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检索条件"任意字段=8th International Conference on Algorithms and Architectures for Parallel Processing"

共 2864 条记录，以下是41-50 订阅

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19th international conference on algorithms and architectures for parallel processing, ICA3PP 2019

19th International Conference on Algorithms and Architecture...

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19th international conference on algorithms andarchitectures for parallel processing, ICA3PP 2019

ISBN: (纸本)9783030389901

the proceedings contain 102 papers. the special focus in this conference is on algorithms and architectures for parallel processing. the topics include: A New Robust and Reversible Watermarking Technique Based on Erasure Code;exit-Less Hypercall: Asynchronous System Calls in Virtualized Processes;automatic Optimization of Python Skeletal parallel Programs;impromptu Rendezvous Based Multi-threaded Algorithm for Shortest Lagrangian Path Problem on Road Networks;FANG: Fast and Efficient Successor-State Generation for Heuristic Optimization on GPUs;DETER: Streaming Graph Partitioning via Combined Degree and Cluster Information;which Node Properties Identify the Propagation Source in Networks?;t/t-Diagnosability of BCube Network;strark-H: A Strategy for Spatial Data Storage to Improve Query Efficiency Based on Spark;SWR: Using Windowed Reordering to Achieve Fast and Balanced Heuristic for Streaming Vertex-Cut Graph Partitioning;multitask Assignment Algorithm Based on Decision Tree in Spatial Crowdsourcing Environment;TIMOM: A Novel Time Influence Multi-objective Optimization Cloud Data Storage Model for Business Process Management;RTEF-PP: A Robust Trust Evaluation Framework with Privacy Protection for Cloud Services Providers;a Privacy-Preserving Access Control Scheme with Verifiable and Outsourcing Capabilities in Fog-Cloud Computing;utility-Aware Edge Server Deployment in Mobile Edge Computing;predicting Hard Drive Failures for Cloud Storage Systems;Efficient Pattern Matching on CPU-GPU Heterogeneous Systems;improving Performance of Batch Point-to-Point Communications by Active Contention Reduction through Congestion-Avoiding Message Scheduling;an Open Identity Authentication Scheme Based on Blockchain;RBAC-GL: A Role-Based Access Control Gasless Architecture of Consortium Blockchain;flexible Data Flow Architecture for Embedded Hardware Accelerators;developing Patrol Strategies for the Cooperative Opportunistic Criminals.

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15th international conference on algorithms and architectures for parallel processing, ICA3PP 2015

15th International Conference on Algorithms and Architecture...

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15th international conference on algorithms and architectures for parallel processing, ICA3PP 2015

ISBN: (纸本)9783319271392

the proceedings contain 59 papers. the special focus in this conference is on Software Systems, Programming Models, Performance Modeling and Evaluation. the topics include: A scalable fault-tolerance programing model on MIC cluster;multi-chunk redundant array of independent SSDS with improved performance;an energy efficient storage system for astronomical observation data on dome a;parallel aware hybrid solid-state storage;automatic optimization of software transactional memory through linear regression and decision tree;a data-centric tool to improve the performance of multithreaded program on NUMA;a light-weight hot data identification scheme via grouping-based LRU lists;towards interactive programming with parallel linear algebra in r;enhancing i/o scheduler performance by exploiting internal parallelism of SSDS;a performance and scalability analysis of the MPI based tools utilized in a large ice sheet model executing in a multicore environment;an efficient algorithm for a generalized LCS problem;on exploring a quantum particle swarm optimization method for urban traffic light scheduling;identifying repeated interleavings to improve the efficiency of concurrency bug detection;global reliability evaluation for cloud storage systems with proactive fault tolerance;performance evaluation and optimization of Wi-Fi display on android;a novel scheduling algorithm for file fetch in transparent computing;joint power and reduced spectral leakage-based resource allocation for d2d communications in 5G and an optimization strategy of energy consumption for data transmission based on optimal stopping theory in mobile networks.

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parallel Implementation of Number-theoretic Transform on GPU Clusters 24th

Parallel Implementation of Number-Theoretic Transform on G...

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24th international conference on algorithms and architectures for parallel processing, ICA3PP 2024

作者： Takahashi, Daisuke Center for Computational Sciences University of Tsukuba 1-1-1 Tennodai Ibaraki Tsukuba305-8577 Japan

ISBN: (纸本)9789819615414

In this paper, we propose a parallel implementation of the number-theoretic transform (NTT) on GPU clusters. the butterfly operation of the NTT can be performed using modular addition, subtraction, and multiplication. We show that the four-step fast Fourier transform algorithm can be applied to the NTT. We parallelized the four-step NTT using MPI and OpenACC on GPU clusters. We achieved a performance of over 745 giga-operations per second on 32 nodes of a GPU cluster equipped with NVIDIA H100 PCIe GPUs for a 235-point NTT with a modulus of 63 bits. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Number theory

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algorithms and architectures for parallel processing: 13th international conference, ICA3PP 2013, Vietri sul Mare, Italy, December 18-20, 2013, Proceedings, Part I

Algorithms and Architectures for Parallel Processing: 13th I...

