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Model-based optimization of High Level Synthesis directives

机译:基于模型的高级合成指令优化

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High Level Synthesis (HLS) tools improve the speed of FPGA hardware design entry compared to traditional hardware description languages by raising the level of design abstraction. Using compiler directives to guide the tool, a wide variety of hardware architectures can be obtained without modification of the original behavioural code. However, selecting an optimal application of directives from this large design space can be daunting and time-consuming for a designer since evaluating a particular setting of directives requires running the FPGA tool flow. This work considers the use of sequential model-based optimization (SMBO) methods for automatically selecting directive settings. These methods construct models of the design space to guide the optimization process and minimize the number of tool evaluations. In this paper, we evaluate the use of SMBO for selecting HLS directives and extend the method to relate multiple uses of the same directive within a design. We observe that SMBO can quickly find optimal directive settings in a space of tens of thousands of possible directive configurations and find that our proposed extension can further improve the convergence rate over the standard method.
机译:高级合成(HLS)工具通过提高设计抽象水平,提高传统硬件描述与传统硬件描述相比的FPGA硬件设计条目的速度。使用编译器指令来指导工具,可以在不修改原始行为代码的情况下获得各种硬件架构。但是,从该大型设计空间中选择最佳应用程序可能对设计者来说是令人生畏和耗时,因为评估指令的特定设置需要运行FPGA刀具流程。此工作考虑使用基于模型的优化(SMBO)方法来自动选择指令设置。这些方法构造了设计空间的模型,以指导优化过程并最大限度地减少工具评估的数量。在本文中,我们评估了SMBO用于选择HLS指令的使用,并扩展了在设计内相关的方法以在设计中进行多种使用。我们观察到SMBO能够迅速在可能的指令配置数以万计的空间,找到最优的指令设置,并发现我们建议的延长,可进一步提高在标准方法的收敛速度。

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