Session

DescriptionThis section presents new developments in embedded modeling, software and architecture. The first paper develops a deep-to-shallow transformable neural architecture search; the second one focuses on efficient code generation for data-intensive Simulink models; the third paper presents a framework of translating regular expressions. The fourth paper investigates a dynamic mechanism for reducing control flow divergence in GPUs. The next paper investigates methods to boost the efficiency of data deduplication; the sixth one develops code optimization schemes to accelerate stencil code kernels; the seventh paper investigates a novel approach to decompose tasks on intermittent computing systems; and the last one proposes a light-weighted idle time stealing strategy.