戴紫彬1
1.解放军信息工程大学 郑州 450001
2.铁道警察学院 郑州 450053
详细信息
作者简介:李盛：男，1984年生，副教授，博士，研究方向为可重构计算与安全专用新芯片编译技术
戴紫彬：男，1966年生，教授，博士，研究方向为可重构计算与安全专用新芯片设计
通讯作者:李盛 lisheng@rpc.edu.cn
中图分类号:TN918.2; TP314计量
文章访问数:290
HTML全文浏览量:87
PDF下载量:32
被引次数:0
出版历程
收稿日期:2020-05-12
修回日期:2021-01-12
网络出版日期:2021-02-02
刊出日期:2021-09-16
Research on Automatic Mapping Method of Reconfigurable Block Cipher Instruction Set Processor
Sheng LI1, 2,,,Zibin DAI1
1. The PLA Information Engineering University, Zhengzhou 450001, China
2. Railway Police College, Zhengzhou 450053, China
摘要
摘要:计算资源与寄存器资源分配是可重构处理器自动并行映射的重要问题，该文针对可重构分组密码指令集处理器的资源分配问题，建立算子调度参数模型和处理器资源参数模型，研究了分组密码并行调度与资源消耗之间的约束关系；在此基础上提出基于贪婪思维、列表调度和线性扫描的自动映射算法，实现了分组密码在可重构分组密码指令集处理器上的自动映射。通过可用资源变化实验验证算法并行映射的有效性，并对AES-128算法的映射效果做了横向对比验证算法的先进性，所提自动映射算法对分组密码在可重构处理中的并行计算研究有一定的指导意义。
关键词:可重构分组密码指令集处理器/
自动映射/
资源分配/
列表调度/
线性扫描
Abstract:The allocation of computing resources and register resources is an important issue for automatic parallel mapping of reconfigurable processors. In this paper, for the resource allocation of reconfigurable block cipher instruction set processors, an operator scheduling parameter model and processor resource parameter model are established, and the constraint relationship between the parallel scheduling of block ciphers and resource consumption is studied; Consequently, an automatic mapping algorithm based on greedy thinking, list scheduling and linear scanning is proposed to realize the block cipher atuomatic mapping on the reconfigurable block cipher instruction set processor. The experiment verifies the effect of the algorithm’s parallel scheduling under different resource constraints, and the contrast of AES-128 algorithm’s mapping effect is made to verify the progress of the algorithm, which obtains certain significance for the parallel computing research of block ciphers in reconfigurable processing.
Key words:Reconfigurable block cipher instruction set processor/
Automatic mapping/
Resource allocation/
List scheduling/
Linear scan
PDF全文下载地址:
https://jeit.ac.cn/article/exportPdf?id=15e1efbc-2485-4e40-bab8-d73368542ba9
