Occupancy Math on the AMD MI355X: A From-First-Principles Guide
The article provides a detailed, first-principles analysis of occupancy calculations on AMD's MI355X GPU, covering compute unit architecture, wavefront scheduling, and register/shared memory constraints, and offers practical guidance for optimizing kernel occupancy.
Background
- The AMD MI355X is a forthcoming data-center GPU designed for AI and high-performance computing, expected to succeed the current MI300X series. It is AMD's direct competitor to NVIDIA's enterprise GPUs (like the H100/B200).
- "Occupancy" in GPU programming refers to the ratio of active wavefronts (groups of threads) to the maximum supported on a compute unit. Higher occupancy can hide memory latency but does not always guarantee higher performance — it depends on the workload.
- This article provides a from-scratch mathematical walkthrough for calculating occupancy on the MI355X, aimed at GPU programmers who need to optimize kernel performance. It does not announce a product launch or benchmark; it is a technical tutorial.
- The guide is part of a growing ecosystem of resources for AMD's ROCm software platform, which competes with NVIDIA's CUDA. Understanding occupancy helps developers tune AI inference and training workloads for AMD hardware.