TheRock/rocm-libraries/projects/composablekernel/example/ck_tile/12_smoothquant/README.md

SmoothQuant with CK Tile

This example demonstrates SmoothQuant, a quantization technique for transformer models, using the CK Tile programming model. SmoothQuant enables efficient int8 inference by scaling activations and weights to balance quantization error.

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Algorithm and Math

Given input X and per-channel scale S:

1. Scale: Y_{i,j} = X_{i,j} \cdot S_j
2. Rowwise Dynamic Quantization:
   • For each row, s = \max(|Y|) / 127
   • Q_{i,j} = \text{round}(Y_{i,j} / s), Q_{i,j} \in \text{int8}

Output:

• Quantized tensor Q (int8)
• Per-row scale s (fp32)

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Tile Programming Model

• Tiles: Each thread block processes a tile (row or block).
• Pipeline: Modular, can be extended for further fusion.

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Build & Run

mkdir build && cd build
sh ../script/cmake-ck-dev.sh  ../ <arch>  # you can replace this <arch> to gfx90a, gfx942...
make tile_smoothquant -j`nproc`

This will result in an executable build/bin/tile_smoothquant

cmdline

args:
          -m    m dimension (default:3328)
          -n    n dimension (default:4096)
   -x_stride    input stride per row, if -1 then equal to n (default:-1)
   -y_stride    output stride per row, if -1 then equal to n (default:-1)
          -v    cpu validation or not (default:1)
      -kname    print kernel name or not (default:1)
       -prec    precision (default:fp16)
     -warmup    cold iter (default:5)
     -repeat    hot iter (default:20)
       -json    0: No Json, 1: Dump Results in Json format (default:0)
   -jsonfile    json file name to dump results (default:smoothquant.json)