High Performance Computing for Computational Science - VECPAR 2008

1. Front Matter

   PDF

2. Parallel and Distributed Computing

   1. An Overview of High Performance Computing and Challenges for the Future

      • Jack Dongarra

      Pages 1-1

   2. Parallelization of Sphere-Decoding Methods

      • Rafael A. Trujillo, Antonio M. Vidal, Víctor M. García, Alberto González

      Pages 2-12

   3. Improving the Performance of a Verified Linear System Solver Using Optimized Libraries and Parallel Computation

      • Mariana Kolberg, Gerd Bohlender, Dalcidio Claudio

      Pages 13-26

   4. Parallelisation of the CFD Code of a CFD-NWP Coupled System for the Simulation of Atmospheric Flows over Complex Terrain

      • Fernando A. Castro, Castro M. P. Silva Santos, José M. L. M. Palma

      Pages 27-38

   5. High Performance Computing for Eigenvalue Solver in Density-Matrix Renormalization Group Method: Parallelization of the Hamiltonian Matrix-Vector Multiplication

      • Susumu Yamada, Masahiko Okumura, Masahiko Machida

      Pages 39-45

   6. Tunable Parallel Experiments in a GridRPC Framework: Application to Linear Solvers

      • Yves Caniou, Jean-Sébastien Gay, Pierre Ramet

      Pages 46-52

3. Cluster and Grid Computing

   1. The Rise of the Commodity Vectors

      • Satoshi Matsuoka

      Pages 53-62

   2. MOPS – A Morphodynamical Prediction System on Cluster Computers

      • Hartmut Kapitza

      Pages 63-68

   3. Implementing a Parallel NetCDF Interface for Seamless Remote I/O Using Multi-dimensional Data

      • Yuichi Tsujita

      Pages 69-82

   4. Vectorized AES Core for High-throughput Secure Environments

      • Miquel Pericàs, Ricardo Chaves, Georgi N. Gaydadjiev, Stamatis Vassiliadis, Mateo Valero

      Pages 83-94

   5. A Matrix Inversion Method with YML/OmniRPC on a Large Scale Platform

      • Maxime Hugues, Serge G. Petiton

      Pages 95-108

   6. Can We Connect Existing Production Grids into a World Wide Grid?

      • Peter Kacsuk, Attila Kertesz, Tamas Kiss

      Pages 109-122

   7. A List Scheduling Algorithm for Scheduling Multi-user Jobs on Clusters

      • Jorge Barbosa, António P. Monteiro

      Pages 123-136

   8. Data Locality Aware Strategy for Two-Phase Collective I/O

      • Rosa Filgueira, David E. Singh, Juan C. Pichel, Florin Isaila, Jesús Carretero

      Pages 137-149

4. Problem Solving Environment and Data Centric

   1. A Grid-Aware Web Portal with Advanced Service Trading for Linear Algebra Calculations

      • Hrachya Astsatryan, Vladimir Sahakyan, Yuri Shoukouryan, Michel Daydé, Aurelie Hurault, Marc Pantel et al.

      Pages 150-159

   2. Resource Matching in Non-dedicated Multicluster Environments

      • Josep Lluis Lérida, Francesc Solsona, Francesc Giné, Jose Ramon García, Porfidio Hernández

      Pages 160-173

   3. A Parallel Incremental Learning Algorithm for Neural Networks with Fault Tolerance

      • Jacques M. Bahi, Sylvain Contassot-Vivier, Marc Sauget, Aurélien Vasseur

      Pages 174-187

   4. High-Performance Query Processing of a Real-World OLAP Database with ParGRES

      • Melissa Paes, Alexandre A. B. Lima, Patrick Valduriez, Marta Mattoso

      Pages 188-200

   5. Improving Search Engines Performance on Multithreading Processors

      • Carolina Bonacic, Carlos Garcia, Mauricio Marin, Manuel Prieto, Francisco Tirado, Cesar Vicente

      Pages 201-213

This book constitutes the thoroughly refereed post-conference proceedings of the 8th International Conference on High Performance Computing for Computational Science, VECPAR 2008, held in Toulouse, France, in June 2008. The 51 revised full papers presented together with the abstract of a surveying and look-ahead talk were carefully reviewed and selected from 73 submissions. The papers are organized in topical sections on parallel and distributed computing, cluster and grid computing, problem solving environment and data centric, numerical methods, linear algebra, computing in geosciences and biosciences, imaging and graphics, computing for aerospace and engineering, and high-performance data management in grid environments.

• AES
• Partition
• Routing
• Simulation
• approximation
• asteroids
• calculus
• cluster computing
• cooperative engineering
• data management
• databases
• design
• encryption
• linear algebra
• load balancing

• Faculdade de Engenharia da Universidade do Porto, Porto, Portugal

  José M. Laginha M. Palma

• University of Toulouse, INP (ENSEEIHT), IRIT, Toulouse CEDEX 7, France

  Patrick R. Amestoy

• University of Toulouse, INP (ENSEEIHT); IRIT, Toulouse CEDEX 7, France

  Michel Daydé

• Federal University of Rio de Janeiro, Rio de Janeiro, Brazil

  Marta Mattoso

• Faculty of Engineering, University of Porto, Porto, Portugal

  João Correia Lopes

Policies and ethics