Dialects Overview

Here is a brief overview of the dialects in the project, please refer to the individual dialect documentation for more details.:

• tt: Common types such as, tt.tile, tt.layout, tt.grid, etc. and enums such as, data formats, memory spaces, iterator types etc.
• ttir: A high level dialect that models the tensor compute graph on tenstorrent devices. Accepts tosa and linalg input.
  • ttir.generic: Generically describe compute work.
  • ttir.to_layout: Convert between different tensor memory layouts and transfer between different memory spaces.
  • tensor.pad: Pad a tensor with a value (ie. convs)
  • ttir.yield: return result memref of computation in dispatch region body, lowers to ttkernel.yield
  • ttir.kernel: lowers to some backend kernel
• ttnn: A TTNN dialect that models ttnn API.
• ttkernel: Tenstorrent kernel library operations.
  • ttkernel.noc_async_read
  • ttkernel.noc_async_write
  • ttkernel.cb_push_back
  • ttkernel.[matmul|add|multiply]: Computations on tiles in source register space, store the result in dest register space.
  • ttkernel.sfpu_*: Computations on tiles in dest register space using sfpu coprocessor.
• ttmetal: Operations that dispatch work from host to device.
  • ttmetal.dispatch: Dispatch a grid of compute work.