1.数学工程与先进计算国家重点实验室,河南郑州 450001
2.郑州大学计算机与人工智能学院, 河南郑州 450001
[ "陈晓杰 男,1993年12月出生,河南武陟人.现为战略支援部队信息工程大学博士研究生,从事可重构计算、信息安全方面的有关研究.E-mail:cctvlibin@163.com" ]
[ "李斌男,1986年12月出生,河南郑州人. 现为郑州大学计算机与人工智能学院讲师,主要从事可重构计算、信息安全方面的有关研究.E-mail:cctvlibin@163.com" ]
[ "周清雷男,1962 年9 月出生,河南郑州人. 教授、博士生导师. 主要从事自动机理论、信息安全和计算复杂性理论方面的有关研究." ]
收稿:2021-04-07,
修回:2022-04-09,
纸质出版:2022-07-25
移动端阅览
陈晓杰,李斌,周清雷.RTL级可扩展高性能数据压缩方法实现[J].电子学报,2022,50(07):1548-1557.
CHEN Xiao-jie,LI Bin,ZHOU Qing-lei.Implementation of RTL Scalable High-Performance Data Compression Method[J].ACTA ELECTRONICA SINICA,2022,50(07):1548-1557.
陈晓杰,李斌,周清雷.RTL级可扩展高性能数据压缩方法实现[J].电子学报,2022,50(07):1548-1557. DOI: 10.12263/DZXB.20210448.
CHEN Xiao-jie,LI Bin,ZHOU Qing-lei.Implementation of RTL Scalable High-Performance Data Compression Method[J].ACTA ELECTRONICA SINICA,2022,50(07):1548-1557. DOI: 10.12263/DZXB.20210448.
针对传统的数据压缩实现方法处理性能较低,难以满足高速网络高负载、低能耗要求,本文提出了基于FPGA(Field-Programmable Gate Array)的高性能数据压缩方法.在数据计算方面,定制化一种专用并行数据匹配方法,并对压缩算法进行子任务划分,设计细粒度的串/并混合结构实现数据压缩和数据编码;在数据存储方面,设计了面向硬件的专用高效字典处理,并采用多级缓存机制优化访存结构;基于FPGA的资源面积,设计了多通道、可扩展数据压缩结构,并采用轮询策略实现多通道的数据分配和回收;在优化过程中,采用RTL(Register Transfer Level)实现数据压缩算法.实验结果表明优化后的压缩算法与CPU相比达到了1.634的加速比,吞吐量为4.33 Gb/s.
As the low processing performance makes traditional data compression implementation methods difficult to meet the high load and low energy consumption requirements of high-speed networks
a high-performance data compression method based on field-programmable gate array is proposed. In terms of data calculation
this paper customize a dedicated parallel data matching method
divide the compression algorithm into sub-tasks
and design a fine-grained serial/parallel hybrid structure to achieve data compression and data encoding. In terms of data storage
a dedicated and efficient dictionary processing for hardware is designed
and a multi-level cache mechanism is used to optimize the memory access structure. Based on the resource area of FPGA
a multi-channel
scalable data compression structure is designed
and a polling strategy is used to realize multi-channel data allocation and recovery. In the optimization process
register transfer level is used to realize the data compression algorithm. The experimental results show that the optimized compression algorithm achieves a speedup ratio of 1.634 compared with the CPU
with a throughput of 4.33 Gb/s.
周俊 , 沈华杰 , 林中允 , 等 . 边缘计算隐私保护研究进展 [J]. 计算机研究与发展 , 2020 , 57 ( 10 ): 2027 - 2051 .
ZHOU Jun , SHEN Hua-jie , LIN Zhong-yun , et al . Research advances on privacy preserving in edge computing [J]. Journal of Computer Research and Development , 2020 , 57 ( 10 ): 2027 - 2051 . (in Chinese)
HOSSAIN K , RAHMAN M , ROY S . IoT data compression and optimization techniques in cloud storage: Current prospects and future directions [J]. International Journal of Cloud Applications and Computing , 2019 , 9 ( 2 ): 43 - 59 .
WENCHANG L , BOYUAN G , GUOHUI L . Communication scheduling in data gathering networks of heterogeneous sensors with data compression: Algorithms and empirical experiments [J]. European Journal of Operational Research , 2018 , 271 ( 2 ): 462 - 473 .
AL-HAFEEDH A , CROCHEMORE M , ILIE L , et al . A comparison of index-based lempel-Ziv LZ77 factorization algorithms [J]. ACM Computing Surveys , 2012 , 45 ( 1 ): 1 - 17 .
HASSAN K , ALAA A , VIKTAR U , et al . New modified RLE algorithms to compress grayscale images with lossy and lossless compression [J]. International Journal of Advanced Computer Science and Applications , 2016 , 7 ( 7 ): 250 - 255 .
DATTA A , NG K F , BALAKRISHNAN D , et al . A data reduction and compression description for high throughput time-resolved electron microscopy [J]. Nature Communications , 2021 , 12 : 664 .
FANG J , CHEN J Y , AL-ARS Z , et al . Work-in-progress: A high-bandwidth snappy decompressor in reconfigurable logic [C]// 2018 International Conference on Hardware/Software Codesign and System Synthesis(CODES+ISSS) . Turin : IEEE , 2018 : 1 - 2 .
XIA MING , HUANG ZUNKAI , TIAN LI , et al . SparkNoC: An energy-efficiency FPGA-based accelerator using optimized lightweight CNN for edge computing [J]. Journal of Systems Architecture , 2021 , 115 ( 4 ): 101991 .
COUSINS D , ROHLOFF K , SUMOROK D . Designing an FPGA-accelerated homomorphic encryption co-processor [J]. IEEE Transactions on Emerging Topics in Computing , 2017 , 5 ( 2 ): 193 - 206 .
ZHANG B , SANDER P V , TSUI C Y , et al . Microshift: An efficient image compression algorithm for hardware [J]. IEEE Transactions on Circuits and Systems for Video Technology , 2019 , 11 ( 29 ): 3430 - 3443 .
TRUONG N M , AOKI M , IGARASHI Y , et al . Real-time lossless compression of waveforms using an FPGA [J]. IEEE Transactions on Nuclear Science , 2018 , 65 ( 9 ): 2650 - 2656 .
INC Xilinx . Xilinx Snappy-Streaming Compression and Decompression [EB/OL]. ( 2021-09-22 )[ 2022-02-28 ]. https://xilinx.github.io/Vitis_Libraries/data_compression/2021.1/source/L2/snappy.html https://xilinx.github.io/Vitis_Libraries/data_compression/2021.1/source/L2/snappy.html .
王超 , 王腾 , 马翔 , 周学海 . 基于FPGA的机器学习硬件加速研究进展 [J]. 计算机学报 , 2020 , 43 ( 6 ): 1161 - 1182 .
WANG Chao , WANG Teng , MA Xiang , ZHOU Xue-hai . Research progress on FPGA-based machine learning hardware acceleration [J]. Chinese Journal of Computers , 2020 , 43 ( 6 ): 1161 - 1182 . (in Chinese)
LIU W , MEI F , WANG C , et al . Data compression device based on modified LZ4 algorithm [J]. IEEE Trans Consumer Electronics , 2018 , 64 ( 1 ): 110 - 117 .
KIM J , CHO J . Hardware-accelerated fast lossless compression based on LZ4 algorithm [C]// Proceedings of the 3rd International Conference on Digital Signal Processing . Jeju Island : ACM , 2019 : 65 - 68 .
0
浏览量
6
下载量
1
CSCD
关联资源
相关文章
相关作者
相关机构
京公网安备11010802024621