PHIDAL (Parallel Hierarchical Interface Decomposition ALgorithm) is a parallel incomplete factorization method which exploits a hierarchical interface decomposition of the adjacency graph of the coefficient matrix. The idea of the decomposition is similar to that of the well-known wirebasket techniques used in domain decomposition. However, the method is devised for general, irregularly structu...

We propose Dijkstra’s algorithm with bounded list size after QR decomposition for decreasing the computational complexity of near maximumlikelihood (ML) detection of signals over multipleinput-multiple-output (MIMO) channels. After that, we compare the performances of proposed algorithm, QR decomposition M-algorithm (QRD-MLD), and its improvement. When the list size is set to achieve the almost...

In this paper we present a new stable algorithm for the parallel QR-decomposition of ”tall and skinny” matrices. The algorithm has been developed for the dense symmetric eigensolver ELPA, whereat the QR-decomposition of tall and skinny matrices represents an important substep. Our new approach is based on the fast but unstable CholeskyQR algorithm [1]. We show the stability of our new algorithm...

We introduce a truss decomposition algorithm for bipartite graphs. A subgraph G of a graph is called k-truss if there are at least k-2 triangles containing any edge e of G. By a standard breadth-first-search algorithm, we can compute the truss decomposition for large graphs. To extract a dense substructure that represents community in graph G, this method avoids the intractable problem of cliqu...

Motivated by the problem of robust factorization of a low-rank tensor, we study the question of sparse and low-rank tensor decomposition. We present an efficient computational algorithm that modifies Leurgans’ algoirthm for tensor factorization. Our method relies on a reduction of the problem to sparse and low-rank matrix decomposition via the notion of tensor contraction. We use well-understoo...

We propose a Uzawa block relaxation domain decomposition method for a two-body contact problem with Tresca friction. We introduce auxiliary interface unknowns to transform the variational problem into a saddle-point problem. Applying a Uzawa block relaxation algorithm to the corresponding augmented Lagrangian functional we obtain a domain decomposition algorithm in which we have to solve two un...

In this paper we focus on image segmentation by proposing a new algorithm based on Haar wavelet decomposition and Kmeans algorithm. When Haar wavelet decomposition is applied to an image it gives an idea about high frequency components. If higher levels of decomposition are performed, different texture region information can be captured. The paper deals with the texture segmentation of an image...

Benders' decomposition is a well-known technique for solving large linear programs with a special structure. In particular it is a popular technique for solving multi-stage stochastic linear programming problems. Early termination in the subproblems generated during Benders' decomposition (assuming dual feasibility) produces valid cuts which are inexact in the sense that they are not as constra...

A new approach to develop parallel and distributed scheduling algorithms for multiprocessor systems is proposed. Its main innovation lies in evolving a decomposition of the global optimization criteria. For this purpose a program graph is interpreted as a multi-agent system. A game-theoretic model of interaction between agents is applied. Competetive coevolutionary genetic algorithm, termed loo...

In this paper we present an efficient decomposition technique to speed up evolutionary algorithms when dealing with large scale optimization problems. Divide and conquer methods aim to solving problems in smaller entities and then combining the sub-solutions to form complete solutions. Often the optimal way to divide the problem varies as the evolutionary algorithm proceeds, thus making a stati...