed on because even if the software was there at the

Well, to provide my own experience bringing GPU acceleration to scientific computation software, AMD got passed on because even if the software was there at the time (it wasn't), there was no way to justify spending a bunch of money buying everyone workstation AMD GPUs when we could just start by picking up basic consumer NVIDIA cards to work on for anyone who didn't happen to have one already and then worry about buying more suitable cards if needed. Of course the end goal was to run on a large HPC cluster we had access to, but for efficient development, support on personal machines was necessary. My personal dual 3090 setup has been invaluable for getting through debugging and testing before dealing with the queueing system on the cluster (Side note: it also ended up revealing another important benefit of consumer side support for GPGPU, a 3090 was easily matching the performance of a single node of the CPU-only version of the cluster, thus massively bringing down the cost of entry to an otherwise computationally restrictive topic).