共查询到20条相似文献,搜索用时 203 毫秒
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将串行动态二表算法应用于并行三表算法的设计中,提出一种求解背包、精确的可满足性和集覆盖等背包类NP完全问题的并行三表六子表算法.基于EREW-PRAM模型,该算法可使用O(2n/8)的处理机在O(27n/16)的时间和O(213n/48)的空间求解n维背包类问题,其时间-空间-处理机折衷为O(25n/6).与现有文献的性能对比分析表明,该算法极大地提高了并行求解背包类问题的时间-空间-处理机折衷性能.由于该算法能够破解更高维数的背包类公钥和数字水印系统,其结论在密钥分析领域具有一定的理论和实际意义. 相似文献
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模糊聚类计算的最佳算法 总被引:14,自引:0,他引:14
给出模糊关系传递闭包在对应模糊图上的几何意义,并提出一个基于图连通分支计算的模糊聚类最佳算法.对任给的n个样本,新算法最坏情况下的时间复杂性函数T(n)满足O(n)≤T(n)≤O(n2).与经典的基于模糊传递闭包计算的模糊聚类算法的O(n3logn)计算时间相比,新算法至少降低了O(n相似文献
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RNA二级结构预测中动态规划的优化和有效并行 总被引:6,自引:0,他引:6
基于最小自由能模型的方法是计算生物学中RNA二级结构预测的主要方法,而计算最小自由能的动态规划算法需要O(n4)的时间,其中n是RNA序列的长度.目前有两种降低时间复杂度的策略:限制二级结构中内部环的大小不超过k,得到O(n2×k2)算法;Lyngso方法根据环的能量规则,不限制环的大小,在O(n3)的时间内获得近似最优解.通过使用额外的O(n)的空间,计算内部环中的冗余计算大为减少,从而在同样不限制环大小的情况下,在O(n3)的时间内能够获得最优解.然而,优化后的算法仍然非常耗时,通过有效的负载平衡方法,在机群系统上实现并行程序.实验结果表明,并行程序获得了很好的加速比. 相似文献
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分别在两种重要并行计算模型中给出计算有向基因组排列的反转距离新的并行算法.基于Hannenhalli和Pevzner理论,分3个主要部分设计并行算法:构建断点图、计算断点图中圈数、计算断点图中障碍的数目.在CREW-PRAM模型上,算法使用O(n2)处理器,时间复杂度为O(log2n);在基于流水光总线的可重构线性阵列系统(linear array with a reconfigurable pipelined bus system, LARPBS)模型上,算法使用O(n3)处理器,计算时间复杂度为O(logn). 相似文献
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本文在一个EREW PRAM(exclusive read exclusive write paralled random accessmachine)上提出一个并行快速排序算法,这个算法用k个处理器可将n个项目在平均O((n/k+logn)logn)时间内排序.所以平均来说算法的时间和处理器数量的乘积对任何k≤n/logn是
O(nlogn). 相似文献
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背包问题无存储冲突的并行三表算法 总被引:4,自引:0,他引:4
背包问题属于经典的NP难问题,在信息密码学和数论等研究中具有极重要的应用,将求解背包问题著名的二表算法的设计思想应用于三表搜索中,利用分治策略和无存储冲突的最优归并算法,提出一种基于EREW-SIMD共享存储模型的并行三表算法,算法使用O(2^n/4)个处理机单元和O(2^3n/8)的共享存储空间,在O(2^3n/8)时间内求解n维背包问题.将提出的算法与已有文献结论进行的对比分析表明:文中算法明显改进了现有文献的研究结果,是一种可在小于O(2^n/2)的硬件资源上,以小于O(2n/2)的计算时问求解背包问题的无存储冲突并行算法。 相似文献
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将串行动态二表算法应用于并行三表算法的设计中,提出一种求解背包、精确的可满足性和集覆盖等背包类NP完全问题的并行三表六子表算法.基于EREW-PRAM模型,该算法可使用O(2n/8)的处理机在O(27n/16)的时间和O(213n/48)的空间求解n维背包类问题,其时间-空间-处理机折衷为O(25n/6).与现有文献的性能对比分析表明,该算法极大地提高了并行求解背包类问题的时间-空间-处理机折衷性能.由于该算法能够破解更高维数的背包类公钥和数字水印系统,其结论在密钥分析领域具有一定的理论和实际意义. 相似文献
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Optimal Parallel Algorithm for the Knapsack Problem Without Memory Conflicts 总被引:11,自引:0,他引:11 下载免费PDF全文
Ken-LiLi Ren-FaLi Qing-HuaLi 《计算机科学技术学报》2004,19(6):0-0
Abstract The knapsack problem is well known to be NP-complete. Due to its importance in cryptosystem and in number theory, in the past two decades, much effort has been made in order to find techniques that could lead to practical algorithms with reasonable running time. This paper proposes a new parallel algorithm for the knapsack problem where the optimal merging algorithm is adopted. The proposed algorithm is based on an EREW-SIMD machine with shared memory. It is proved that the proposed algorithm is both optimal and the first without memory conflicts algorithm for the knapsack problem. The comparisons of algorithm performance show that it is an improvement over the past researches. 相似文献
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A parallel two-list algorithm for the knapsack problem 总被引:10,自引:0,他引:10
An n-element knapsack problem has 2n possible solutions to search over, so a task which can be accomplished in 2″ trials if an exhaustive search is used. Due to the exponential time in solving the knapsack problem, the problem is considered to be very hard. In the past decade, much effort has been done in order to find techniques which could lead to practical algorithms with reasonable running time. In 1994, Chang et al. proposed a brilliant parallel algorithm, which needs O(2n/8) processors to solve the knapsack problem in O(2n/2) time; that is, the cost of Chang et al.'s parallel algorithm is O(25n/8). In this paper, we propose a parallel algorithm to improve Chang et al.'s parallel algorithm by reducing the time complexity to be O(23n/8) under the same O(2n/8) processors available. Thus, the proposed parallel algorithm has a cost of O(2n/2). It is an improvement over previous literature. We believe that the proposed parallel algorithm is pragmatically feasible at the moment when multiprocessor systems become more and more popular. 相似文献
