PHAROS: Pipelined Heterogeneous Accelerators for Real-time Safety-critical Systems With Deadline Compliance

TL;DR

PHAROS is a framework for designing spatially partitioned heterogeneous accelerators that guarantees real-time safety in safety-critical systems through schedulability analysis and tailored design space exploration.

Contribution

It introduces real-time-aware design methods, preemption mechanisms, and schedulability analysis for heterogeneous accelerators, addressing safety-critical real-time requirements.

Findings

PHAROS's DSE finds more feasible configurations than throughput-focused methods.

The framework improves real-time performance across diverse applications.

Response-time analysis supports the schedulability guarantees.

Abstract

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.