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检索条件"任意字段=8th International Conference on Parallel Processing and Applied Mathematics"

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

15th International Conference on Parallel Processing and App...

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

ISBN: (纸本)9783031856990

the proceedings contain 75 papers. the special focus in this conference is on parallel processing and applied mathematics. the topics include: Enabling Mixed-Precision with the Help of Tools: A Nekbone Case Study;Sparse Matrix Ordering for Fine Grain parallel Triangular Solve Using SIMD;Stabilizing the Block BiCG with Extended Precision: A Case Study;Exploring the Design Space for Message-Driven Systems for Dynamic Graph processing Using CCA;introducing the Arm-Membench throughput Benchmark;Segmentation of Aortic Valve Calcium Lesions Using FPGA Accelerators;parallel Maximal Common Subgraphs with Labels for Molecular Biology;PPQSort: Pattern parallel Quicksort;ACE: Algorithm-Independent Acceleration and parallelization of Clustering Implementations;Improved GPU Memory Management in Evolutionary Decision Tree Induction for Large-Scale Data;Multi-GPU Accelerated Rendering of Massive Scenes with Out-of-Core Support for CPU Memory;A GPU Implementation of McMurchie-Davidson Algorithm for Two-Electron Repulsion Integral Computation;measuring and Interpreting Dependent Task-Based Applications Performances;using parallel Performance Data to Classify parallel Algorithms;Tracing of GPU-Aware MPI Applications: First Benchmarks for the Angara Interconnect;Flexible Algorithms for Persistent MPI Allreduce Communication;Towards the Democratization and Standardization of Dynamic Resources with MPI Spawning;compiler Support for Semi-manual AoS-to-SoA Conversions with Data Views;cultural Heritage 3D Object Management with Integrated Automation Workflows;collaborative Learning as a Service – a Blueprint for a Cloud Based Rural IoTs Deployment Facility;High-Performance Implementation of the Optimized Event Generator for Strong-Field QED Plasma Simulations;GPU-Based Interval Optimization in the Context of Optical MIMO Systems.

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

15th International Conference on Parallel Processing and App...

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

ISBN: (纸本)9783031856969

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

15th International Conference on Parallel Processing and App...

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

ISBN: (纸本)9783031857027

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14th international conference on parallel processing and applied mathematics, PPAM 2022

14th International Conference on Parallel Processing and App...

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14th international conference on parallel processing and applied mathematics, PPAM 2022

ISBN: (纸本)9783031304415

the proceedings contain 77 papers. the special focus in this conference is on parallel processing and applied mathematics. the topics include: Neural Nets with a Newton Conjugate Gradient Method on Multiple GPUs;Exploring Techniques for the Analysis of Spontaneous Asynchronicity in MPI-parallel Applications;Cost and Performance Analysis of MPI-Based SaaS on the Private Cloud Infrastructure;building a Fine-Grained Analytical Performance Model for Complex Scientific Simulations;evaluation of Machine Learning Techniques for Predicting Run Times of Scientific Workflow Jobs;Smart Clustering of HPC Applications Using Similar Job Detection Methods;distributed Work Stealing in a Task-Based Dataflow Runtime;task Scheduler for Heterogeneous Data Centres Based on Deep Reinforcement Learning;Shisha: Online Scheduling of CNN Pipelines on Heterogeneous Architectures;General Framework for Deriving Reproducible Krylov Subspace Algorithms: BiCGStab Case;proactive Task Offloading for Load Balancing in Iterative Applications;language Agnostic Approach for Unification of Implementation Variants for Different Computing Devices;high Performance Dataframes from parallel processing Patterns;global Access to Legacy Data-Sets in Multi-cloud Applications with Onedata;MD-Bench: A Generic Proxy-App Toolbox for State-of-the-Art Molecular Dynamics Algorithms;Breaking Down the parallel Performance of GROMACS, a High-Performance Molecular Dynamics Software;GPU-Based Molecular Dynamics of Turbulent Liquid Flows with OpenMM;a Novel parallel Approach for Modeling the Dynamics of Aerodynamically Interacting Particles in Turbulent Flows;reliable Energy Measurement on Heterogeneous Systems–on–Chip Based Environments;distributed Objective Function Evaluation for Optimization of Radiation therapy Treatment Plans;a Generalized parallel Prefix Sums Algorithm for Arbitrary Size Arrays;GPU4SNN: GPU-Based Acceleration for Spiking Neural Network Simulations;Ant System Inspired Heuristic Optimization of UAVs Depl

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14th international conference on parallel processing and applied mathematics, PPAM 2022

14th International Conference on Parallel Processing and App...

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14th international conference on parallel processing and applied mathematics, PPAM 2022

ISBN: (纸本)9783031304446

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Performance Analysis of Floyd-Warshall Algorithm: Sequential and parallel Execution Using Intel oneAPI 8

Performance Analysis of Floyd-Warshall Algorithm: Sequential...

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8th international conference on Electronics, Communication and Aerospace Technology, ICECA 2024

作者： Kumar, Sanjay Karthik, S. Srilakshmi, S. Dharun Viginesh, P. Srm Institute of Science and Technology Department of Ece Vadapalani Chennai India

ISBN: (纸本)9798350367904

the Floyd-Warshall algorithm is a widely utilized graph-based technique designed to address the all-pairs shortest path problem. However, its cubic time complexity O(n3) creates performance bottlenecks when applied to large graphs, especially in sequential execution. this paper explores the use of Intel oneAPI's Data parallel C++ (DPC++) programming model to optimize the performance of the Floyd-Warshall algorithm through parallel processing. A comparative performance analysis between sequential and parallel implementations on an Intel Xeon(R) CPU highlights up to a 43 % improvement in execution time for graphs with 800 nodes. the results underscore the potential of parallel computing in significantly reducing computational time for large-scale graph algorithms. © 2024 IEEE.

