一种基于阵列配置加速比模型的无损压缩算法

徐金甫; 刘露; 李伟; 王周闯; 杨宇航

doi:10.11999/JEIT170900

一种基于阵列配置加速比模型的无损压缩算法

doi: 10.11999/JEIT170900

1.
(解放军信息工程大学郑州 450001) ②(复旦大学专用集成电路与系统国家重点实验室上海 201203)

基金项目:

国家自然科学基金(61404175)

计量
- 文章访问数: 1228
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- 被引次数: 0
出版历程
- 收稿日期: 2017-09-22
- 修回日期: 2018-04-13
- 刊出日期: 2018-06-19

A New Lossless Compression Algorithm Based on Array Configuration Speedup Model

1.
(The PLA Information Engineering University, Zhengzhou 450001, China)

Funds:

The National Natural Science Foundation of China (61404175)

摘要

摘要: 针对现有压缩算法通过增加复杂度来降低压缩率，获得信息高效传输的问题。该文提出阵列配置加速比模型，证明低压缩率不一定能提高传输效率，并找到影响信息传输效率的因子，即解压模块吞吐率和数据块压缩率。将影响因子与配置信息特征结合，设计了一种新的无损压缩算法，并硬件实现了解压模块，吞吐率可达到16.1 Gbps。采用AES, A5-1和SM4对无损压缩算法进行测试，然后与主流无损压缩算法LZW, Huffman, LPAQ1和Arithmetic对比。结果表明，整体压缩率相当，但该文压缩算法产生的数据块压缩率经过优化，不仅能满足加速需求，且具有高吞吐率的解压性能；该文无损压缩算法获得的配置加速比，比硬件吞吐率理想情况下的LPAQl, Arithmetic, Huffman, LZW算法分别高8%, 9%, 10%, 22%左右。
- 阵列 /
- 配置加速比 /
- 无损压缩 /
- 吞吐率 /
- 压缩率
Abstract: In order to obtain efficient information transmission, the existing compression algorithms reduce the compression ratio by increasing complexity. In view of this problem, an array configuration speedup model is proposed in this paper. It is proved that low compression ratio may not improve the transmission efficiency and the factors, decompression module throughput and data block compression rate which affect the efficiency of information transmission, are found. Combined the influencing factors with the configuration information, a new lossless compression method is designed and the decompression hardware circuit is implemented, whose throughput can reach 16.1 Gbps. The lossless compression algorithm is tested using AES, A5-1 and SM4. Compared with the mainstream lossless compression algorithms LZW, Huffman, LPAQ1 and Arithmetic, the results show that the overall compression ratio is equivalent. However, the compression ratio of data block generated by the compression algorithm is optimized, which can not only meet the demand of acceleration, but also possesses high throughput decompression performance. The configuration speedup ratio obtained by lossless compression algorithm is about 8%, 9%, 10% and 22% higher than LPAQl, Arithmetic, Huffman, and LZW with ideal hardware throughput.
- Array /
- Configuration speedup /
- Lossless compression /
- Throughput /
- Compression ratio

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