Correlating Cost with Performance in LLVM

A common technique to exploit data level parallelism is code vectorization. When performed by a compiler, it needs to find a valid vectorization and assess its benefit. In LLVM, this analysis is based on a cost calculation, which will approve the transformation if the cost of the vectorized code is lower than the original scalar code. However, the calculated cost does not correlate to the actual speedup gain. We therefore propose a pluggable cost model that correctly accounts for vectorization overheads and further features of the target hardware platform. Using such a platform specific model, the compiler can assess a code transformation’s impact on application performance, make safe choices whether to transform or not, and compare different optimization options.