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This is the release of the CUDA 13.3 samples, which include additions for CUDA Tile C++, and updated CCCL and Python samples.
925 B
925 B
tileLayerNorm
Description
This sample demonstrates a persistent layer-norm forward pass using
CUDA Tile C++:
y = (x - mean) * rsqrt(var + eps) * weight + bias. The grid launches NUM_SMS
persistent blocks; each block walks the row dimension with a grid-stride loop,
processing BLOCK_N rows by BLOCK_D cols per iteration and
striding by NUM_SMS * BLOCK_N rows between iterations. Per-row
mean and inverse standard deviation are reduced across the column
dimension with cuda::tiles row reductions and saved to float32
side buffers, while the weight and bias tiles are loaded once and
broadcast across rows.
Expected Output
Success! Persistent LayerNorm matches expected results.
Prerequisites
- CUDA Toolkit version 13.3 or later.
- CUDA Driver version 580 or later.
- Host compiler with C++20 support.