针对二进制域上现有求逆算法计算量大、并行度小、速度慢的缺点进行改进,基于二元Euclidean算法提出了改进,设计了相应的乘法器硬件结构,并且分析了其运算效能和资源占用情况。将此求逆计算器的并行改进算法使用Verilog语言编程实现,利...针对二进制域上现有求逆算法计算量大、并行度小、速度慢的缺点进行改进,基于二元Euclidean算法提出了改进,设计了相应的乘法器硬件结构,并且分析了其运算效能和资源占用情况。将此求逆计算器的并行改进算法使用Verilog语言编程实现,利用Xilinx ISE 12.4对整个求逆算法综合仿真(行为级),在Xilinx Virtex-5 XC5VFX70T的硬件平台上验证求逆算法的运算效率,结果表明对求逆算法的改进有效地提高了求逆运算的速度。展开更多
Recently, cryptographic applications based on finite fields have attracted much attention. The most demanding finite field arithmetic operation is multiplication. This investigation proposes a new multiplication algor...Recently, cryptographic applications based on finite fields have attracted much attention. The most demanding finite field arithmetic operation is multiplication. This investigation proposes a new multiplication algorithm over GF（2^m） using the dual basis representation. Based on the proposed algorithm, a parallel-in parallel-out systolic multiplier is presented, The architecture is optimized in order to minimize the silicon covered area （transistor count）. The experimental results reveal that the proposed bit-parallel multiplier saves about 65% space complexity and 33% time complexity as compared to the traditional multipliers for a general polynomial and dual basis of GF（2^m）.展开更多
In general, there are three popular basis representations, standard （canonical, polynomial） basis, normal basis, and dual basis, for representing elements in GF（2^m）. Various basis representations have their disti...In general, there are three popular basis representations, standard （canonical, polynomial） basis, normal basis, and dual basis, for representing elements in GF（2^m）. Various basis representations have their distinct advantages and have their different associated multiplication architectures. In this paper, we will present a unified systolic multiplication architecture, by employing Hankel matrix-vector multiplication, for various basis representations. For various element representation in GF（2^m）, we will show that various basis multiplications can be performed by Hankel matrix-vector multiplications. A comparison with existing and similar structures has shown that time complexities. the proposed architectures perform well both in space and展开更多
文摘针对二进制域上现有求逆算法计算量大、并行度小、速度慢的缺点进行改进,基于二元Euclidean算法提出了改进,设计了相应的乘法器硬件结构,并且分析了其运算效能和资源占用情况。将此求逆计算器的并行改进算法使用Verilog语言编程实现,利用Xilinx ISE 12.4对整个求逆算法综合仿真(行为级),在Xilinx Virtex-5 XC5VFX70T的硬件平台上验证求逆算法的运算效率,结果表明对求逆算法的改进有效地提高了求逆运算的速度。
文摘Recently, cryptographic applications based on finite fields have attracted much attention. The most demanding finite field arithmetic operation is multiplication. This investigation proposes a new multiplication algorithm over GF（2^m） using the dual basis representation. Based on the proposed algorithm, a parallel-in parallel-out systolic multiplier is presented, The architecture is optimized in order to minimize the silicon covered area （transistor count）. The experimental results reveal that the proposed bit-parallel multiplier saves about 65% space complexity and 33% time complexity as compared to the traditional multipliers for a general polynomial and dual basis of GF（2^m）.
文摘In general, there are three popular basis representations, standard （canonical, polynomial） basis, normal basis, and dual basis, for representing elements in GF（2^m）. Various basis representations have their distinct advantages and have their different associated multiplication architectures. In this paper, we will present a unified systolic multiplication architecture, by employing Hankel matrix-vector multiplication, for various basis representations. For various element representation in GF（2^m）, we will show that various basis multiplications can be performed by Hankel matrix-vector multiplications. A comparison with existing and similar structures has shown that time complexities. the proposed architectures perform well both in space and
