
Parallel Processing and Applied Mathematics
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This book constitutes the refereed proceedings of the 15th International Conference on Parallel Processing and Applied Mathematics, PPAM 2024, held in Ostrava, Czech Republic, during September 8-11, 2024.
The 75 full papers included in this book were carefully reviewed and selected from 134 submissions. . The papers are organized in the following topical sections:
Part I : Numerical Algorithms and Parallel Scientific Computing; Architectural Aspects of HPC; Parallel Non-numerical Algorithms; GPU Computing; Performance Analysis and Prediction in HPC
Systems; Environments and Frameworks for Parallel/Cloud/Edge Computing; and Applications of Parallel and Distributed Computing.
Part II : First PPAM Workshop on RISC-V (RISC-V PPAM 2024); Special Session on Scheduling for Parallel Computing; 10th Workshop on Language-Based Parallel Programming (WLPP 2024); 7th Workshop on Models Algorithms and Methodologies for Hybrid Parallelism in New HPC Systems (MAMHYP 2024); and Second Workshop on Quantum Computing and Communication.
Part III : First Workshop on Advancements of Global Challenges Application; Second Workshop on Applications of Machine Learning and Artificial Intelligence in High Performance Computing; 5th Workshop on Applied High Performance Numerical Algorithms for PDEs; Special Session on Parallel EVD/SVD and its Application in Matrix Computations; 6th Minisymposium on HPC Applications in Physical
Sciences; and 8th Workshop on Complex Collective Systems.
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Content
.- First Workshop on Advancements of Global Challenges Applications.
.- Simulation of wildfires using EuroHPC resources: challenges and opportunities.
.- Ktirio Urban Building: A Computational Framework for City Energy Simulations Enhanced by CI/CD Innovations on EuroHPC Systems.
.- Fostering uncertainty quantification in Global Challenges with mUQSA toolkit.
.- Portability of Multiphysics Applications on Heterogeneous Modular Supercomputers.
.- Efficient allocation of image recognition and LLM tasks on multi-GPU system.
.- Parallel reinforcement learning and Gaussian process regression for improved physics-based nasal surgery planning.
.- Second Workshop on Applications of Machine Learning and Artificial Intelligence in High Performance Computing.
.- AI-Driven Acceleration of Computational Fluid Dynamic Simulations.
.- A Framework and Methodology for Performance Prediction of HPC Workloads.
.- EM algorithm for cluster of multicore nodes using Level 3 BLAS operations to learn Gaussian mixture models.
.- MLP-based Adaptive Sampling and Optimization of Laser-Ion Acceleration with Ultra-Short Laser Pulses.
.- Minimization of Nonlinear Energies in Python Using FEM and Automatic Differentiation Tools.
.- Comparison of multigrid and machine learning-based Poisson solvers.
.- Adaptive Parallel Average Schwarz Preconditioner for reduced Hsieh-Clouh-Tocher Macro Element.
.- Special Session on Parallel EVD/SVD and its Application in Matrix Computations.
.- Preconditioning of the One-Sided Block-Jacobi SVD Algorithm by Polar Decomposition.
.- Comparison of Two QUBO Formulations of Approximate Block Diagonalization and Their Performance on the D-Wave Advantage Quantum Annealing Machine.
.- 6th Minisymposium on HPC Applications in Physical Sciences.
.- Efficient Algorithm for U(N) to U(3) Representation Reduction in Isospin-Adapted Nuclear Structure Calculations.
.- Study of the magnetic behaviour of oleic-acid coated Co ferrite nanoparticles: A multiscale modeling approach using high-performance computing.
.- 8th Workshop on Complex Collective Systems.
.- High-Resolution Agent-Based Modeling of Campus Population Behaviors for Pandemic Response Planning.
.- A comparison of selected agent-based modelling frameworks.
.- Modelling of opinion formation process on different social networks.
.- Machine learning approach for detecting potential anomalous cosmic rays particles tracks in Earth-scale Cosmic Ray Extremely Distributed Observatory.
.- A multi-cell cellular automata model for roundabout traffic flow considering the heterogeneity of human delay and acceleration.
.- Kernel estimates of pedestrian density applied in simulation of recreational pedestrian movement.
.- Personal Space of People in Movement under Different Conditions.
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