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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)9783319271361

the proceedings contain 59 papers. the special focus in this conference is on Applications of parallel and Distributed Computing. the topics include: On exploring a virtual agent negotiation inspired approach for route guidance in urban traffic networks;optimization of binomial option pricing on intel MIC heterogeneous system;stencil computations on HPC-oriented ARMv8 64-bit multi-core processor;a particle swarm optimization algorithm for controller placement problem in software defined network;a streaming execution method for multi-services in mobile cloud computing;economy-oriented deadline scheduling policy for render system using IaaS cloud;towards detailed tissue-scale 3D simulations of electrical activity and calcium handling in the human cardiac ventricle;task parallel implementation of matrix multiplication on multi-socket multi-core architectures;refactoring for separation of concurrent concerns;exploiting scalable parallelism for remote sensing analysis models by data transformation graph;resource-efficient vibration data collection in cyber-physical systems;a new approach for vehicle recognition and tracking in multi-camera traffic system;a scalable distributed fingerprint identification system;energy saving and load balancing for SDN based on multi-objective particle swarm optimization;pre-stack kirchhoff time migration on hadoop and spark;a cyber physical system with GPU for CNC applications;a solution of the controller placement problem in software defined networks;parallel column subset selection of kernel matrix for scaling up support vector machines;real-time deconvolution with GPU and spark for big imaging data analysis and parallel kirchhoff pre-stack depth migration on large high performance clusters.

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A Mini-model can Make Machine Unlearning Better 24th

A Mini-model can Make Machine Unlearning Better

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24th international conference on algorithms and architectures for parallel processing, ica3pp 2024

作者： Zhao, Mingkang Yu, Weng Zhu, Congcong China University of Geosciences Wuhan China Ministry of Education Key Laboratory of Ethnic Language Intelligent Analysis and Security Governance School of Information Engineering Beijing China Hainan International College of Minzu University of China Li’an International Education Innovation pilot Zone Hainan572499 China City University of Macau 999078 China

ISBN: (纸本)9789819615247

In recent years, with the development of machine learning, plenty of personal data have been utilized in the training process of the models which incurs severe privacy leakage in the field. Current regulations mandate the removal of private user information from both databases and machine learning models upon specific deletion requests. While wiping data records from memory storage is a straightforward task, eliminating the influence of specific data samples from an already-trained model is challenging. Numerous studies in machine unlearning focus on mitigating the impact of target data by adjusting model parameters in deep learning. However, existing methods for data removal in deep learning often fall short of meeting real-world practicality. the intricacies of deep neural networks make unlearning in deep learning a less expedient process than retraining from scratch. For example, some methods require a ton of matrix calculations or even more complicated computations, and some algorithms need a lot of space, which ends up hindering their effectiveness in real-world applications. Accordingly, we’ve come up with a more practical solution. Our method just needs a small part of the validation dataset to pre-train a mini-model to update the parameters of the target model quickly. With this assistant model, we can quickly and accurately unlearn target classes and items. We prove that our proposed method is highly effective in unlearning tasks with not very large amounts of data. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Information leakage

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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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algorithms and architectures for parallel processing - 8th international conference, 2008, Proceedings

Algorithms and Architectures for Parallel Processing - 8th I...

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8th international conference on algorithms and architectures for parallel processing, ica3pp 2008

ISBN: (纸本)9783540695004

the proceedings contain 33 papers. the topics discussed include: smart content delivery on the Internet;parallel query processing in databases on multicore architectures;evaluation of a novel load-balancing algorithm with variable granularity;a static multiprocessor scheduling algorithm for arbitrary directed task graphs in uncertain environments;architecture aware partitioning algorithms;a simple and efficient fault-tolerant adaptive routing algorithm for meshes;fault tolerance in the biswapped network;a general approach to predict the performance order of TSP family problems;examining the feasibility of reconfigurable models for molecular dynamics simulation;parallel simulated annealing for materialized view selection in data warehousing environments;an optimization service for DSP multicomputers;and a non-blocking multithreaded architecture with support for speculative threads.

