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13th international conference on parallel processing and applied mathematics, PPAM 2019

ISBN: (纸本)9783030432218

the proceedings contain 91 papers. the special focus in this conference is on parallel processing and applied mathematics. the topics include: Performance/Energy Aware Optimization of parallel Applications on GPUs Under Power Capping;improving Energy Consumption in Iterative Problems Using Machine Learning;automatic Software Tuning of parallel Programs for Energy-Aware Executions;overview of Application Instrumentation for Performance Analysis and Tuning;Energy-Efficiency Tuning of a Lattice Boltzmann Simulation Using MERIC;Evaluating the Advantage of Reactive MPI-aware Power Control Policies;application-Aware Power Capping Using Nornir;A New Hardware Counters Based thread Migration Strategy for NUMA Systems;alea – Complex Job Scheduling Simulator;studying the Performance of Vector-Based Quicksort Algorithm;makespan Minimization in Data Gathering Networks with Dataset Release Times;overlapping Schwarz Preconditioner for Fourth Order Multiscale Elliptic Problems;MATLAB Implementation of C1 Finite Elements: Bogner-Fox-Schmit Rectangle;simple Preconditioner for a thin Membrane Diffusion Problem;a Numerical Scheme for Evacuation Dynamics;Additive Average Schwarz with Adaptive Coarse Space for Morley FE;application of Multiscale Computational Techniques to the Study of Magnetic Nanoparticle Systems;clique: A parallel Tool for the Molecular Nanomagnets Simulation and Modelling;Modelling of Limitations of BHJ Architecture in Organic Solar Cells;monte Carlo Study of Spherical and Cylindrical Micelles in Multiblock Copolymer Solutions;parallel Tiled Cache and Energy Efficient Code for Zukers RNA Folding;electronic and Optical Properties of Carbon Nanotubes Directed to their Applications in Solar Cells;the MPFI Library: Towards IEEE 17882015 Compliance;softmax and McFaddens Discrete Choice Under Interval (and Other) Uncertainty;experiments with Heterogenous Automata-Based Multi-agent Systems.

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13th international conference on parallel processing and applied mathematics, PPAM 2019

13th International Conference on Parallel Processing and App...

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13th international conference on parallel processing and applied mathematics, PPAM 2019

ISBN: (纸本)9783030432287

the proceedings contain 91 papers. the special focus in this conference is on parallel processing and applied mathematics. the topics include: A high-performance implementation of a robust preconditioner for heterogeneous problems;hybrid solver for quasi block diagonal linear systems;parallel adaptive cross approximation for the multi-trace formulation of scattering problems;Implementation of parallel 3-D Real FFT with 2-D decomposition on intel xeon phi clusters;Exploiting symmetries of small prime-sized DFTs;parallel computations for various scalarization schemes in multicriteria optimization problems;early performance assessment of the thunderX2 processor for lattice based simulations;An area efficient and reusable HEVC 1D-DCT hardware accelerator;improving locality-aware scheduling with acyclic directed graph partitioning;structure-aware calculation of many-electron wave function overlaps on multicore processors;isoefficiency maps for divisible computations in hierarchical memory systems;OpenMP target device offloading for the SX-Aurora TSUBASA vector engine;On the road to DiPOSH: Adventures in high-performance openSHMEM;click-Fraud detection for online advertising;parallel graph partitioning optimization under PEGASUS DA application global state monitoring;cloud infrastructure automation for scientific workflows;Posit NPB: Assessing the precision improvement in HPC scientific applications;a high-order discontinuous galerkin solver with dynamic adaptive mesh refinement to simulate cloud formation processes;Performance and portability of state-of-art molecular dynamics software on modern GPUs;Exploiting parallelism on shared memory in the QED particle-in-cell code PICADOR with greedy load balancing;lazy stencil integration in multigrid algorithms;parallelized construction of extension velocities for the level-set method;Relative expression classification tree. A preliminary GPU-Based implementation;SIMD-node transformations for non-blocking data structures.