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2013年

作者： Joanna KołOdziej Beniamino Di Martino Domenico Talia

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algorithms and architectures for parallel processing: 13th international conference, ICA3PP 2013, Vietri sul Mare, Italy, December 18-20, 2013, Proceedings, Part II

Algorithms and Architectures for Parallel Processing: 13th I...

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2013年

作者： Rocco Aversa Joanna KołOdziej Jun Zhang

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PEbfs: Implement High-Performance Breadth-First Search on PEZY-SC3s 24th

PEbfs: Implement High-Performance Breadth-First Search on P...

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24th international conference on algorithms and architectures for parallel processing, ICA3PP 2024

作者： Guo, Weihao Wang, Qinglin Liu, Xiaodong Peng, Muchun Yang, Shun Liang, Yaling Shi, Yongzhen Cao, Ligang Liu, Jie Laboratory of Digitizing Software for Frontier Equipment National University of Defense Technology Changsha410073 China National Key Laboratory of Parallel and Distributed Computing National University of Defense Technology Changsha410073 China Engineering Research Center for National Fundamental Software National University of Defense Technology Changsha410073 China

ISBN: (纸本)9789819615506

the breadth-first search (BFS) algorithm is a fundamental algorithm in graph theory, and it’s parallelization can significantly improve performance. therefore, there have been numerous efforts to leverage the powerful parallel computing capabilities of hardware like GPGPU to implement high-performance BFS algorithms. However, the energy efficiency is relatively low due to the high power consumption of the platforms on which the algorithm is adapted to. To deal with these challenges, this paper introduces PEbfs that is a high-performance BFS algorithm based on the PEZY-SC3s efficient processor. We integrated three search algorithms, two algorithm optimization strategies, and a directional optimization scheme into PEbfs. through multiple evaluations of the performance of PEbfs on the public SNAP dataset, the results demonstrate that the average energy efficiency ratio of PEbfs is higher than that of Enterprise and Tigr, the two most advanced implementations on Nvidia’s GPGPU: It achieves 3.08× the average energy efficiency ratio of Enterprise and 4.53× that of Tigr. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Optimization algorithms

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MARO: Enabling Full MPI Automatic Refactoring in DSL-Based Programming Framework 24th

MARO: Enabling Full MPI Automatic Refactoring in DSL-Based ...

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24th international conference on algorithms and architectures for parallel processing, ICA3PP 2024

作者： Lei, Tong Chen, Zongjing Che, Yonggang Xu, Chuanfu Laboratory of Digitizing Software for Frontier Equipment National University of Defense Technology Changsha410073 China National Key Laboratory of Parallel and Distributed Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China

ISBN: (纸本)9789819615445

Currently, the landscape of computer hardware architecture presents the characteristics of heterogeneity and diversity, prompting widespread attention to cross-platform portable parallel programming techniques. Most existing portable programming approaches adopt the "MPI+X" strategy, focusing mainly on node-level "X" parallelism, while inter-node parallelization still relies on manual MPI programming. OP2 is a domain-specific language-based portable parallel programming framework for unstructured mesh applications that supports the automatic generation of MPI parallel code. However, programmers must manually write pre-processing code during code refactoring, such as handling the mapping relationship between global and process-local variables and the initial distribution of process-local data. In this paper, we propose MARO (MPI Automatic Refactoring for OP2), an automatic refactoring method for generating pre-processing code targeting MPI code generation within the OP2 programming framework for unstructured mesh applications. this method automatically generates the pre-processing code required for MPI parallelism through the source-to-source translator, enabling OP2 to generate MPI parallel code without requiring users to write MPI-related code manually. We compare the automatically refactored OP2 applications using the proposed method with those manually refactored to validate its effectiveness. the proposed method enhances OP2’s automatic parallel code generation capability, enabling it to achieve fully automatic MPI parallelization. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Automatic programming

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Dynamic Offloading Control for Waste Sorting Based on Deep Q-Network 24th

Dynamic Offloading Control for Waste Sorting Based on Deep...