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The knapsack problem is well known to be NP-complete. Due to its importance in cryptosystem and in number theory, in the past
two decades, much effort has been made in order to find techniques that could lead to practical algorithms with reasonable
running time. This paper proposes a new parallel algorithm for the knapsack problem where the optimal merging algorithm is
adopted. The proposed algorithm is based on anEREW-SIMD machine with shared memory. It is proved that the proposed algorithm is both optimal and the first without memory conflicts
algorithm for the knapsack problem. The comparisons of algorithm performance show that it is an improvement over the past
researches. 相似文献
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Weifa Liang Brent R.P. Hong Shen 《Parallel and Distributed Systems, IEEE Transactions on》2001,12(8):846-864
Given a graph G=(V, E) with n vertices and m edges, the k-connectivity of G denotes either the k-edge connectivity or the k-vertex connectivity of G. In this paper, we deal with the fully dynamic maintenance of k-connectivity of G in the parallel setting for k=2, 3. We study the problem of maintaining k-edge/vertex connected components of a graph undergoing repeatedly dynamic updates, such as edge insertions and deletions, and answering the query of whether two vertices are included in the same k-edge/vertex connected component. Our major results are the following: (1) An NC algorithm for the 2-edge connectivity problem is proposed, which runs in O(log n log(m/n)) time using O(n3/4) processors per update and query. (2) It is shown that the biconnectivity problem can be solved in O(log2 n ) time using O(nα(2n, n)/logn) processors per update and O(1) time with a single processor per query or in O(log n logn/m) time using O(nα(2n, n)/log n) processors per update and O(logn) time using O(nα(2n, n)/logn) processors per query, where α(.,.) is the inverse of Ackermann's function. (3) An NC algorithm for the triconnectivity problem is also derived, which takes O(log n logn/m+logn log log n/α(3n, n)) time using O(nα(3n, n)/log n) processors per update and O(1) time with a single processor per query. (4) An NC algorithm for the 3-edge connectivity problem is obtained, which has the same time and processor complexities as the algorithm for the triconnectivity problem. To the best of our knowledge, the proposed algorithms are the first NC algorithms for the problems using O(n) processors in contrast to Ω(m) processors for solving them from scratch. In particular, the proposed NC algorithm for the 2-edge connectivity problem uses only O(n3/4) processors. All the proposed algorithms run on a CRCW PRAM 相似文献
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背包问题属于NP完全问题,经典算法对规模为n的背包问题求解的时间复杂度为O(n2)。给出了基于固定相位的背包问题量子计算算法,证明了该算法在多解的情况下,能够以不低于98%的成功率在O(√N/M)步完成对规模为n的背包问题求解(M是解的数目),而基于原始Grover算法的背包问题量子计算算法计算复杂度为O(√N/M),成功率是50%~100%。 相似文献
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已知一个无向图G(V,E),|V|=n,|E|=m,本文基于SIMD共享存贮模型,运用数据在图中快速传播原理,建议了一个新的求图的连通分支算法,具体来讲,在SIMD—CREW共享存贮模型上,求图的连通分支需O(log2n)时间、O(n2/logn)处理器;而在SIMD—CRCW共享存贮模型上需O(logn)时间、O(n2)处理器,建议的算法同著名的Hirschberg算法相比,其主要差别表现在:1)采用的求解方法不同;2)建议的算法简单易懂 相似文献
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用动态规划算法求解0-1背包问题的时空复杂度为O(nC)。这个空间复杂度在求解大规模问题上是不可接受的。从计算0-1背包问题最优值的递归方程出发,给出高效利用内存的动态规划算法。为了克服内存高效的动态规划算法带来的缺点,设计新混合算法求解0-1背包问题。该新混合算法的时间复杂度为O(nC);它消除了回溯阶段,并且为求得放入背包的物品所使用的空间复杂度仅为O(「n/d?+C),其中d为计算机字长。实验结果表明,混合算法的工作效率与理论分析相同。 相似文献