NVIDIA / NVIDIA/cutlass

[QST] SmemCopyAtom and MMA_Atom for fp32?

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Description

What is your question?
hello, I am developing a full precision attention backward kernel using cutlass, and get stuck in the use of ldmatrix and mma instructions for fp32.

My Gemm calculation is based on fp32 matrix, i.e. the datatype of D/A/B/C are all fp32. But the structs providied in mma_sm80.hpp take half-precision/mixed precision inputs so I am pretty confused about how to do things right in full precision. Here is my current setting for MMA, smem and gmem. Is there a way to use SM75_U32x4_LDSM_N and one of the mma instructions in my case?

  // MMA
  using TiledMma = TiledMMA<MMA_Atom<UniversalFMA<float, float, float>>, Layout<Shape<Int<16>, Int<8>, _1>>>;

  // Smem
  using SmemLayoutAtom = decltype(
    composition(Swizzle<3,3,3>{},
                Layout<Shape < _16,_32>,
                       Stride<_32, _1>>{}));
  using SmemCopyAtom = Copy_Atom<DefaultCopy, float>;

  // Gmem
  using GmemTiledCopy = decltype(
    make_tiled_copy(Copy_Atom<SM80_CP_ASYNC_CACHEALWAYS<cute::uint128_t>, float>{},
                    Layout<Shape <_16,_8>,
                           Stride< _8,_1>>{},
                    Layout<Shape < _1,_4>>{}));

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First steps

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  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with the fp32-related definitions in mma_sm80.hpp and the shown TiledMma, SmemCopyAtom, and GmemTiledCopy configuration. Check whether SM75_U32x4_LDSM_N and an available MMA instruction support the requested fp32 operands, and document a confirmed configuration or the missing support.

Written by the indexing model from the issue text.

Assessment

Tech stack
cpp
Domain
hpc, performance
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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