The major one, I feel, is an easy way to train multiple models in parallel. I can run one model on one GPU, one model on multiple GPUs, and multiple models on multiple GPUs. However, it's currently very inefficient to run multiple small models on a single GPU. Even though a model being used for an embedded application might be well under a meg, the CUDA instance needed to run it is almost a gig in size, so a GPU with 6 gigs of spare VRAM can only run 6 models in parallel, when it should be able to run a much greater number with greater efficiency. Basically, anything in general that will let you run multiple models on the same GPU without large computational bottlenecks would be great.