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Area efficient floating-point FFT butterfly architectures based on multi-operand adders

机译:基于多操作数加法器的面积有效的浮点FFT蝶形架构

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Hardware implementation of the fast Fourier transform (FFT) function consists of multiple consecutive arithmetic operations over complex numbers. Applying floating-point arithmetic to FFT coprocessors leads to a wider dynamic range and allows the coprocessor to collaborate with general purpose processors via the standard floating-point arithmetic. This offloads compute-intensive tasks from the primary processor and overcomes floating-point concerns such as scaling and overflow/underflow detection. The downside, however, is that floating-point units are slower than the fixed-point counterparts. One of the popular ways to improve the speed of floating-point FFT units is to merge the arithmetic operations inside the butterfly units of a FFT architecture. This leads to a butterfly architecture based on multi-operand adders. Butterfly units are designed, in two of the most recent works, using three-operand and four-operand adders. However, the work reported here by the present authors goes further and a butterfly architecture based on a five-operand adder is proposed. Simulation results demonstrate that the proposed butterfly architecture is 50% smaller than the fastest previous work with about 17% latency overhead. Compared with the smallest previous work, the proposed design is 47% smaller and 8% faster.
机译:快速傅立叶变换(FFT)功能的硬件实现包括对复数的多个连续算术运算。将浮点算术应用于FFT协处理器会导致更宽的动态范围,并允许协处理器通过标准浮点算术与通用处理器协作。这减轻了主处理器的计算密集型任务的负担,并克服了浮点问题,例如扩展和上溢/下溢检测。但是,不利的是浮点单位比定点单位慢。改善浮点FFT单元速度的一种流行方法是将算术运算合并到FFT体系结构的蝶形单元内部。这导致基于多操作数加法器的蝶形架构。在最近的两部作品中,使用三操作数和四操作数加法器设计了蝶形单元。然而,本作者在这里报告的工作进一步进行,并提出了一种基于五操作数加法器的蝶形架构。仿真结果表明,提出的蝶形架构比之前最快的工作小了50%,而延迟开销却只有17%。与以前的最小工作相比,拟议的设计小47%,快8%。

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  • 来源
    《Electronics Letters》 |2015年第12期|895-897|共3页
  • 作者

    Kaivani Amir; Seok-Bum Ko;

  • 作者单位

    Electr. & Comput. Eng. Dept., Univ. of Saskatchewan, Saskatoon, SK, Canada;

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  • 正文语种 eng
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