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首页> 外文会议>Signal Processing amp; Its Applications, 2009. CSPA 2009 >Clonal selection algorithm for partitioning and scheduling of codesign systems
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Clonal selection algorithm for partitioning and scheduling of codesign systems

机译：用于代码分配系统分区和调度的克隆选择算法

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In system-level design, applications are presented as task graphs where tasks; i.e. nodes of the graph, have several implementation options differing in some criteria such as time, area and power. Systems designed with this approach are those that are application specific and for performance reasons are implemented in a hardware/software codesign manner. In this paper the most important design issues in these systems i.e. partitioning and scheduling are investigated. Our approach, namely CSPA, is a heuristic algorithm inspired by the biological immune system and attempts to obtain an optimal design for a given system composed of several hardware and software components. We use a graph representation of the system where nodes are operational components and edges are communication links between them. We propose an immune-based approach which based on artificial immune system and apply the clonal selection algorithm as one of the different types of algorithms inspired by biological systems. To date there is no work in this field that uses the clonal selection algorithm for optimization of partitioning. Empirical results show a suitable improvement by using this approach in comparison with traditional evolutionary algorithms and also traditional immune-based approach.
机译：在系统级设计中，应用程序以任务图的形式呈现在其中；即，图的节点具有在某些标准（例如时间，面积和功率）上不同的多个实现选项。用这种方法设计的系统是那些特定于应用程序的系统，并且出于性能原因，这些系统以硬件/软件代码签名的方式实现。本文研究了这些系统中最重要的设计问题，即分区和调度。我们的方法，即CSPA，是一种受生物免疫系统启发的启发式算法，并试图为由多个硬件和软件组件组成的给定系统获得最佳设计。我们使用系统的图形表示，其中节点是操作组件，边缘是它们之间的通信链接。我们提出了一种基于免疫的方法，该方法基于人工免疫系统，并将克隆选择算法作为受生物系统启发的不同类型算法之一。迄今为止，该领域还没有使用克隆选择算法来优化分区的工作。实验结果表明，与传统的进化算法以及传统的基于免疫的方法相比，通过使用这种方法可以得到适当的改进。

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