基于模EVMDD的LUT级联RNS FFT电路

Hiroki Nakahara, Tsutomu Sasao, H. Nakanishi, K. Iwai
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引用次数: 3

摘要

本文提出了一种基于剩余数系统(RNS)的基于LUT级联的FFT电路。为了减少FPGA中查找表(lut)的数量,我们使用了两种技术。第一个是使用RNS对乘数进行函数分解。二是动态范围逐步增大。该电路需要RNS2RNS转换器,它可以将小动态范围转换为大动态范围。为了紧凑地实现RNS2RNS转换器,我们将其分解为一个RNS2Binary转换器和一个Binary2RNS转换器。虽然Binary2RNS转换器可以通过基于多终端多值决策图(MTMDD)的LUT级联实现,但对于传统电路来说,RNS2Binary转换器往往体积较大。因此,我们引入了一个基于模边值多值决策图(mod-EVMDD)的LUT级联。模型- evmdd是一种高效表示RNS2Binary转换器的新型决策图。我们在Xilinx公司的Virtex 6 FPGA上实现了所提出的RNS FFT。与传统二进制FFT实现相比,虽然块ram (bram)数量增加了11.1% ~ 25.0%,但lut数量减少了44.2 ~ 52.2%,最大时钟频率增加了9.3 ~ 41.7%。使用这种技术,我们成功地在可用的FPGA上实现了所需的FFT,因为过多的lut是二进制FFT的瓶颈。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An RNS FFT Circuit Using LUT Cascades Based on a Modulo EVMDD
This paper proposes an FFT circuit based on a residue number system (RNS) using LUT cascades. To reduce the number of look-up tables (LUTs) in an FPGA, we used two techniques. The first one is the functional decomposition of multipliers using RNS. The second one is the increase of the dynamic range stage by stage. The circuit requires the RNS2RNS converter which converts a small dynamic range to a large dynamic range. To compactly realize the RNS2RNS converter, we decompose it into an RNS2Binary converter and a Binary2RNS converter. Although the Binary2RNS converter can be realized by an LUT cascade based on a multi-terminal multi-valued decision diagram (MTMDD), the RNS2Binary converter tend to be large for the conventional circuit. Thus, we introduce an LUT cascade based on a modulo edge-valued multi-valued decision diagram (mod-EVMDD). The mod-EVMDD is a new type of a decision diagram that efficiently represents the RNS2Binary converter. We implemented the proposed RNS FFT on the Xilinx Corp. Virtex 6 FPGA. Compared with the conventional binary FFT implementation, although the number of block RAMs (BRAMs) increased by 11.1-25.0%, the number of LUTs decreased by 44.2-52.2% and the maximum clock frequency increased by 9.3-41.7%. With this technique, we successfully implemented a required FFT on an available FPGA, since the excessive number of LUTs was the bottleneck of the binary FFT.
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