Hard real-time systems like image processing, autonomous driving, etc. require an increasing need of computational power that classical multi-core platforms can not provide, to fulfill with their timing constraints. Heterogeneous Instruction Set Architecture (ISA) platforms allow accelerating real-time workloads on application-specific cores (e.g. GPU, DSP, ASICs) etc. and are suitable for these applications. In addition, these platforms provide larger design choices as a given functionnality can be implemented onto several types of compute elements. HPC-DAG (Heterogeneous Parallel Directed Acyclic Graph) task model has been recently proposed to capture real-time workload execution on heterogeneous platforms. It expresses the ISA heterogeneity, and some specific characteristics of hardware accelerators, as the absence of preemption or costly preemption, alternative implementations and on-line conditional execution. In this paper, we propose a time-table scheduling approach to allocate and schedule a set of HPC-DAG tasks onto a set of heterogeneous cores, by the mean Integer Linear Programming (ILP). Our design allows to handle heterogeniety of resources, on-line execution costs, and a faster solving time, by exploring gradually the design space
翻译:此外,这些平台提供了更大的设计选择,因为某些功能可以适用于若干类型的计算要素。最近提议了HPC-DAG任务模型(HPC-DAG)来捕捉不同平台的实时工作量执行。该模型表示ISA的异质性以及硬件加速器的某些具体特征,因为没有预设性或昂贵的预设性、替代性实施和在线有条件执行。在本文中,我们提议采用一个时间表表办法,通过平均的 Integer 线性规划(ILPP) 将一套HPC-DAG任务分配给一组混杂核心并安排在一组混杂的核心上进行分配和安排。我们的设计可以以更快的方式处理空间设计成本,并逐步解决空间设计成本问题。