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5th international conference on parallel processing and applied mathematics, PPAM 2003

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5th international conference on parallel processing and applied mathematics, PPAM 2003

ISBN: (纸本)3540219463

the proceedings contain 149 papers. the special focus in this conference is on parallel, Distributed Architectures, Scheduling and Load Balancing. the topics include: Session guarantees to achieve pram consistency of replicated shared objects;an extended atomic consistency protocol for recoverable DSM systems;hyper-threading technology speeds clusters;configurable microprocessor array for DSP applications;on generalized moore digraphs;RDMA communication based on rotating buffers for efficient parallel fine-grain computations;communication on the fly in dynamic SMP clusters;accelerated diffusion algorithms on general dynamic networks;suitability of load scheduling algorithms to workload characteristics;minimizing time-dependent total completion time on parallel identical machines;diffusion based scheduling in the agent-oriented computing system;approximation algorithms for scheduling jobs with chain precedence constraints;combining vector quantization and ant-colony algorithm for mesh-partitioning;wavelet-neuronal resource load prediction for multiprocessor environment;fault-tolerant scheduling in distributed real-time systems;online scheduling of multiprocessor jobs with idle regulation;predicting the response time of a new task on a beowulf cluster;space decomposition solvers and their performance in pc-based parallel computing environments;evaluation of execution time of mathematical library functions based on historical performance information;empirical modelling of parallel linear algebra routines;efficiency of divisible load processing;gray box based data access time estimation for tertiary storage in grid environment;performance modeling of parallel fem computations on clusters;asymptotical behaviour of the communication complexity of one parallel algorithm and analytical modeling of optimized sparse linear code.

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Fair-Sharing Simulator for Batch Computing Systems 15th

Fair-Sharing Simulator for Batch Computing Systems

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15th international conference on parallel processing and applied mathematics, PPAM 2024

作者： Klusáček, Dalibor CESNET Prague Czech Republic

ISBN: (纸本)9783031856990

Scientific computing centers or private (in-house) cloud data centers do not rely on the standard pay-as-you-go business model which is common in commercial clouds to allocate resources. Instead, the system is typically shared by a set of selected users, and the administrator’s job is to ensure that resources are shared fairly given the existing policies of that organization. One common approach, especially in batch systems, is to deploy a fairshare-based prioritization in the scheduler, where a prioritization mechanism balances resource consumption so that individual users get the right shares of resources over time. In this paper, we present a tool developed to simulate the fairshare setting in a batch system. Using a set of experiments, we demonstrate the utility of this tool in tuning fairshare settings in a standard HPC/HTC scheduler and present the impact of often-overlooked additional options for modifying the basic fairshare settings. All the findings in this paper are based on our real-world experience of running and optimizing a distributed national computing infrastructure in the Czech Republic. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Batch data processing

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11th international conference on parallel processing and applied mathematics, PPAM 2015

11th International Conference on Parallel Processing and App...

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11th international conference on parallel processing and applied mathematics, PPAM 2015

ISBN: (纸本)9783319321486

the proceedings contain 56 papers. the special focus in this conference is on parallel Architectures and Resilience, Numerical Algorithms and parallel Scientific Computing. the topics include: Exploring memory error vulnerability for parallel programming models;an approach for ensuring reliable functioning of a supercomputer based on a formal model;sparse matrix multiplication on dataflow engines;energy efficient calculations of text similarity measure on FPGA-accelerated computing platforms;a bucket sort algorithm for the particle-in-cell method on manycore architectures;experience on vectorizing lattice boltzmann kernels for multi- and many-core architectures;performance analysis of the Kahan-enhanced scalar product on current multicore processors;performance analysis of the Chebyshev basis conjugate gradient method on the K computer;dense symmetric indefinite factorization on GPU accelerated architectures;a parallel multi-threaded solver for symmetric positive definite bordered-band linear systems;parallel algorithm for quasi-band matrix-matrix multiplication;comparative performance analysis of coarse solvers for algebraic multigrid on multicore and manycore architectures;LU preconditioning for overdetermined sparse least squares problems;experimental optimization of parallel 3D overlapping domain decomposition schemes;massively parallel approach to sensitivity analysis on HPC architectures by using scalarm platform;GPU implementation of Krylov solvers for block-tridiagonal eigenvalue problems;comparison of large graphs using distance information;fast incremental community detection on dynamic graphs;a diffusion process for graph partitioning;a parallel algorithm for LZW decompression, with GPU implementation;parallel FDFM approach for computing GCDs using the FPGA and parallel induction of nondeterministic finite automata.

