How to use Google microbenchmarks for evaluating TPU performance- Google Developers Blog

Introduces a microbenchmark suite for evaluating TPU performance across network, compute, HBM, and host transfer categories. Details key metrics like TFLOPs, MFU, and memory bandwidth. Explains how microbenchmarks inform the Roofline model to diagnose compute, memory, or network-bound bottlenecks. Presents a case study on optimizing a 110B MoE training workload on TPU 7x, highlighting the impact of microbenchmark-driven interventions like SparseCore collective offloading and Tokamax Splash Attention.