Spatially partitioned heterogeneous accelerators (HAs) are increasingly adopted in embedded systems for their performance and flexibility. Yet most existing HA design frameworks optimize primarily for throughput or quality-of-service (QoS) metrics. They often overlook safety-critical real-time requirements, including hardware support for predictable execution, real-time-aware design space exploration (DSE), and rigorous schedulability analysis. These requirements are essential in safety-critical applications such as smart transportation, where schedulability guarantees directly affect system safety. To address this gap, we present PHAROS, a real-time-centric HA design framework. PHAROS introduces preemption mechanisms and scheduler designs for spatially partitioned HAs under first-in-first-out (FIFO) and earliest-deadline-first (EDF) policies. Leveraging modern real-time theory, we further develop a soft real-time (SRT) schedulability-oriented DSE with objectives and constraints tailored to SRT schedulability. Through comprehensive modeling, analysis, and evaluation across diverse applications, we show that PHAROS's DSE discovers more feasible configurations for a broader range of task sets than throughput-oriented DSE baselines while delivering improved real-time performance. We also provide response-time analyses for the supported scheduling algorithms.

翻译：空间分区异构加速器因其性能和灵活性而在嵌入式系统中日益普及。然而，现有大多数异构加速器设计框架主要针对吞吐量或服务质量指标进行优化，往往忽视安全关键实时需求，包括对可预测执行的硬件支持、实时感知的设计空间探索以及严格的可调度性分析。这些需求在智能交通等安全关键应用中至关重要，因为可调度性保证直接影响系统安全性。为弥补这一空白，我们提出PHAROS，一个以实时为中心的异构加速器设计框架。PHAROS为空间分区异构加速器引入抢占机制和调度器设计，支持先入先出和最早截止时间优先策略。利用现代实时理论，我们进一步开发了面向软实时可调度性的设计空间探索方法，其目标和约束均针对软实时可调度性定制。通过跨多样化应用的全面建模、分析和评估，我们证明PHAROS的设计空间探索相比面向吞吐量的基线方法，能为更广泛的任务集发现更多可行配置，同时提供更优的实时性能。我们还对所支持的调度算法提供了响应时间分析。