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parallel Construction of Independent Spanning Trees on 3-ary n-cube Networks 20th

Parallel Construction of Independent Spanning Trees on 3-a...

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20th IFIP WG 10.3 international conference on Network and parallel Computing, NPC 2024

作者： Xu, Yuzhen Fan, Weibei Lv, Mengjie Sun, Xueli Han, Lei Xiao, Fu School of Computer Science Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9789819628292

As networks grow larger and more intricate, failures become unavoidable. Interconnection networks need continual and reliable functioning, as well as effective routing methods for transmitting data among processors. Ensuring fault tolerance in routing, especially through independent spanning trees (ISTs), is crucial. the 3-ary n-cube network (Qn3) boasts numerous properties such as low vertex degree, regularity, and straightforward implementation. In this paper, We have presented an effective parallel constructive approach for ISTs on Qn3 relying on the ascending sequence. Derived from the ISTs constructed before, we obtain a fault-tolerant routing system that utilizes those as its routing table. Following this, we evaluate the effectiveness of the fault-tolerant routing mechanism through simulated data. Simulated data reveals a progressive escalation in transmission success rates as dimensionality increases, approaching near-perfection at almost 100%. Its findings can provide a valuable benchmark and offer insights into the efficacy of fault-tolerant communication within a broad spectrum of cube-based systems. © IFIP international Federation for Information processing 2025.

关键词： Trees (mathematics)

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11th international conference on parallel processing and applied mathematics, PPAM 2015

11th International Conference on Parallel Processing and App...

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11th international conference on parallel processing and applied mathematics, PPAM 2015

ISBN: (纸本)9783319321516

the proceedings contain 56 papers. the special focus in this conference is on Models, Algorithms, Energy Aspects of Computation, Scheduling for parallel Computing and Language-Based parallel Programming Models. the topics include: Virtualizing CUDA enabled GPGPUS on arm clusters;a distributed hash table for shared memory;mathematical approach to the performance evaluation of matrix multiply algorithm;a scalable numerical algorithm for solving tikhonov regularization problems;energy performance modeling with TIA and EML;considerations of computational efficiency in volunteer and cluster computing;parallel programs scheduling with architecturally supported regions;adaptive multi-level workflow scheduling with uncertain task estimates;divisible loads scheduling in hierarchical memory systems with time and energy constraints;extending Gustafson-barsis’s law for dual-architecture computing;free scheduling of tiles based on the transitive closure of dependence graphs;multi-threaded construction of neighbour lists for particle systems in openMP;high productivity and high performance;parallel ant brood graph partitioning in Julia;scalability model based on the concept of granularity;performance and power-aware modeling of MPI applications for cluster computing;running time prediction for web search queries;performance analysis of a parallel, multi-node pipeline for DNA sequencing;parallelising the computation of minimal absent words;modeling and simulations of edge-emitting broad-area semiconductor lasers and amplifiers;application of the parallel inmost platform to subsurface flow and transport modelling;genetic algorithm and exact diagonalization approach for molecular nanomagnets modelling and parallel Monte Carlo simulations for spin models with distributed lattice.

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Harnessing Large Language Models for Precision Topic Extraction and Technology Patent Nomination: A GPT-centric Methodology 16

Harnessing Large Language Models for Precision Topic Extract...

