> which are highly optimized for inference. My understanding is that grayskull is a devboard for inference, Wormhole is supposed to do both, because you can sc

> which are highly optimized for inference. My understanding is that grayskull is a devboard for inference, Wormhole is supposed to do both, because you can scale it out with multiple cards. > With CUDA you get a lot of flexibility which you don't get with Grayskull Do you? From what I can tel tt-metalium gives you quite low level access. Grayskull/Wormhole/... basically have a bunch of tensix cores, which each have 5 small rv32 cores, where some are used for data movement and some for computation. IIRC two (could be one) drive a SIMT compute unit. From what I can tell there is no "matrix in matrix out" style fixed accelerator, the SIMT unit looks decently flexible, the grayskull one is a bit limited isa wise, wormhole is supposed to improve on that. tt-buda is supposed to be the high level API with pytorch, tensorflow, ... support, but idk how much compatibility there is at the moment. I assume there is a lot of software work left.