关键词： Simulated annealing

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A parallel Algorithm of Kirchhoff Pre-stack Depth Migration Based on GPU 1

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14th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Wang, Yida Li, Chao Tian, Yang Yan, Haihua Zhao, Changhai Zhang, Jianlei Beihang Univ Sch Comp Sci & Engn Beijing 100191 Peoples R China

ISBN: (数字)9783319111940

ISBN: (纸本)9783319111940;9783319111933

Kirchhoff pre-stack depth migration (KPSDM) algorithm, as one of the most widely used migration algorithms, plays an important part in getting the real image of the earth. However, this program takes considerable time due to its high computational cost;hence the working efficiency of the oil industry is affected. the general purpose Graphic processing Unit (GPU) and the Compute Unified Device Architecture (CUDA) developed by NVIDIA have provided a new solution to this problem. In this study, we have proposed a parallel algorithm of the Kirchhoff pre-stack depth migration and an optimization strategy based on the CUDA technology. Our experiments indicate that for large data computations, the accelerated algorithm achieves a speedup of 8 similar to 15 times compared with NVIDIA GPU.

关键词： Kirchhoff pre-stack depth migration GPU CUDA parallel algorithm optimization

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PruX: Communication Pruning of parallel BFS in the Graph 500 Benchmark 18th

PruX: Communication Pruning of Parallel BFS in the Graph 500...

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18th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Jia, Menghan Zhang, Yiming Li, Dongsheng Mei, Songzhu Natl Univ Def Technol Changsha Peoples R China

ISBN: (纸本)9783030050511;9783030050504

parallel Breadth First Search (BFS) is a representative algorithm in Graph 500, the well-known benchmark for evaluating supercomputers for data-intensive applications. However, the specific storage model of Graph 500 brings severe challenge to efficient communication when computing parallel BFS in large-scale graphs. In this paper, we propose an effective method PruX for optimizing the communication of parallel BFS in two aspects. First, we adopt a scalable structure to record the access information of the vertices on each machine. Second, we prune unnecessary inter-machine communication for previously accessed vertices by checking the records. Evaluation results show that the performance of our method is at least six times higher than that of the original implementation of parallel BFS.

关键词： Breadth First Search Graph 500 Communication pruning

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A Multiplatform parallel Approach for Lattice Sieving algorithms 20th

A Multiplatform Parallel Approach for Lattice Sieving Algori...

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20th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Andrzejczak, Michal Gaj, Kris Mil Univ Technol Warsaw Poland George Mason Univ Fairfax VA 22030 USA

ISBN: (纸本)9783030602451;9783030602444

Lattice sieving is currently the leading class of algorithms for solving the shortest vector problem over lattices. the computational difficulty of this problem is the basis for constructing secure post-quantum public-key cryptosystems based on lattices. In this paper, we present a novel massively parallel approach for solving the shortest vector problem using lattice sieving and hardware acceleration. We combine previously reported algorithms with a proper caching strategy and develop hardware architecture. the main advantage of the proposed approach is eliminating the overhead of the data transfer between a CPU and a hardware accelerator. the authors believe that this is the first such architecture reported in the literature to date and predict to achieve up to 8 times higher throughput when compared to a multi-core high-performance CPU. Presented methods can be adapted for other sieving algorithms hard to implement in FPGAs due to the communication and memory bottleneck.

