The distribution of Seidel eigenvalues of cographs is investigated in this paper.We prove that there is no Seidel eigenvalue of nontrivial cographs in the interval(−1,1).We also show the optimality of the interval(−1,...The distribution of Seidel eigenvalues of cographs is investigated in this paper.We prove that there is no Seidel eigenvalue of nontrivial cographs in the interval(−1,1).We also show the optimality of the interval(−1,1)in the sense that for any ε>0 either of the intervals(1,1+ε)and(−1−ε,−1)contains a Seidel eigenvalue of some cograph of order n when n is sufficiently large.展开更多
针对基于PVM的微机网络并行计算环境下，处理机的运算速度较快而处理机间的通信相对较慢的实际情况，给出了一种网上并行求解线性方程组的Guass—Seidel迭代算法。该算法将方程组的增广矩阵按行卷帘方式分布存储在各处理机中，循环传送...针对基于PVM的微机网络并行计算环境下，处理机的运算速度较快而处理机间的通信相对较慢的实际情况，给出了一种网上并行求解线性方程组的Guass—Seidel迭代算法。该算法将方程组的增广矩阵按行卷帘方式分布存储在各处理机中，循环传送每一次的迭代向量以减少处理间的通信次数，同时，采用计算与通信部分重叠技术，提高并行算法的效率。并用1—12台桌面PC机联成的局域网，在PVM3．4 on Windowsi2000，VC6．0并行计算平台上编程对该算法进行了数值试验，试验结果表明，该算法较传统的基于列扫描法的Guass—Seidel并行迭代算法优越。展开更多
基金Supported by the National Natural Science Foundation of China(Grant No.12001006)the Natural Science Foundation of Universities of Anhui Province(Grant No.2023AH050904).
文摘The distribution of Seidel eigenvalues of cographs is investigated in this paper.We prove that there is no Seidel eigenvalue of nontrivial cographs in the interval(−1,1).We also show the optimality of the interval(−1,1)in the sense that for any ε>0 either of the intervals(1,1+ε)and(−1−ε,−1)contains a Seidel eigenvalue of some cograph of order n when n is sufficiently large.
基金Supported by the National Natural Science Foundation of China under Grant No.60373008(国家自然科学基金)the National High-Tech Research and Development Plan of China under Grant No.2006AA01Z105(国家高技术研究发展计划(863))the Key Project of the Ministry of Education of China under Grant No.106019(国家教育部科学技术研究重点项目)
文摘针对基于PVM的微机网络并行计算环境下，处理机的运算速度较快而处理机间的通信相对较慢的实际情况，给出了一种网上并行求解线性方程组的Guass—Seidel迭代算法。该算法将方程组的增广矩阵按行卷帘方式分布存储在各处理机中，循环传送每一次的迭代向量以减少处理间的通信次数，同时，采用计算与通信部分重叠技术，提高并行算法的效率。并用1—12台桌面PC机联成的局域网，在PVM3．4 on Windowsi2000，VC6．0并行计算平台上编程对该算法进行了数值试验，试验结果表明，该算法较传统的基于列扫描法的Guass—Seidel并行迭代算法优越。
