Amphisbaena: Modeling two orthogonal ways to hunt on heterogeneous many-cores

Heterogeneous many-cores can deliver high performance or energy efficiency. There are two orthogonal ways to improve performance: 1) scale-out by exploiting thread-level parallelism, and 2) scale-up by enabling core heterogeneity. Predicting the performance of such architecture is increasingly challenging. We propose a comprehensive performance model Amphisbaena, or Φ, built from two orthogonal functions α and β. Function α describes the scale-out speedup and function β handles the scale-up speedup. The Φ model can clearly tell not only the overall speedup of a given multithreading and core mapping strategy, but also how to improve the multithreading and core mapping, hence should be a promising performance predictor for future heterogenous many-cores. The results show that Φ model´s error rate is within 12%, which is lower than state-of-the-art methods. We demonstrate the application of Φ model by introducing a heuristic scheduling algorithm, which outperforms the baselines by 13% on average.