Modular Mojo Kernels: Portability and Platform Specialization

AI Impact Summary

This document outlines the portability strategy for Structured Mojo Kernels, focusing on a key differentiator: the ability to progressively specialize components for different hardware targets. The core kernel logic remains unchanged, allowing for a single, portable foundation while platform-specific optimizations are applied through modular components. This approach contrasts with traditional GPU programming frameworks like CUTLASS and Triton, which often require significant code duplication or performance degradation on non-NVIDIA hardware. The architecture leverages shared components like tile-based decomposition and layout algebra, combined with platform-specific adaptations in areas such as synchronization primitives and data movement, to achieve optimal performance across AMD MI355X and NVIDIA Blackwell GPUs.