论文标题
用于构建Hadamard矩阵的GPU加速遗传算法
A GPU accelerated Genetic Algorithm for the Construction of Hadamard Matrices
论文作者
论文摘要
我们使用遗传算法来构建Hadamard矩阵。生成随机矩阵的初始群体在每个列中具有平衡的+1和-1条目，除了所有+1的第一列。为了找到最有效的功能，实施了几种健身功能。交叉过程通过交换父矩阵种群的列来创建后代矩阵种群。突变过程在随机列中翻转+1和-1输入对。 Python在图形处理单元中使用Cupy库使我们能够并行处理数千个矩阵和矩阵操作的人群。
We use a genetic algorithm to construct Hadamard Matrices. The initial population of random matrices is generated to have a balanced number of +1 and -1 entries in each column except the first column with all +1. Several fitness functions are implemented in order to find the most effective one. The crossover process creates offspring matrix population by exchanging columns of the parent matrix population. The mutation process flips +1 and -1 entry pairs in random columns. The use of CuPy library in Python on graphics processing units enables us to handle populations of thousands of matrices and matrix operations in parallel.
