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Parallel Processing and Applied Mathematics: 12th International Conference, PPAM 2017, Lublin, Poland, September 10-13, 2017, Revised Selected Papers, Part I de Roman Wyrzykowski

Parallel Processing and Applied Mathematics: 12th International Conference, PPAM 2017, Lublin, Poland, September 10-13, 2017, Revised Selected Papers, Part I: Lecture Notes in Computer Science, cartea 10777

Editat de Roman Wyrzykowski, Jack Dongarra, Ewa Deelman, Konrad Karczewski
en Limba Engleză Paperback – 23 mar 2018
The two-volume set LNCS 10777 and 10778 constitutes revised selected papers from the 12th International Conference on Parallel Processing and Applied Mathematics, PPAM 2017, held in Lublin, Poland, in September 2017.
The 49 regular papers presented in this volume were selected from 98 submissions. For the workshops and special sessions, that were held as integral parts of the PPAM 2017 conference, a total of 51 papers was accepted from 75 submissions.
The papers were organized in topical sections named as follows:
Part I: numerical algorithms and parallel scientific computing; particle methods in simulations; task-based paradigm of parallel computing; GPU computing; parallel non-numerical algorithms; performance evaluation of parallel algorithms and applications; environments and frameworks for parallel/distributed/cloud computing; applications of parallel computing; soft computing with applications; and special session on parallel matrix factorizations.
Part II: workshop on models, algorithms and methodologies for hybrid parallelism in new HPC systems; workshop power and energy aspects of computations (PEAC 2017); workshop on scheduling for parallel computing (SPC 2017); workshop on language-based parallel programming models (WLPP 2017); workshop on PGAS programming; minisymposium on HPC applications in physical sciences; minisymposium on high performance computing interval methods; workshop on complex collective systems. 
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Specificații

ISBN-13: 9783319780238
ISBN-10: 3319780239
Pagini: 1100
Ilustrații: XXV, 660 p. 261 illus.
Dimensiuni: 155 x 235 mm
Greutate: 0.95 kg
Ediția:1st ed. 2018
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Theoretical Computer Science and General Issues

Locul publicării:Cham, Switzerland

Cuprins

Numerical Algorithms and Parallel Scientific Computing.- Advances in Incremental PCA Algorithms.- Algorithms for forward and backward solution of the Fokker-Planck equation in the heliospheric transport of cosmic rays.- Efficient Evaluation of Matrix Polynomials.- A Comparison of Soft-Fault Error Models in the Parallel Preconditioned Flexible GMRES.- Multilayer Approach for Joint Direct and Transposed Sparse Matrix Vector Multiplication for Multithreaded CPUs.- Comparison of parallel time-periodic Navier–Stokes solvers.- Blocked Algorithms for Robust Solution of Triangular Linear Systems.- A Comparison of Accuracy and Efficiency of Parallel Solvers for Fractional Power Diffusion Problems.- Efficient Cross Section Reconstruction on Modern Multi and Many Core Architectures.- Parallel assembly of ACA BEM matrices on Xeon Phi clusters.- Stochastic bounds for Markov chains on Intel Xeon Phi coprocessor.- Particle Methods in Simulations.- Fast DEM collision checks on multicorenodes.- A Space and Bandwidth Efficient Multicore Algorithm for the Particle-in-Cell Method.- Load Balancing for Particle-in-Cell Plasma Simulation on Multicore Systems.- Task-Based Paradigm of Parallel Computing.- TaskUniVerse: A Task-Based Unified Interface for Versatile Parallel Execution.- Comparison of Time and Energy Oriented Scheduling for Task-based Programs.- Experiments with sparse Cholesky using a parametrized task graph Implementation.- A Task-Based Algorithm for Reordering the Eigenvalues of a Matrix in Real Schur Form.- GPU Computing.- Radix Tree for Binary Sequences on GPU.-  A comparison of performance tuning process for different generations of NVIDIA GPUs and an example scientific computing algorithm.-  NVIDIA GPUs Scalability to Solve Multiple (Batch) Tridiagonal Systems Implementation of cuThomasBatch.- Two-Echelon System Stochastic Optimization with R and CUDA.- Parallel Hierarchical Agglomerative Clustering for fMRI Data.- Parallel Non-numerical Algorithms.- Two Parallelization Schemes for the Induction of Nondeterministic Finite Automata on PCs.- Approximating Personalized Katz Centrality in Dynamic Graphs.- Graph-Based Speculative Query Execution for RDBMS.- A GPU Implementation of Bulk Execution of the Dynamic Programming for the Optimal Polygon Triangulation.- Performance Evaluation of Parallel Algorithms and Applications.- Early performance evaluation of the hybrid cluster with torus interconnect aimed at molecular-dynamics simulations.- Load balancing for CPU-GPU coupling in Computational Fluid Dynamics.- Implementation and Performance Analysis of 2.5D-PDGEMM on the K Computer.- An Approach for Detecting Abnormal Parallel Applications Based on Time Series Analysis Methods.- Prediction of the Inter-Node Communication Costs of a New Gyrokinetic Code with Toroidal Domain.- D-Spline Performance Tuning Method Flexibly Responsive to Execution Time Perturbation.- Environments and Frameworks for Parallel/Distributed/Cloud Computing.- Dfuntest: A Testing Framework for Distributed Applications.- Security monitoring and analytics in the context of HPC processing model.- Multidimensional Performance and Scalability Analysis for Diverse Applications Based on System Monitoring Data.- Bridging the Gap between HPC and Cloud using HyperFlow and PaaSage.- A Memory Efficient Parallel All-Pairs Computation Framework: Computation – Communication Overlap.- Automatic Parallelization of ANSI C to CUDA C Programs.-Consistency Models for Global Scalable Data Access Services.- Applications of Parallel Computing.- Global state monitoring in optimization of parallel event–driven simulation.- High Performance Optimization of Independent Component Analysis Algorithm for EEG Data.- Continuous and discrete models of melanoma progression simulated in multi-GPU environment.- Early experience on using Knights Landing processors for Lattice Boltzmann applications.- Soft Computing with Applications.-Towards a Model of Semi-Supervised Learning for the Syntactic Pattern Recognition-based Electrical Load Prediction System.- Parallel Processing of Color Digital Images for Linguistic Description of Their Content.- Co-evolution of fitness predictors and Deep Neural Networks.- Performance evaluation of DBN learning on Intel multi- and manycore architectures.- Special Session on Parallel Matrix Factorizations.- On the Tunability of a New Hessenberg Reduction Algorithm Using Parallel Cache Assignment.- New Preconditioning for the One–Sided Block–Jacobi SVD Algorithm.- Structure-preserving technique in the block SS–Hankel method for solving Hermitian generalized eigenvalue problems.- On using the Cholesky QR method in the full-blocked one-sided Jacobi algorithm.- Parallel Divide-and-Conquer Algorithm for Solving Tridiagonal Eigenvalue Problems on Manycore Systems.- Partial Inverses of Complex Block Tridiagonal Matrices.- Parallel Nonnegative Matrix Factorization Based on Newton Iteration with Improved Convergence Behavior.

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and Applications of Parallel and Distributed Computing.Part II : First PPAM Workshop on RISC-V (RISC-V PPAM 2024); and Second Workshop on Quantum Computing and Communication. Part III : First Workshop on Advancements of Global Challenges Application;

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Chapters "Parallel Adaptive Cross Approximation for the Multi-trace Formulation of Scattering Problems" and "A High-Order Discontinuous Galerkin Solver with Dynamic Adaptive Mesh Refinement to Simulate Cloud Formation Processes" are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.