This paper develops an arithmetic coding algorithm based on delta recurrent neural network for edge computing devices called DRAC. Our algorithm is implemented on a Xilinx Zynq 7000 Soc board. We evaluate DRAC with four datasets and compare it with the state-of-the-art compressor DeepZip. The experimental results show that DRAC outperforms DeepZip and achieves 5X speedup ratio and 20X power consumption saving.

中文翻译：

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DRAC：一种用于边缘计算的基于增量循环神经网络的算术编码算法

本文开发了一种基于 delta 递归神经网络的算术编码算法，用于称为 DRAC 的边缘计算设备。我们的算法是在 Xilinx Zynq 7000 SoC 板上实现的。我们使用四个数据集评估 DRAC，并将其与最先进的压缩器 DeepZip 进行比较。实验结果表明，DRAC 优于 DeepZip，实现了 5 倍的加速比和 20 倍的功耗节省。