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A New Approach to Implement Discrete Wavelet Transform on Coarse-Grained Reconfigurable Architecture

机译:一种在粗粒度可重构架构上实现离散小波变换的新方法

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Discrete Wavelet Transform (DWT) is widely-used in image and video processing with high computing complexity and regular data flow, which is suitable for the implementation on a Coarse-grained Reconfigurable Architecture (CGRA) owing to its rich parallel computing resources. In this article, the two wavelet filters adopted in JPEG2000 image standard, 5/3 DWT and 9/7 DWT, were realized on a CGRA platform called Reconfigurable Multimedia System-II (REMUS-II). The result shows that the CGRA-based implementation has advantage in area, power and performance over the state-of the-art GPU including 7800GTX and 9800GTX. The die size and power consumption of REMUS-II is respectively less than 1% and 10% compared to the GPU implementations, whereas the performance speed-up is 92.9x for 9/7 filter compared to GPU 7800GTX and 6.54x for 5/3 filter compared to GPU 9800GTX.
机译:离散小波变换(DWT)广泛应用于具有高计算复杂性和常规数据流的图像和视频处理中,这适用于由于其丰富的并行计算资源而在粗粒化可重构架构(CGRA)上。 在本文中,在称为可重新配置多媒体系统-II(REMUS-II)的CGRA平台上实现了JPEG2000图像标准,5/3 DWT和9/7 DWT中采用的两个小波滤波器。 结果表明,基于CGRA的实现在包括最先进的GPU的区域,功率和性能中具有优势,包括7800GTX和9800GTX。 与GPU实现相比,REMUS-II的芯片尺寸和功耗分别小于1%和10%,而性能加速为92.9倍,而9/7滤波器与GPU 7800GTX和5/3的6.54x相比 滤波器与GPU 9800GTX相比。

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