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检索条件"任意字段=10th International Conference on Algorithms and Architectures for Parallel Processing"

共 2805 条记录，以下是231-240 订阅

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parallel Asynchronous Stochastic Dual Coordinate Descent algorithms for High Efficiency and Stable Convergence

Parallel Asynchronous Stochastic Dual Coordinate Descent Alg...

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29th Euromicro international conference on parallel, Distributed and Network-Based processing (PDP)

作者： Chen, Yung-Chen Liu, Pangfeng Wu, Jan-Jan Natl Taiwan Univ Dept Comp Sci & Informat Engn Taipei Taiwan Natl Taiwan Univ Grad Inst Networking & Multimedia Taipei Taiwan Acad Sinica Inst Informat Sci Taipei Taiwan

ISBN: (纸本)9781665414555

parallel asynchronous stochastic dual coordinate descent algorithm (PASSCoDe) is an efficient method to train linear models in multi-core shared-memory systems. PASSCoDe enjoys a good speedup when the number of threads is less than 8 on sparse datasets, i.e., the percentage of nonzero elements in the training data is relatively small. However, due to the memory conflict and delayed parameter access problem in parallel execution, it often diverges or does not converge to the best accuracy as a serial dual coordinate descent algorithm does. In this paper, we propose two algorithms - Adaptive Hybrid algorithm and Lazy-Sync algorithm, to overcome the convergence issues in parallel execution. Both algorithms use the current accuracy to guide the execution and strike a balance between accuracy and efficiency. Experimental results indicate that both algorithms converge to the same high accuracy as a sequential program does on all datasets tested except on an extremely small one. On the other hand, PASSCoDe sometimes converges to a less accurate value or does not converge at all on some datasets. Our methods also outperform PASSCoDe-Fix, an improved version of PASSCoDe, in stable convergence, execution speed, and scalability. For example, the Adaptive llybrid algorithm runs up to 2.8 times faster than PASSCoDe-Fix, and the Lazy-Sync algorithm runs 11 times faster than PASSCoDe-Fix on dataset covt ype with 10 threads.

关键词： Machine learning parallel dual coordinate descent asynchronous algorithm linear model support vector machine

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High Performance Portable Solver for Tridiagonal Toeplitz Systems of Linear Equations

High Performance Portable Solver for Tridiagonal Toeplitz Sy...

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26th international conference on parallel and Distributed Computing (Euro-Par)

作者： Dmitruk, Beata Stpiczynski, Przemyslaw Marie Curie Sklodowska Univ Inst Comp Sci Ul Akad 9 PL-20033 Lublin Poland

ISBN: (纸本)9783030715939;9783030715922

We show that recently developed divide and conquer parallel algorithm for solving tridiagonal Toeplitz systems of linear equations can be easily and efficiently implemented for a variety of modern multicore and GPU architectures, as well as hybrid systems. Our new portable implementation that uses OpenACC can be executed on both CPU-based and GPU-accelerated systems. More sophisticated variants of the implementation are suitable for systems with multiple GPUs and it can use CPU and GPU cores. We consider the use of both columnwise and row wise storage formats for two dimensional double precision arrays and show how to efficiently convert between these two formats using cache memory. Numerical experiments performed on Intel CPUs and Nvidia GPUs show that our new implementation achieves relatively good performance.

关键词： Tridiagonal Toeplitz systems parallel algorithms Vectorization Portability OpenACC Hybrid systems

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Keyword-spotting and speech onset detection in EEG-based Brain Computer Interfaces 10

Keyword-spotting and speech onset detection in EEG-based Bra...

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10th international IEEE-EMBS conference on Neural Engineering (NER)

作者： Sakthi, Madhumitha Desai, Maansi Hamilton, Liberty Tewfik, Ahmed Univ Texas Austin Dept ECE Austin TX 78712 USA Univ Texas Austin Dept Speech Language & Hearing Sci Austin TX 78712 USA Univ Texas Austin Dept Neurol Austin TX 78712 USA

ISBN: (纸本)9781728143378

the growing intervention of automated speech recognition applications in everyday life drives improvement in Brain-Computer Interfaces (BCI) for speech processing. By incorporating ASR (Automatic Speech Recognition)-based "keyword spotting" or "wake up commands", we provide techniques for assessing when a BCI should start decoding, improving accuracy and efficiency for end users. Here, we use high density scalp EEG collected while participants listened to continuous speech in an audio-only, clear context, or while they watched highly noisy, naturalistic audiovisual movie clips. We designed three speech processing deep learning models: A sentence spotter (SS) model, Phoneme vs. Silence (PS) classifier and finally, Audio vs. Audio-visual (AV) stimuli induced EEG response classifier. the overall goal of this study is to design and examine the performance of these techniques for various speech processing applications. We use Long-Short Term Memory (LSTM) and Gated Recurrent Units (GRUs) neural network architectures and evaluated them on 16 participants' EEG data. We show 98.15% accuracy for our AV classifier, 98.56 F1 score on SS model and 70.33 F1 score on the PS model.(1)

关键词： Speech processing

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An MPI-based Algorithm for Mapping Complex Networks onto Hierarchical architectures 27th

An MPI-based Algorithm for Mapping Complex Networks onto Hie...

