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A Data-Driven Paradigm to Develop and Tune Data-Driven Realtime System

机译:一种数据驱动的范例来开发和调整数据驱动的实时系统

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The authors have studied RESCUE (Realtime Execution System for CUE-series data-driven processors) which supports performance prediction, verification and tuning for realtime multi-processing system based on CUE processors. This paper proposes a data-driven paradigm totally supports development with considering both of user's requirements and engineering constraints. In the paradigm, a user defines functional specification and performance specification. The former describes at least algorithm and data-structure. The latter includes at least turnaround time and dataflow rate. The engineering constraints covers pipeline configuration and instruction set. In this paper, the authors firstly propose data-driven schema-based specification for turnaround time, dataflow rate and pipeline configuration. Implementation for realtime verification of turnaround time and processor load follows. This paper then proposes a scheme to localize emulation target, and discusses implementation to generate initial state and input stream needed for the localization. Lastly this paper preliminarily evaluates and shows interactiveness of RESCUE.
机译:作者已经研究了基于提示处理器的实时多处理系统的性能预测,验证和调整的救援(用于提示系列数据驱动处理器的实时执行系统)。本文提出了一种数据驱动的范例,他们通过考虑用户的要求和工程限制来完全支持开发。在范例中,用户定义了功能规范和性能规范。前者至少描述了至少算法和数据结构。后者至少包括周转时间和数据流率。工程限制涵盖流水线配置和指令集。在本文中,作者首先提出了基于模式的基于模式的周转时间,数据流率和管道配置规范。随后的周转时间和处理器负载实时验证的实现。然后,本文提出了一种对本地化仿真目标的方案,并讨论实现以生成本地化所需的初始状态和输入流。最后,本文初步评估并显示救援的互动。

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