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VECPAR is a series of international conferences dedicated to the promotion and advancement of all aspects of high-performance computing for computational science, as an industrial technique and academic discipline, extending the fr- tier of both the state of the art and the state of practice. The audience for and participants in VECPAR are seen as researchers in academic departments, g- ernment laboratories and industrial organizations. There is now a permanent website for the series, http://vecpar.fe.up.pt, where the history of the conf- ences is described. ThesixtheditionofVECPARwasthe?rsttimetheconferencewascelebrated outside Porto – at the Universitad Politecnica de Valencia (Spain), June 28–30, 2004. The whole conference programme consisted of 6 invited talks, 61 papers and26posters,outof130contributionsthatwereinitiallysubmitted.Themajor themes were divided into large-scale numerical and non-numerical simulations, parallel and grid computing, biosciences, numerical algorithms, data mining and visualization. This postconference book includes the best 48 papers and 5 invited talks presented during the three days of the conference. The book is organized into 6 chapters, with a prominent position reserved for the invited talks and the Best Student Paper. As a whole it appeals to a wide research community, from those involved in the engineering applications to those interested in the actual details of the hardware or software implementations, in line with what, in these days, tends to be considered as computational science and engineering (CSE).




This book constitutes the thoroughly refereed post-proceedings of the 6th International Conference on High Performance Computing for Computational Science, VECPAR 2004, held in Valencia, Spain, in June 2004.

The 48 revised full papers presented together with 5 invited papers were carefully selected during two rounds of reviewing and improvement from initially 130 contributions. The papers are organized in topical sections on large-scale computations, data management and data mining, GRID computing infrastructure, cluster computing, parallel and distributed computing, and computational linear and non-linear algebra.

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