关键词： C++ (programming language)

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parallel processing of Power System Operation Data Based on MapReduce Algorithm 8

Parallel Processing of Power System Operation Data Based on ...

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8th international conference on Electrical, Mechanical and Computer Engineering, ICEMCE 2024

作者： Song, Tao Pu, Yu Luo, Yulei Zhong, Jiyou Tang, Hao Yalong River Hydropower Development Co. Ltd Chengdu610055 China Power China Sichuan Electric Power Engineering Co. Ltd Chengdu610095 China

ISBN: (纸本)9798331506230

the transition to large-scale new energy systems has greatly increased the complexity, volume, and multidimensionality of power data in the cloud, making data management more challenging and potentially risking the safe and stable operation of power systems. To tackle this, the paper proposes a power grid data analysis method using the MapReduce algorithm for efficient data processing. Results show that, even with large data volumes, processing efficiency is maintained at around 30 minutes, with stability and accuracy preserved as data volume grows. this method allows for parallel analysis of the grid and provides valuable insights for future data processing in power grid operations. © 2024 IEEE.

关键词： MapReduce

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Spatial Constrained and Candidate Expanded parallel Matching for Ultra-Low Delay Camera Pose Estimation 8

Spatial Constrained and Candidate Expanded Parallel Matching...

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8th international conference on Imaging, Signal processing and Communications (ICISPC)

作者： Sun, Tengxiao Li, Yuan Hu, Tingting Fuchikami, Ryuji Wang, Wei Ikenaga, Takeshi Waseda Univ Grad Sch Informat Prod & Syst Kitakyushu Fukuoka Japan Panasonic Connect Co Ltd Res & Dev Div Osaka Japan

ISBN: (纸本)9798350367164;9798350367157

In fields like robotics and factory automation (FA), an ultra-low delay vision system has emerged as a critical tool. this system processes videos at an astonishing 1000 frames per second (fps), with each frame being processed within 1 millisecond (1-ms). Camera pose estimation plays a crucial role by providing real-time and accurate spatial information, enabling rapid response and precise control of production processes in such systems. Existing works mainly focus on general purpose use (60fps) while less of the focus on specific use (1000fps). this paper proposed an ultra-low delay camera pose estimation method designed to meet the stringent requirements of modern FA systems. the spatial constrained and candidate expanded parallel matching is proposed for accelerating 3D-2D matching process. Spatial constrain utilizes the tiny movements between adjacent frames to shrink the search range to decrease the probability of matching conflicts. And candidate expansion increases the candidate matching points to guarantee the quality of matching between 2D and 3D spaces, which increases parallelism and enhances efficiency of the 3D-2D matching process. Experiments are conducted using a 1000 fps camera with resolution of 640 x 360 . the proposed method demonstrated robust performance across horizontal, vertical, and random camera movements, achieving an average Relative Pose Error (RPE) of 0.5 cm for translation and 0.4 degrees for rotation respectively.

关键词： camera pose estimation factory automation acceleration parallel ultra-low delay

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Automated Root Identification and Pattern Detection for Agglutinative Language processing: Enhancing Machine Learning Models for Complex Morphological Structures 24

Automated Root Identification and Pattern Detection for Aggl...

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8th international conference on Natural Language processing and Information Retrieval, NLPIR 2024

作者： Kardava, Irakli Faculty of Mathematics and Computer Science Department of Artificial Intelligence Adam Mickiewicz University Poznan Poznan Poland

ISBN: (纸本)9798400717383

Achieving high accuracy in various Language Models (LMs) and Large Language Models (LLMs) relies heavily on extensive training datasets. However, as natural languages evolve, words change form, and new words emerge, necessitating the continuous updating of these models. Incorporating new languages also adds to this complexity. Since texts are composed of words, these updates hinge on changes in word forms, making words and their forms the most critical components of the training set. this research focuses on generating grammatically correct word forms for different parts of speech using natural language processing (NLP) techniques, eliminating the need for manual pre-recording of the data and its storage in databases. this is crucial when dealing with agglutinative languages, and is especially valuable in the case of Less Resourced Languages (LRLs). Our experiments and findings primarily revolve around the Georgian language, but we indicate that this approach can be effectively applied to other agglutinative languages as well. © 2024 Copyright held by the owner/author(s).

关键词： Natural language processing systems

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Proceedings - 8th IEEE international conference on Image and Signal processing and their Applications, ISPA 2024

Proceedings - 8th IEEE International Conference on Image and...

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8th IEEE international conference on Image and Signal processing and their Applications, ISPA 2024

ISBN: (纸本)9798350309249

the proceedings contain 138 papers. the topics discussed include: efficient parking lot management system for parking attendants based on real-time impulsive sound detection and voice command recognition;impact of PON network range and laser power on GPON and XGSPON coexistence system;enhancing breast cancer classification using ensemble techniques and feature selection algorithms;diabetic retinopathy detection using modified U-Net architecture and artificial metaplasticity algorithm;brain tumor classification using DenseNet and U-net convolutional neural networks;a comparative analysis of branch-cut and quality-guided algorithms for inSAR interferogram;classification of multi-view mammogram images using a parallel pre-trained models system;and deep learning approaches for plant diseases identification and classification: a comprehensive review.

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