[anon291]

> SCALE doesn't use cuBlas and friends. For those APIs, it uses either its own implementations of the functions, or delegates to an existing AMD library (such as rocblas).

And this is the problem. I guarantee you NVIDIA has more engineers working on cuBLAS et al than AMD does.

The NVIDIA moat is not CUDA the language or CUDA the library. It's CUDA the ecosystem. That means things like all the high performance libraries; all the high performance libraries with clustering support (does AMD even have a clustering solution like NVLink -- everyone forgets that NVIDIA also does high speed networking); all the high perf appliances (everyone also forgets that NVIDIA sells entire systems, not GPUS); all the high perf servers (Triton inference server, etc). We can go on.

I commend the project volunteers for what they've done, but I would recommend getting VC money and competing directly with NVIDIA.