首页> 外文会议>Proceedings of the 1990 ACM annual conference on Cooperation >Parallel unit tangent vector computation for homotopy curve tracking on a hypercube
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Parallel unit tangent vector computation for homotopy curve tracking on a hypercube

机译:超立方体上同伦曲线跟踪的并行单位切向量计算

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Probability-one homotopy methods are a class of methods for solving nonlinear systems of equations that are globally convergent from an arbitrary starting point. The essence of all such algorithms is the construction of an appropriate homotopy map and subsequent tracking of some smooth curve in the zero set of the homotopy map. Tracking a homotopy curve involves finding the unit tangent vectors at different points along the zero curve. Because of the way a homotopy map is constructed, the unit tangent vector at each point in the zero curve of a homotopy map &rgr;a(λ,&khgr;) is in the kernel of the Jacobian matrix D&rgr;a(λ,&khgr;). Hence, tracking the zero curve of a homotopy map involves finding the kernel of the Jacobian matrix D&rgr;a(λ,&khgr;). The Jacobian matrix D&rgr;a is a n × (n+1) matrix with full rank. Since the accuracy of the unit tangent vector is very important, an orthogonal factorization instead of an LU factorization of the Jacobian matrix is computed. Two related orthogonal factorizations, namely QR and LQ factorization, are considered here. This paper presents computational results showing the performance of several different parallel orthogonal factorization/triangular system solving algorithms on a hypercube. Since the purpose of this study is to find ways to parallelize homotopy algorithms, it is assumed that the matrices have a special structure such as that of the Jacobian matrix of a homotopy map. In particular, we are interested in relatively small and dense Jacobians.

机译:概率一同伦方法是一类用于求解从任意起点全局收敛的非线性方程组的方法。所有这些算法的本质是构造适当的同构图,并随后在同构图的零集中跟踪某些平滑曲线。跟踪同伦曲线涉及在沿零曲线的不同点处找到单位切向量。由于构造同构图的方式,同构图&rgr; a (λ,&khgr;)的零曲线上每个点的单位正切向量位于Jacobian矩阵的核< ITALIC> D &rgr; a (λ,&khgr;)。因此,跟踪同伦图的零曲线涉及找到雅可比矩阵 D &rgr; a (λ,&khgr;)的核。雅可比矩阵 D &rgr; a 是具有完整等级的 n ×( n +1)矩阵。由于单位正切向量的精度非常重要,因此计算了Jacobian矩阵的正交分解而不是 LU 分解。这里考虑两个相关的正交分解,即 QR LQ 分解。本文提出的计算结果显示了超立方体上几种不同的并行正交正交分解/三角系统求解算法的性能。由于本研究的目的是找到并行化同伦算法的方法,因此假定矩阵具有特殊结构,例如同伦图的Jacobian矩阵。特别是,我们对相对较小和密集的Jacobian感兴趣。

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