多核嵌入式系统可执行数据流基准生成技术

Jeonggyu Jang, Hoeseok Yang
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引用次数: 0

摘要

随着多核嵌入式系统复杂性的不断增长,多核嵌入式系统的优化与验证变得越来越重要。因此,确保一组合理复杂度的基准测试来验证多核嵌入式系统的设计是非常重要的。数据流模型一直被认为是描述嵌入式系统行为的一种合适的计算模型。在本文中,我们提出了一种用于多核嵌入式系统的数据流基准生成技术,利用两种现有工具:随机数据流拓扑生成器和随机C代码生成器。在该技术中,作为准备步骤,通过随机的C代码生成工具建立C代码数据库,然后由现有的工具生成一个随机的数据流图,每个节点都标注了执行时间信息。对于生成图中的每个节点,根据给定的执行时间信息,适当地选择多个随机生成的C代码段,并将其容纳在单个函数中。在此过程中,导出并求解了一组线性方程。随后,使用现有的基于模型的嵌入式系统设计框架,我们自动生成整个数据流图的可执行基准。此外,为了提高生成代码的准确性,在生成和测试运行后应用了一种简单的校准技术。结果表明,所生成的代码保证了多核嵌入式系统的多样性和复杂性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Executable Dataflow Benchmark Generation Technique for Multi-Core Embedded Systems
As the complexity of multi-core embedded systems continuously grows, the optimization and verification of such systems become non-trivial. Thus, it is important to secure a set of benchmarks of reasonable complexity to validate the design of multi-core embedded systems. Dataflow model has long been considered as a suitable model-of-computation for specifying the behavior of embedded systems. In this paper, we proposes a dataflow benchmark generation technique for multi-core embedded systems, leveraging two existing tools: a random dataflow topology generator and a random C code generator. In the proposed technique, as a preparatory step, a C code database is established by means of a random C code generation tool Then, a random dataflow graph, with execution time information annotated to each node, is generated by an existing tool For each node in the generated graph, a number of randomly generated C code segments are properly chosen and accommodated in a single function as per the given execution time information. In doing so, a set of linear equations are derived and solved. Subsequently, using existing model-based embedded system design frameworks, we automatically generate an executable benchmark for the entire dataflow graph. Further, in order to enhance the accuracy of the generated code, a simple calibration technique is applied after the generation and test runs. It is shown that the generated codes assure the diversity and complexity as embedded software benchmark for multi-core embedded systems.
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