How to Speed Up Transformer Training Using NVIDIA Apex (FusedAdam, FusedLayerNorm) and Native torch.amp

The article benchmarks NVIDIA Apex fused optimizers and normalization layers against standard PyTorch in Transformer training.

It walks through setting up a CUDA GPU environment, building Apex with extensions, and checking which fused kernels are actually available.

Results compare FusedAdam, FusedLayerNorm, and FusedRMSNorm against non-fused PyTorch equivalents to measure throughput gains.

It also contrasts legacy apex.amp with native torch.amp to show the practical mixed-precision path for faster training.

The main takeaway is to verify your Apex install before relying on fused kernels, so you avoid false performance assumptions.