UID:
almahu_9950000761902882
Format:
XIX, 374 p. 96 illus., 80 illus. in color.
,
online resource.
Edition:
1st ed. 2025.
ISBN:
9783031857003
Series Statement:
Lecture Notes in Computer Science, 15580
Content:
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.
Note:
-- 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.
In:
Springer Nature eBook
Additional Edition:
Printed edition: ISBN 9783031856990
Additional Edition:
Printed edition: ISBN 9783031857010
Language:
English
DOI:
10.1007/978-3-031-85700-3
URL:
https://doi.org/10.1007/978-3-031-85700-3
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