快速和高效的堆排序IP图像压缩应用程序

Yuhui Bai, S. Z. Ahmed, B. Granado
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引用次数: 1

摘要

我们提出了一种堆排序算法的硬件架构,该排序被用于基于小波的图像编码器的子带编码块,称为Öktem图像编码器[1]。虽然这种编码器提供了良好的图像质量,但排序耗时,并且是特定于应用程序的,因为在子带编码中对不同数量的数据重复使用排序,因此在运行时难以扩展具有固定排序容量的简单硬件实现。为了解决这个问题,必须考虑时间/功率效率和分拣大小的灵活性。我们在Zabołotny[2]的基础上提出了一种改进的FPGA堆排序架构,作为图像编码器的IP加速器。通过使用自适应层启用元素,提出了一种可配置的体系结构,以便在运行时调整排序容量,从而有效地对不同数量的数据进行排序。在自适应内存关闭的情况下,我们改进的架构与基线实现相比,内存功耗降低了20.9%。此外,与ARM cortex相比,我们的架构提供了13倍的加速。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fast and Power Efficient Heapsort IP for Image Compression Application
We present a hardware architecture of a heapsort algorithm, the sorting is employed in a subband coding block of a wavelet-based image coder termed Öktem image coder [1]. Although this coder provides good image quality, the sorting is time consuming, and is application specific, as the sorting is repetitively used for different volume of data in the subband coding, thus a simple hardware implementation with fixed sorting capacity will be difficult to scale during runtime. To tackle this problem, the time/power efficiency and the sorting size flexibility have to be taken in to account. We proposed an improved FPGA heapsort architecture based on Zabołotny's work [2] as an IP accelerator of the image coder. We present a configurable architecture by using adaptive layer enable elements so the sorting capacity could be adjusted during runtime to efficiently sort different amount of data. With the adaptive memory shutdown, our improved architecture provides up to 20.9% power reduction on the memories compared to the baseline implementation. Moreover, our architecture provides 13x speedup compared to ARM CortexA9.
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