Parallel Processing and Applied Mathematics 15th International Conference, PPAM 2024, Ostrava, Czech Republic, September 8–11, 2024, Revised Selected Papers, Part II
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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.
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;
.- 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.