소개
This skill provides specialized guidance for parallelizing Mojo code using Single Instruction, Multiple Data (SIMD) techniques. It helps developers identify performance bottlenecks in loops, calculate hardware-specific SIMD widths using compile-time constants, and implement vectorized load/store patterns. By automating the transformation of scalar computations into vector operations and providing robust strategies for remainder handling, it enables Mojo applications to achieve significant performance gains, typically ranging from 4x to 8x speedups in tensor-heavy AI and machine learning workloads.