Hopefully I will update this to improve my own understanding of SIMD@Arm. I will mainly discover the repository Kleidiai Gitlab Repo

My current understanding of kleidiai is that it is a library that provides a set of ukernels that uses different SIMD technologies @ arm (e.g. NEON, SVE, SVE2, SME2) to accelerate the performance of ML workloads, and then it’s integrated into higher level frameworks like Tensorflow, PyTorch, etc. The scope of this post to try to provide a understanding of different SIMD technologies @ Arm and how kleidiai is using them to accelerate the performance of ML workloads, also why so many different ukernel VARIANTS are needed.