Description
High Performance Computing for Computational Science - VECPAR 2012, 2013
10th International Conference, Kope, Japan, July 17-20, 2012, Revised Selected Papers
Theoretical Computer Science and General Issues Series
Language: English468 p. · 15.5x23.5 cm · Paperback
Description
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Programming the LU Factorization for a Multicore System with Accelerators.- Efficient Two-Level Preconditioned Conjugate Gradient Method on the GPU.- Parallelization of the QR Decomposition with Column Pivoting Using Column Cyclic Distribution on Multicore and GPU Processors.- A High Performance SYMV Kernel on a Fermi-core GPU.- Optimizing Memory-Bound SYMV Kernel on GPU Hardware Accelerators.- Numerical Simulation of Long-Term Fate of CO2 Stored in Deep Reservoir Rocks on Massively Parallel Vector Supercomputer.- High Performance Simulation of Complicated Fluid Flow in 3D Fractured Porous Media with Permeable Material Matrix Using LBM.- Parallel Scalability Enhancements of Seismic Response and Evacuation Simulations of Integrated Earthquake Simulator.- QMC=Chem: A Quantum Monte Carlo Program for Large-Scale Simulations in Chemistry at the Petascale Level and beyond.- Optimizing Sparse Matrix Assembly in Finite Element Solvers with One-Sided Communication.- Implementation and Evaluation of 3D Finite Element Method Application for CUDA.- A Service-Oriented Architecture for Scientific Computing on Cloud Infrastructures.- Automatic Generation of the HPC Challenge’s Global FFT Benchmark for Blue Gene/P.- High Performance CPU Kernels for Multiphase Compressible Flows.- Efficient Algorithm for Linear Systems Arising in Solutions of Eigenproblems and Its Application to Electronic-Structure.- Control Formats for Unsymmetric and Symmetric Sparse Matrix–Vector Multiplications on Open MP Implementations.- Sparsification on Parallel Spectral Clustering.- A Multi GPU Read Alignment Algorithm with Model-Based Performance Optimization.- Parallel Smoother Based on Block Red-Black Ordering for Multigrid Poisson Solver.- Accelerating the Reorthogonalization of Singular Vectors with a Multi-core Processor.
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