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RTSS2025顶会

TSI: A Time-Semantic Instruction Set for Deterministic Data-Flow Execution in Real-Time Embedded Systems

Yinkang Gao, Bo Zhang, Yixuan Zhu, Lei Gong, Teng Wang, Wenqi Lou, Chao Wang, Xi Li, Xuehai Zhou

2025年份
1被引次数

摘要

Real-Time Embedded Systems (RTES) are widely used in safety-critical devices, where deterministic data flow is essential to system verification and reliable execution. It requires that each consumer task instance reads data from the deterministic producer task instance. In software based on general-purpose computing instruction sets, communication-related instruction execution order couples data flow among tasks, necessitating a deterministic execution order of these instructions to preserve data-flow determinism. However, enforcing this order complicates software, and suffers from priority inversion and variable execution overheads, which significantly increases task worst-case response times (WCRT) and response time variability. This paper identifies the cause of above issues as the semantics of general-purpose instruction sets, under which dataflow determinism relies on the deterministic execution order of communication-related instructions. To address this, we make the following contributions. First, we propose Time-Semantic Instruction set (TSI), which supports memory access using both addresses and timestamps. TSI enables data-flow determinism without strict instruction ordering. Second, we design a TSI-enabled implementation compatible with conventional memory systems. Third, we provide two TSI-based deterministic data-flow programming paradigms, along with correctness proofs. Finally, we evaluate TSI hardware cost and implement a cycle-accurate simulator based on a TSI-extended RISC-V. Experiments demonstrate that, under reasonable memory overhead, our approach reduces programming complexity and achieves up to21.6×21.6 \timesreduction in WCRT and up to89.6×89.6 \timesreduction in response time variability compared to existing methods.

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