CoMEt: x86 Cost Model Explanation Framework

ML-based program cost models have been shown to yield highly accurate predictions. They have the capability to replace heavily-engineered analytical program cost models in mainstream compilers, but their black-box nature discourages their adoption. In this work, we propose the first method for obtaining faithful and intuitive explanations for the throughput predictions made by ML-based cost models. We demonstrate our explanations for the state-of-the-art ML-based cost model, Ithemal. We compare the explanations for Ithemal with the explanations for a hand-crafted, accurate analytical model, uiCA. Our empirical findings show that high similarity between explanations for Ithemal and uiCA usually corresponds to high similarity between their predictions.