5,210 research outputs found

    Non-power-of-Two FFTs: Exploring the Flexibility of the Montium TP

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    Coarse-grain reconfigurable architectures, like the Montium TP, have proven to be a very successful approach for low-power and high-performance computation of regular digital signal processing algorithms. This paper presents the implementation of a class of non-power-of-two FFTs to discover the limitations and Flexibility of the Montium TP for less regular algorithms. A non-power-of-two FFT is less regular compared to a traditional power-of-two FFT. The results of the implementation show the processing time, accuracy, energy consumption and Flexibility of the implementation

    Low Power Implementation of Non Power-of-Two FFTs on Coarse-Grain Reconfigurable Architectures

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    The DRM standard for digital radio broadcast in the AM band requires integrated devices for radio receivers at very low power. A System on Chip (SoC) call DiMITRI was developed based on a dual ARM9 RISC core architecture. Analyses showed that most computation power is used in the Coded Orthogonal Frequency Division Multiplexing (COFDM) demodulation to compute Fast Fourier Transforms (FFT) and inverse transforms (IFFT) on complex samples. These FFTs have to be computed on non power-of-two numbers of samples, which is very uncommon in the signal processing world. The results obtained with this chip, lead to the objective to decrease the power dissipated by the COFDM demodulation part using a coarse-grain reconfigurable structure as a coprocessor. This paper introduces two different coarse-grain architectures: PACT XPP technology and the Montium, developed by the University of Twente, and presents the implementation of a\ud Fast Fourier Transform on 1920 complex samples. The implementation result on the Montium shows a saving of a factor 35 in terms of processing time, and 14 in terms of power consumption compared to the RISC implementation, and a\ud smaller area. Then, as a conclusion, the paper presents the next steps of the development and some development issues

    A Flexible Implementation of a Matrix Laurent Series-Based 16-Point Fast Fourier and Hartley Transforms

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    This paper describes a flexible architecture for implementing a new fast computation of the discrete Fourier and Hartley transforms, which is based on a matrix Laurent series. The device calculates the transforms based on a single bit selection operator. The hardware structure and synthesis are presented, which handled a 16-point fast transform in 65 nsec, with a Xilinx SPARTAN 3E device.Comment: 4 pages, 4 figures. IEEE VI Southern Programmable Logic Conference 201

    A VLSI pipeline design of a fast prime factor DFT on a finite field

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    A conventional prime factor discrete Fourier transform (DFT) algorithm is used to realize a discrete Fourier-like transform on the finite field, GF(q sub n). A pipeline structure is used to implement this prime factor DFT over GF(q sub n). This algorithm is developed to compute cyclic convolutions of complex numbers and to decode Reed-Solomon codes. Such a pipeline fast prime factor DFT algorithm over GF(q sub n) is regular, simple, expandable, and naturally suitable for VLSI implementation. An example illustrating the pipeline aspect of a 30-point transform over GF(q sub n) is presented
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