On Mon, Sep 13, 2021 at 3:20 PM Arnd Bergmann <a...@arndb.de> wrote: > One straightforward hardware independent low-level API would > be the traditional BLAS GEMM call[1] for matrix multiplication > and its variants (integer, float, bfloat16, ...).
What this (and subsequent posts from Dave and Daniel) show, is that the general pattern is that what we are accelerating is no longer the specialized use cases of linear algebra such as 3D "shaders" or whatever inference linear algebra NPUs are doing, which appear to include regression, bayesian stuff, gaussian quadrature... name it. What we are talking about here is acceleration, using an efficient data path, of numerical analysis, using tailored hardware. I'm not even sure we are limited to linear algebra anymore. Is this what is happening, and should we be thinking numerical analysis accelerators and their different shapes and sizes rather than usecase-foo-accelerators, so we don't end up with this situation again the next time applied math comes knocking on the door with their next usecase? Yours, Linus Walleij --------------------------------------------------------------------- To unsubscribe, e-mail: dev-unsubscr...@tvm.apache.org For additional commands, e-mail: dev-h...@tvm.apache.org
