Ralf Karrenberg presents Whole-Function Vectorization (WFV) an approach that allows a compiler
to automatically create code that exploits data-parallelism using SIMD instructions.
Data-parallel applications such as particle simulations stock option price estimation or video
decoding require the same computations to be performed on huge amounts of data. Without WFV
one processor core executes a single instance of a data-parallel function. WFV transforms the
function to execute multiple instances at once using SIMD instructions. The author describes an
advanced WFV algorithm that includes a variety of analyses and code generation techniques. He
shows that this approach improves the performance of the generated code in a variety of use
cases.
