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[CK_TILE] Fix FP8 MXGEMM numerical error in async load path (#4704) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit ## Summary Fixes FP8 MXGEMM producing half the expected result (e.g., 128 instead of 256 with all 1s input). **Bug introduced in:** `b7de1e14cea70681a23cd1a136df42910c776e4a` - "[CK_TILE] Add blockscale GEMM support for EightWarps on gfx950 (#4280)" ## Root Cause In the `static_move_ys=true` code path in `tile_window.hpp`, the IMM optimization computes `lds_ys_offset` using a default-constructed tensor descriptor: ```cpp make_tensor_coordinate(decltype(tensor_descriptor){}, idx_ys_offset) ``` This default-constructed descriptor has different strides than the actual DRAM tensor descriptor used for dram_ys_offset. When these offsets are mixed in the address calculation: ```cpp imm_valid = lds_ys_offset % IMM_RANGE; // From wrong descriptor wave_offset = dram_ys_offset - imm_valid; // From correct descriptor ``` The final address wave_offset + imm_valid ≠ dram_ys_offset, causing incorrect memory accesses. Fix ```cpp Set imm_valid = 0 to bypass the IMM optimization and ensure the full offset is passed through wave_offset: constexpr auto imm_valid = 0; // Avoids inconsistency between lds_ys_offset and dram_ys_offset ``` This disables the 12-bit immediate field optimization in the buffer_load_lds instruction but guarantees correctness. A proper fix would require making the DRAM tensor descriptor constexpr, which is not feasible since tensor strides depend on runtime parameters (LDA, LDB).
ck_tile/core
ck_tile/core contains every basic functions and structures to create a GPU kernel using ck_tile. User should only include ck_tile/core.hpp this single header to use all the functionality. Everything is under ck_tile namespace. The coding style under this folder should be similar to std (snake_case for structure/function, Camel for template types...)
algorithm/
coordinate transform and some other reusable algorithm
arch/
contains some basic device building block like mma, buffer addressing, etc...
container/
contains basic container data structure, array/sequence/tuple/...
numeric/
data type, and data type related math
tensor/
tensor descriptors and tile level API
utility/
other utility function for both host/device