Emma Kujala developed a decomposition pass for the fmod operator on the Arm backend in the pytorch/executorch repository, targeting optimization of floating-point modulus operations. Using Python and leveraging PyTorch’s backend development capabilities, Emma designed and implemented an algorithm that improves numeric correctness and performance for Arm architectures. The work included comprehensive testing, covering a wide range of edge cases such as extreme values and NaNs, to ensure robust and reliable behavior. This feature not only enhanced the backend’s robustness but also established a foundation for future Arm-specific optimizations, demonstrating depth in algorithm design and a methodical approach to testing.