PyTorch: 'free normalization' fuses Layer Norm into GEMM and attention kernels — Meta targets lower training cost for large models
The PyTorch team at Meta published techniques for fusing normalization operations directly into GEMM and attention kernels, with the goal of eliminating their computational cost — 'free normalization'. The code is available on GitHub through a kernel library, and the direct result is faster training and inference for models with frequent Layer Norm and RMS Norm operations.