Wafer announces AI performance engineering series, starting with transformer inference

Wafer says it plans to share every resource from its AI performance engineering repository, starting with “All About Transformer Inference” from How To Scale Your Model. It describes the resource as covering the computations, memory traffic and serving decisions behind running transformer models. Highlighted topics include cache sizing, how batching and quantization shift compute and memory-bandwidth limits, and communication overhead when models are split across hardware.