Parallelizing compilers are a promising solution to tackle key challenges of MPSoC programming. One fundamental aspect foraprofitable parallelization is to estimate the performance of the applications on the target platforms. There is a wide range of state-of-theart performance estimation techniques, such as, simulation-based, measurement-based, among others. They provide performance estimates typically only at function or basic block granularity. However, MPSoC compilers require performance information at other granularities, such as statement, loopor even arbitrary code blocks. In this paper, we propose a framework to adapt performance information sources to any granularity required by an MPSoC compiler.