Parallel Processing and Applied Mathematics : 15th International Conference, PPAM 2024, Ostrava, Czech Republic, September 8-11, 2024, Revised Selected Papers, Part II (Lecture Notes in Computer Science)

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Parallel Processing and Applied Mathematics : 15th International Conference, PPAM 2024, Ostrava, Czech Republic, September 8-11, 2024, Revised Selected Papers, Part II (Lecture Notes in Computer Science)

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  • 製本 Paperback:紙装版/ペーパーバック版/ページ数 374 p.
  • 言語 ENG
  • 商品コード 9783031856990
  • DDC分類 004.35

Full Description

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.

Contents

.- First PPAM Workshop on RISC-V (RISC-V PPAM 2024).
.- RAVE: RISC-V Analyzer of Vector Executions, a QEMU tracing plugin.
.- Batched DGEMMs for scientific codes running on long vector architectures.
.- Vectorization of Gradient Boosting of Decision Trees Prediction in the CatBoost Library for RISC-V Processors.
.- QR Factorization on a Long-Vector Processor.
.- Special Session on Scheduling for Parallel Computing.
.- HEAPS: a novel energy-based configurable HPC scheduler.
.- Fair-Sharing Simulator for Batch Computing Systems.
.- Scalability and Reliability of Port Simulation Workflow on Slurm.
.- 10th Workshop on Language-Based Parallel Programming (WLPP 2024).
.- On the Incorrect Use of Application Efficiency to Calculate Performance Portability.
.- Assessing the Performance of Portable Programming Models Across GPU Vendors for the N-Body Problem.
.- Performance Portability of SpMV for CSR and BSR Storage Formats Implemented Using OpenACC and SYCL.
.- The Impact of SYCL Data Management on Performance Portability.
.- LLM-driven Cross-Platform Code Generation for Polyhedral Optimized NPDP Codes.
.- Juliana: Automated Julia CUDA.jl Code Translation Across Multiple GPU Platforms.
.- 7th Workshop on Models Algorithms and Methodologies for Hybrid Parallelism in New HPC Systems (MAMHYP 2024)
.- Boosting GPGPU virtualization and multiplexing with RDMA communication.
.- Efficient Load Scheduling of IMRT Planning in Heterogeneous multicore clusters.
.- Deploying AI-Based Environmental Monitoring Applications at the Edge: Two Case Studies.
.- Parallelism in GNN: possibilities and limits of current approaches.
.- Solving Soil Microbiota Growth Problem by PINNs.
.- Two-Phase Distributed Algorithm for Solving the Bi-Objective Minimum Spanning Tree Problem: A Preliminary Study.
.- Second Workshop on Quantum Computing and Communication.
.- Feedback-Based Quantum Algorithm for Constrained Optimization Problems.
.- Halving the number of qubits of quantum comparators.
.- Private Computation of Boolean Functions Using Single Qubits.
.- The Fredholm determinants approach to the computations of quantum entanglement.
.- Power Consumption and Energy Efficiency of Quantum Computing Platforms in High Performance Computing Integration.
.- Feasibility Study of a Hybrid Quantum-Classical Setup for Multiple GPUs and Two Photonic Quantum Computers.
.- QCG-QuantumLauncher: a modular tool for quantum scenarios.
.- Semi-self-testing Quantum Random Number Generator with CMOS Sensors.

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