This thesis introduces a framework for automatically determining the weight tables which capture processor characteristics. In result, it simplifies retargetable profiling, increases estimation accuracy, and enables evaluating hardware and software configurations. In particular, the contributions of this work are a comprehensive framework for running benchmarks on different target platforms extracting the execution times metrics. We make a Linear programming formulation that identifies weight table parameters subject to minimizing the overall error over the evaluated benchmarks.

Moazzami_MS14_CalibPerfEst.pdf