SIMD (Single Instruction, Multiple Data) is a parallel computing architecture that allows a single operation to be performed simultaneously on multiple data points, significantly improving performance for data-parallel tasks. It is widely used in applications such as graphics processing, scientific computing, and machine learning to enhance computational efficiency by exploiting data-level parallelism.