关键词： Lattice sieving Hardware acceleration Cryptography Multi-platform parallel approach parallel algorithms

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Accelerating Exhaustive Pairwise Metagenomic Comparisons 17th

Accelerating Exhaustive Pairwise Metagenomic Comparisons

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17th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Perez-Wohlfeil, Esteban Torreno, Oscar Trelles, Oswaldo Univ Malaga Dept Comp Architecture Blvd Louis Pasteur 35 Malaga Spain

ISBN: (纸本)9783319654829;9783319654812

In this manuscript, we present an optimized and parallel version of our previous work IMSAME, an exhaustive gapped aligner for the pairwise and accurate comparison of metagenomes. parallelization strategies are applied to take advantage of modern multiprocessor architectures. In addition, sequential optimizations in CPU time and memory consumption are provided. these algorithmic and computational enhancements enable IMSAME to calculate near optimal alignments which are used to directly assess similarity between metagenomes without requiring reference databases. We show that the overall efficiency of the parallel implementation is superior to 80% while retaining scalability as the number of parallel cores used increases. Moreover, we also show that sequential optimizations yield up to 8x speedup for scenarios with larger data.

关键词： High Performance Computing Pairwise comparison parallel computing Next Generation Sequencing Metagenome comparison

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algorithms and architectures for parallel processing 1

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丛书名： Lecture Notes in Computer Science

1000年

ISBN: (数字)9783540695011

ISBN: (纸本)9783540695004

Welcome to the proceedings of the 8th international conference on algorithms and architectures for parallel processing (ica3pp 2008). ica3pp 2008 consist of two keynote addresses, seven technical sessions, and one tutorial. Included in these proceedings are papers whose authors are from Australia, Brazil, Canada, China, Cyprus, France, India, Iran, Israel, Italy, Japan, Korea, Germany, Greece, Mexico, Poland, Portugal, Romania, Spain, Switzerland, Taiwan, Tunisia, UAE, UK, and USA. Each paper was rigorously reviewed by at least three Program Committee members and/or external revi- ers, and the acceptance ratio is 35%. these papers were presented over seven technical sessions. Based on the paper review results, three papers were selected as the best papers. We would like to thank the many people who helped make this conference a successful event. We thank all authors who submitted their work to ica3pp 2008, and all Program Committee members and additional reviewers for their diligent work in the paper review process ensuring a collection of high-quality papers. We are grateful to Hong Shen University of Adelaide, Australia and Kleanthis Psarris University of Texas at San Antonio, United States, for their willingness to be the keynote speakers. Our thanks go to Hai Jin and George Papapodoulos, the conference General Co-chairs, and Andrzej Goscinski, W- lei Zhou and Yi Pan, the conference Steering Committee Co-chairs for help in many aspects of organizing this conference. Finally, we thank all the conference participants for traveling to Cyprus.

关键词： Software Engineering/Programming and Operating Systems Computer Engineering Programming Techniques Computer Systems Organization and Communication Networks Computation by Abstract Devices Algorithm Analysis and Problem Complexity

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Efficient parallel Implementations of Controlled Optimization of Traffic Phases

Efficient Parallel Implementations of Controlled Optimizatio...

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11th international conference on algorithms and architectures for parallel processing (ica3pp)

作者： Samra, Sameh El-Mahdy, Ahmed Gomaa, Walid Wada, Yasutaka Shoukry, Amin E JUST Alexandria Egypt Waseda Univ Fac Engn Sci Tokyo Japan

ISBN: (纸本)9783642246494

Finding optimal phase durations for a controlled intersection is a computationally intensive task requiring O(N-3) operations. In this paper we introduce cost-optimal parallelization of a dynamic programming algorithm that reduces the complexity to O(N-2). three implementations that span a wide range of parallel hardware are developed. the first is based on shared-memory architecture, using the OpenMP programming model. the second implementation is based on message passing, targeting massively parallel machines including high performance clusters, and supercomputers. the third implementation is based on the data parallel programming model mapped on Graphics processing Units (GPUs). Key optimizations include loop reversal, communication pruning, load-balancing, and efficient thread to processors assignment. Experiments have been conducted on 8-core server, IBM BlueGene/L supercomputer 2-node boards with 128 processors, and GPU GTX470 GeForce Nvidia with 448 cores. Results indicate practical scalability on all platforms, with maximum speed up reaching 76x for the GTX470.

关键词： parallel processing high performance computation traffic phases

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