Euclids algorithm is widely used in calculating of GCD (Greatest Common Divisor) of two positive numbers. There are various fields where this division is used such as channel coding, cryptography, and error correction codes. This makes the GCD a fundamental algorithm in number theory, so a number of methods have been discovered to efficiently compute it. The main contribution of this paper is to investigate a method that computes the GCD of two 32-bit numbers based on Euclidean algorithm which targets six different Xilinx chips. The complexity of this method that we call Optimized_GCDSAD is achieved by utilizing Sum of Absolute Difference (SAD) block which is based on a fast carry-out generation function. The efficiency of the proposed architecture is evaluated based on criteria such as time (latency), area delay product (ADP) and space (slice number) complexity. The VHDL codes of these architectures have been implemented and synthesized through ISE 14.7. A detailed comparative analysis indicates that the proposed Optimized_GCDSAD method based on SAD block outperforms previously known results.
翻译:Euclids 算法被广泛用于计算两个正数的 GCD (最大常见divisor) 。 使用这个分区的有多个领域, 例如频道编码、 加密和错误校正代码。 这使GCD 成为数字理论中的一个基本算法, 因此发现了一些方法来有效地计算它。 本文的主要贡献是调查一种方法,根据Euclidean 算法计算出以六种不同的 Xilinx 芯片为对象的 GCDSAD 两个32 位数的计算法。 我们称之为Optimicized_GCDSAD 的方法的复杂性是通过使用基于快速执行生成功能的绝对差异总和( SAD) 来达到的。 拟议的结构的效率是根据时间( 延缓性)、 地区延迟产值( ADP) 和 空间( 秒号) 复杂程度等标准来评估的。 这些建筑的VHDL 代码已经通过ISE 14. 7 详细比较分析表明, 以 SADDD 区块的预期的Opimizmized_ GCDSADSADDDD 方法是以以前已知结果为基础的。