• •AMD's ROCm blog provides a first-principles breakdown of occupancy math specifically for the CDNA4-based MI355X GPU.
• •The guide details register pressure and vector/scalar register constraints as primary determinants for kernel performance.
• •Hardware developers still lack benchmark data comparing these theoretical occupancy models to real-world performance under diverse heavy-load AI workloads.

AMD has published a technical guide detailing how to calculate GPU occupancy for its new CDNA4 architecture on the MI355X chip. Unlike previous generalized documentation, this focuses on the specific register file constraints that dictate how many active warps a compute unit can manage simultaneously. However, the guide remains a theoretical framework for developers, leaving the practical trade-offs between occupancy and latency for specific large language model kernels largely unverified by independent benchmarks. Understanding these constraints is essential for developers looking to extract peak performance, though it remains to be seen if the complexity of manual tuning outweighs the benefits provided by automated compiler optimizations.