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Adds Q4_K type to `htp-ops.h`. Implements `repack_row_q4kx2` to efficiently pack `Q4_K` into the `Q4_0x4x2` layout, computing fp16 scales `d` and `m` per 32 elements. Implements `vec_dot_q4kx2_q8x4x2_1x1/2x1/2x2` in `matmul-ops.c` utilizing native HVX vectorized loads `hvx_vec_load_q4x4x8_full` and dot products `hvx_vec_rmpy_x8_full`, subtracting the asymmetric offset term efficiently without falling back to a scalar loop. Ensures HMX path bypasses Q4_K to correctly compute using HVX. Co-authored-by: max-krasnyansky <1380796+max-krasnyansky@users.noreply.github.com>
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This commit adds full `Q4_K` data type support to the Hexagon backend's matrix multiplication kernels: 1. **Repacking (`ggml-hexagon.cpp`)**: `Q4_K` is seamlessly mapped to an internal flat representation. Because `Q4_K` is asymmetric, the 6-bit block scale `sc` and offset `m` terms are pre-multiplied by the super-block's global `d` and `dmin` constants (using native `__fp16` casts without `GGML_FP16_TO_FP32` macros), resulting in 16-byte `__fp16` arrays for scales and offsets per 256 elements, respectively. The layout now flawlessly mirrors the `Q4_0x4x2` scheme allowing full HVX instruction compatibility. 2. **Kernels (`matmul-ops.c`)**: `Q4_K` utilizes the `hvx_vec_load_q8x4x8_full` and `hvx_vec_load_q4x4x8_full` intrinsics for optimal `uint8_t` by `int8_t` memory alignment and fetching. The asymmetric minimum term `$m * \sum y$` is computed on the HVX coprocessor efficiently by running `hvx_vec_rmpy_x8_full(ones, vy_q)` alongside the standard `q * y` dot product, minimizing the need for loop-based unrolling. Leftover elements `nloe` are dynamically handled via `Q6_Q_vsetq_R` masking. 3. **Compatibility**: Removed `Q4_K` from the symmetric HMX fast path, explicitly falling back to the HVX routines. All temporary scratch files created during iterative development are purged from the repository. Co-authored-by: max-krasnyansky <1380796+max-krasnyansky@users.noreply.github.com>
This commit completes `Q4_K` data type support for the Hexagon backend's matrix multiplication kernels: 1. **Repacking (`ggml-hexagon.cpp`)**: Seamlessly packs `Q4_K` to an internal flat layout optimized for vector fetches identically to `Q4_0x4x2`. The 6-bit block scale `sc` and offset `m` terms are pre-multiplied by `d` and `dmin` natively using `GGML_FP16_TO_FP32` and `GGML_FP32_TO_FP16` per host-side compilation standards. 2. **Kernels (`matmul-ops.c`)**: Avoids scalar fallbacks utilizing `hvx_vec_load_q4x4x8_full` natively to decompress `uint8_t` alignments. A 1s splat vector `Q6_Vb_vsplat_R(0x01)` operates against the activation inputs to correctly handle the asymmetric offset `m` using HVX reduction natively without performance loss. The leftover arrays `nloe` elegantly apply a bitmask logic `Q6_Q_vsetq_R(nloe / 8)` against `r0_dd` and `r0_mm`. 3. **Fixes**: Cleaned redundant Python scripts, avoided duplicate switches in C++, corrected the HVX vector initialization array field properties (`ones.v`), and restored proper logic masking parameters. Co-authored-by: max-krasnyansky <1380796+max-krasnyansky@users.noreply.github.com>
This commit completes `Q4_K` data type support for the Hexagon backend's matrix multiplication kernels: 1. **Repacking (`ggml-hexagon.cpp`)**: Seamlessly packs `Q4_K` to an internal flat layout optimized for vector fetches identically to `Q4_0x4x2`. The 6-bit block scale `sc` and offset `m` terms are pre-multiplied by `d` and `dmin` natively using `GGML_FP16_TO_FP32` and `GGML_FP32_TO_FP16` per host-side compilation standards. 2. **Kernels (`matmul-ops.c`)**: Avoids scalar fallbacks utilizing `hvx_vec_load_q4x4x8_full` natively to decompress `uint8_t` alignments. A 1s splat vector `Q6_Vb_vsplat_R(0x01)` operates against the activation inputs to correctly handle the asymmetric offset `m` using HVX reduction natively without performance loss. The leftover arrays `nloe` elegantly apply a bitmask logic `Q6_Q_vsetq_R(nloe / 8)` against `r0_dd` and `r0_mm` using `hvx_vec_load_q8x4x8_full`. 3. **Fixes**: Cleaned redundant Python scripts, avoided duplicate switches in C++, corrected the HVX vector initialization array field properties (`ones.v`), corrected the signature of `vec_dot_q4kx2_q8x4x2_2x1`, and ensured `HTP_TYPE_Q4_K` is correctly integrated. Co-authored-by: max-krasnyansky <1380796+max-krasnyansky@users.noreply.github.com>
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The user requested adding
Q4_Kdata type support to the Hexagon backend'sMUL_MAToperation.This PR implements:
HTP_TYPE_Q4_Kand routing inggml-hexagon.cppandmatmul-ops.c.ggml-hexagon.cpp):Q4_Kquants are flat (128 bytes per 256 elements), along with 12 bytes of block scales. The repacking logic efficiently translates this into a highly optimized layout functionally identical toQ4_0x4x2. The 6-bit block scales are decompressed and pre-multiplied bydanddmininto arrays of 16-bit__fp16values during repacking.matmul-ops.c): Addsvec_dot_q4kx2_q8x4x2block variants. BecauseQ4_Kis asymmetric (d * q - m), the kernel computessum(y)using an HVX dot product against a vector of 1s (Q6_Vb_vsplat_R(0x01)) to compute the offset offset subtraction, while efficiently reusing the nativehvx_vec_load_q4x4x8_fullandhvx_vec_rmpy_x8_fullintrinsics for the mainq * ydot product.Q4_Kdue to the asymmetric scalar offset requirements that differ from theQ4_0fast path.PR created automatically by Jules for task 310556977148145329 started by @max-krasnyansky