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16th international conference on Ambient Systems, Networks and Technologies Networks, ANT 2025 / 8th international conference on Emerging Data and Industry 4.0, EDI40 2025

作者： Nkolongo, Franck Tshibanda Echchakoui, Said Mehdi, Adda Department of Mathematics Computer Science and Engineering University of Quebec at Rimouski Canada Management Sciences Departmental Unit University of Quebec at Rimouski (Lévis) Canada

Topic modeling is widely used for analyzing large textual datasets, particularly in technology patent nomination. Traditional methods, such as Latent Dirichlet Allocation (LDA) and Non-Negative Matrix Factorization (NMF), often struggle with semantic comprehension, scalability, and adaptability. this study investigates Large Language Models (LLMs) to overcome these limitations. Leveraging their advanced language understanding, GPT models generate coherent and contextually relevant topics, outperforming conventional methods. they also excel in identifying emerging trends, enhancing patent nomination processes. Our findings demonstrate the potential of GPT-based approaches to streamline patent analysis and accelerate technological discovery. © 2025 Elsevier B.V.. All rights reserved.

关键词： GPT Applications Large Language Models (LLMs) Natural Language processing (NLP) Patent Analysis Topic Modeling

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Special issue on advances in techniques for assessment performance portability of HPC applications

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Future Generation Computer Systems 2025年 171卷

作者： Marowka, Ami Stpiczyński, Przemyslaw Wyrzykowski, Roman Parallel Research Lab Petach Tikva49729 Israel Institute of Computer Science Maria Curie-Sklodowska University Lublin20-033 Poland Department of Computer Science Czestochowa University of Technology Czestochowa42-201 Poland

this special issue aims to present new developments and advances in techniques for assessment performance portability of high performance computing applications. It contains revised and extended versions of selected papers presented at the 10th Workshop on Language-Based parallel Programming Models, WLPP 2024, which was a part of 15th international conference on parallel processing and applied mathematics, PPAM 2024, held on September 8–11, 2024, in Ostrava, Czech Republic. © 2025

关键词： HPC applications parallel programming languages Performance portability

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parallel Reinforcement Learning and Gaussian Process Regression for Improved Physics-Based Nasal Surgery Planning 15th

Parallel Reinforcement Learning and Gaussian Process Regres...

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15th international conference on parallel processing and applied mathematics, PPAM 2024

作者： Rüttgers, Mario Hübenthal, Fabian Tsubokura, Makoto Lintermann, Andreas Jülich Supercomputing Centre Forschungszentrum Jülich Jülich52428 Germany RWTH Aachen University Aachen52062 Germany Department of Computational Science Graduate School of System Informatics Kobe University Kobe657-8501 Japan Complex Phenomena Unified Simulation Research Team RIKEN Center for Computational Science Kobe650-0047 Japan

ISBN: (纸本)9783031857027

Septoplasty and turbinectomy are among the most frequent but also most debated interventions in the field of rhinology. A previously developed tool enhances surgery planning by physical aspects of respiration, i.e., for the first time a reinforcement learning (RL) algorithm is combined with large-scale computational fluid dynamics (CFD) simulations to plan anti-obstructive surgery. In the current study, an improvement of the tool’s predictive capabilities is investigated for the aforementioned types of surgeries by considering two approaches: (i) training of parallel environments is executed on multiple ranks and the agents of each environment share their experience in a pre-defined interval and (ii) for some of the state-reward combinations the CFD solver is replaced by a Gaussian process regression (GPR) model for an improved computational efficiency. It is found that employing a parallel RL algorithm improves the reliability of the surgery planning tool in finding the global optimum. However, parallel training leads to a larger number of state-reward combinations that need to be computed by the CFD solver. this overhead is compensated by replacing some of the computations with the GPR algorithm, i.e., around 6% of the computations can be saved without significantly degrading the predictions’ accuracy. Nevertheless, increasing the number of state-reward combinations predicted by the GPR algorithm only works to a certain extent, since this also leads to larger errors. © the Author(s) 2025.

关键词： Reinforcement learning

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