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Hybrid Wordlength Optimization Methods of Pipelined FFT Processors

机译:流水线FFT处理器的混合字长优化方法

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Quickly and accurately predicting of the performance based on the requirements for IP-based system implementations optimizes design and reduces design time and overall cost. This study describes a novel hybrid method for the wordlength optimization of pipelined FFT processors that is the arithmetic kernel of OFDM-based systems. This methodology utilizes the rapid computing of statistical analysis and the accurate evaluation of simulation-based analysis to investigate a speedy optimization flow. A statistical error model for varying wordlengths of PE stages of an FFT processor was developed to support this optimization flow. Experimental results designate that the wordlength optimization employing the speedy flow reduces the percentage of the total area of the FFT processor that increases with an increasing FFT length. Finally, the proposed hybrid method requires shorter prediction time than the absolute simulation-based method does and achieves more accurate outcomes than a statistical calculation does.
机译:根据基于IP的系统实现的要求,快速,准确地预测性能,可以优化设计并减少设计时间和总体成本。这项研究描述了一种新颖的混合方法,用于流水线FFT处理器的字长优化,它是基于OFDM的系统的运算核心。这种方法利用统计分析的快速计算和基于仿真的分析的准确评估来研究快速的优化流程。为了支持这种优化流程,开发了用于FFT处理器PE级的不同字长的统计误差模型。实验结果表明,采用快速流的字长优化减少了FFT处理器总面积的百分比,该百分比随着FFT长度的增加而增加。最后,与基于绝对模拟的方法相比,所提出的混合方法需要更短的预测时间,并且比统计计算所需要的更准确。

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