autovectorize
Autovectorize, also known as auto-vectorization, is a compiler or language feature that automatically converts scalar operations and loops into vectorized instructions that operate on multiple data elements per cycle using SIMD (single instruction, multiple data) units. The goal is to improve performance for data-parallel workloads without requiring explicit vector code from the programmer.
How autovectorization works varies by compiler, but generally it analyzes loops to identify independent iterations, memory
Commonly used in C, C++, and Fortran, autovectorization is supported by modern compilers such as GCC, Clang/LLVM,
Limitations of autovectorization include conservative analysis that may miss parallelism, dependencies introduced by pointers or complex