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24th international conference on algorithms and architectures for parallel processing, ICA3PP 2024

作者： Wang, Jing Wang, Xiaoyang Guo, Jianxiong Tang, Zhiqing Ding, Xingjian Wang, Tian Advanced Institute of Natural Sciences Beijing Normal University Zhuhai China Guangdong Key Lab of AI and Multi-modal Data Processing Department of Computer Science BNU-HKBU United International College Zhuhai China Faculty of Information Technology Beijing University of Technology Beijing China

ISBN: (纸本)9789819615278

With the increasing concern for environmental protection and resource optimization, efficient waste sorting has become a serious challenge today. In this paper, we propose a new offloading control problem that aims to solve waste sorting in wireless bin communication networks. Due to limited computational power, bins belonging to embedded devices rely on simple classification models with varying accuracy. In this scenario, consider a network of intelligent bins, each acting as an independent agent capable of deciding to offload an image to the edge server with a more accurate but resource-intensive model when the local classification is deemed inaccurate. thus, Our goal is to find a lightweight online offloading policy that can achieve the best possible sorting accuracy while balancing transmission traffic. the method utilizes a Deep Q-network algorithm that enables each intelligent bin to make image-processing decisions autonomously. In the experiment, we validate the effectiveness of improving the performance of waste classification compared with existing flow control methods. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Distributed Resource Allocation Intelligent Waste Management Waste Sorting Wireless Communication Network

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Federated Learning and parallel Prompt Scheduling Strategies for Large Language Models 24th

Federated Learning and Parallel Prompt Scheduling Strategie...

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24th international conference on algorithms and architectures for parallel processing, ICA3PP 2024

作者： Lv, Guangtong Gu, Bruce Jia, Xiaocong Gao, Longxiang Qu, Youyang Cui, Lei Jinan China Shandong Provincial Key Laboratory of Computer Power Internet and Service Computing Shandong Fundamental Research Center for Computer Science Jinan China

ISBN: (纸本)9789819615278

Large language models have garnered significant attention and are widely utilized across different fields due to their impressive performance. However, centralized training of these models can pose privacy risks like data leakage, hindering their application and advancement. As a decentralized learning paradigm, Federated Learning(FL) can effectively address data security in large language models and has specific application scenarios. In addition, the fine-tuning process of large language models also incurs significant communication expenses and leads to the loss of computational resources. the utilization of prompt tuning in federated learning is anticipated to decrease training costs, accelerate the training process, and enhance model performance. In this paper, we propose ‘FedLLM-PPS’ to explore a novel approach for large language models within federated learning. this method address data security concerns associated with large language models while enhancing performance and efficiency. Experiments based on several datasets for various Natural Language processing(NLP) tasks demonstrate superior performance and efficiency compared to baseline methods. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Federated learning

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Retinal Image Analysis for Detection of Diabetic Macular Edema Using Transfer Learning 8

Retinal Image Analysis for Detection of Diabetic Macular Ede...

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8th international conference on Data Science and Machine Learning Applications, CDMA 2025

作者： Asim, Tayyaba Akbar, Shahzad Shahzore, Usama Rehman, Amjad Saba, Tanzila Ayesha, Noor Riphah College of Computing Riphah International University Faisalabad Pakistan Prince Sultan University AIDA Lab. CCIS Riyadh Saudi Arabia Zhengzhou University Zhengzhou China Henan450001 China

ISBN: (纸本)9798331539696

Diabetic Macular Edema (DME) is a disease of the eye's retina and it's a major factor of causing vision problems and leads towards blindness if it is undiagnosed. Early detection of DME can prevent vision loss and may reduce diabetic-related problems like cardiovascular issues. therefore, this study presents a method for detecting DME through Optical Coherence Tomography (OCT) and fundus images using transfer learning. the proposed method is based on four stages: Pre-processing, augmentation, segmentation through DeepLabV3+, and binary classification of DME by using two (02) publicly available datasets;the first dataset is Messidor-2, which contains fundus images, and the second dataset is Retinal Images of Optical Coherence Tomography (OCT). In the Messidor-2 dataset, the total number of images is 1744, and Retinal OCT Images dataset consists of 84,495 images total, separated into four categories (CNV, DME, DRUSEN, NORMAL). In the proposed method, Convolutional Neural Networks (CNN) architectures ResNet50 and VGG-19 have been used for the detection of the DME. Convolutional Neural Networks (CNNs) have been extensively used in medical imaging analysis and classification. Using the well-known ResNet50 architecture for classification of each dataset, the proposed model yielded an accuracy of 98.79%, 99% of F1 Score, 98.43% of Precision, and recall of 98.89%. By using VGG-19, the proposed model gives an accuracy of 98.81%, 98.94% of Fl Score, 98.1 % of Precision and recall of 98.73%. When both models (ResNet50 and VGG-19) were compared, the VGG-19 gave the best accuracy. © 2025 IEEE.

关键词： Convolutional neural networks

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