Automatic Extraction of Task-Level Parallelism for Heterogeneous MPSoCs

Heterogeneous multi-core platforms are increasingly attractive for embedded applications due to their adaptability and efficiency. This proliferation of heterogeneity demands new approaches for extracting thread level parallelism from sequential applications which have to be efficient at runtime. We present, to the best of our knowledge, the first Integer Linear Programming (ILP)-based parallelization approach for heterogeneous multi-core platforms. Using Hierarchical Task Graphs and high-level timing models, our approach manages to balance the extracted tasks while considering performance differences between cores. As a result, we obtain considerable speedups at runtime, significantly outperforming tools for homogeneous systems. We evaluate our approach by parallelizing standard benchmarks from various application domains.