José M. Badía

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This paper presents a general framework for agglomerative hierarchical clustering based on graphs. Different hierarchical agglomerative clustering algorithms can be obtained from this framework, by specifying an inter-cluster similarity measure, a subgraph of the 13-similarity graph, and a cover routine. We also describe two methods obtained from this(More)
llc is a language designed to extend OpenMP to distributed memory systems. Work in progress on the implementation of a compiler that translates llc code and targets distributed memory platforms is presented. Our approach generates code for communications directly on top of MPI. We present computational results for two different benchmark applications on a(More)
In this paper, we design and implement an efficient algorithm that uses the cyclic odd-even reduction method to solve large tridiagonal systems on a Distributed Memory Multiprocessor. The algorithm works on a bidirectional array of transputers, and the code has beeii written in Occam2. The algorithm perfornzs a parallel cyclic reduction of the original(More)
This paper describes the parallelization of the low-rank ADI iteration for the solution of large-scale, sparse Lyapunov equations. The only relevant operations involved in the method are matrix-vector products and the solution of linear systems. Experimental results on a cluster, using the SuperLU library, show the performance of this approach.
In this paper, a new access method for very high-dimensional data space is proposed. The method uses a graph structure and pivots for indexing objects, such as documents in text mining. It also applies a simple search algorithm that uses distance or similarity based functions in order to obtain the k-nearest neighbors for novel query objects. This method(More)
In this paper we present two parallel algorithms to solve non-symmetric Toeplitz systems of linear equations. The first algorithm performs a modified QR factorization of the matrix by using the generalized Schur algorithm. The second one is based on the transformation of the Toeplitz matrix into a Cauchy-like matrix in order to reduce the communication(More)
In this paper, we present an efficient parallel algorithm to solve Toeplitz–block and block–Toeplitz systems in distributed memory multicomputers. This algorithm parallelizes the Generalized Schur Algorithm to obtain the semi-normal equations. Our parallel implementation reduces the communication cost and optimizes the memory access. The experimental(More)