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27th international European conference on parallel and Distributed Computing (Euro-Par)

作者： Predari, Maria Tzovas, Charilaos Schulz, Christian Meyerhenke, Henning Humboldt Univ Berlin Germany Heidelberg Univ Heidelberg Germany

ISBN: (纸本)9783030856656;9783030856649

processing massive application graphs on distributed memory systems requires to map the graphs onto the system's processing elements (PEs). this task becomes all the more important when PEs have non-uniform communication costs or the input is highly irregular. Typically, mapping is addressed using partitioning, in a two-step approach or an integrated one. parallel partitioning tools do exist;yet, corresponding mapping algorithms or their public implementations all have major sequential parts or other severe scaling limitations. In this paper, we propose a parallel algorithm that maps graphs onto the PEs of a hierarchical system. Our solution integrates partitioning and mapping;it models the system hierarchy in a concise way as an implicit labeled tree. the vertices of the application graph are labeled as well, and these vertex labels induce the mapping. the mapping optimization follows the basic idea of parallel label propagation, but we tailor the gain computations of label changes to quickly account for the induced communication costs. Our MPI-based code is the first public implementation of a parallel graph mapping algorithm;to this end, we extend the partitioning library PARHIP. To evaluate our algorithm's implementation, we perform comparative experiments with complex networks in the million- and billion-scale range. In general our mapping tool shows good scalability on up to a few thousand PEs. Compared to other MPI-based competitors, our algorithm achieves the best speed to quality trade-off and our quality results are even better than non-parallel mapping tools.

关键词： Load balancing Process mapping Hierarchical architectures parallel label propagation

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Simulating Cyber Attacks and Designing Malware using Python

Simulating Cyber Attacks and Designing Malware using Python

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international conference on Signal processing and Integrated Networks (SPIN)

作者： Akash Ankit Shubham Inder Anuj Sharma Rahul Johari Deo Prakash Vidyarthi SWINGER: Security Wireless IoT Network Group of Engineering and Research University School of Information Communication and Technology Guru Gobind Singh Indraprastha University Dwarka New Delhi India Royal Melbourne Institute of Technology (RMIT University) Melboume Victoria Australia Parallel and Distributed System Lab School of Computer and Systems Sciences Jawaharlal Nehru University New Delhi India

In this Internet era, we have become heavily dependent on the World Wide Web and it has become a basic amenity for humans. A normal user can be trapped easily in this vicious web if not careful enough. It is a field that requires users to be on their toes every time they try to connect to this enormous interconnection of networks. Reports and Surveys have said that in the coming years, Cybercrime could become the biggest threat. In this proposed work, the authors have deployed applications and designed malware for the purpose of simulating various kinds of cyber-attacks so that they could study their effects & affects and ultimately devise solutions to resolve the vulnerabilities in a system. these applications included networking concepts & protocols and a software based keylogger which was developed with no malicious intent, but to analyse the architectural view or design of a malware and to study the stages of a malware attack like entry, distribution, exploitation, infection and execution. Efforts have been made to demonstrate spooting attacks with an idea of identifying vulnerabilities and security loopholes in a particular system that can be exploited by an attacker if not resolved within time.

关键词： Surveys Protocols Malware Internet Web sites Security Signal resolution

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A Log-Linear (2+5/6)-Approximation Algorithm for parallel Machine Scheduling with a Single Orthogonal Resource 27th

A Log-Linear (2+5/6)-Approximation Algorithm for Parallel Ma...

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27th international European conference on parallel and Distributed Computing (Euro-Par)

作者： Naruszko, Adrian Przybylski, Bartlomiej Rzadca, Krzysztof Univ Warsaw Inst Informat Warsaw Poland

ISBN: (纸本)9783030856656;9783030856649

As the gap between compute and I/O performance tends to grow, modern High-Performance Computing (HPC) architectures include a new resource type: an intermediate persistent fast memory layer, called burst buffers. this is just one of many kinds of renewable resources which are orthogonal to the processors themselves, such as network bandwidth or software licenses. Ignoring orthogonal resources while making scheduling decisions just for processors may lead to unplanned delays of jobs of which resource requirements cannot be immediately satisfied. We focus on a classic problem of makespan minimization for parallel-machine scheduling of independent sequential jobs with additional requirements on the amount of a single renewable orthogonal resource. We present an easily-implementable log-linear algorithm that we prove is 25/6-approximation. In simulation experiments, we compare our algorithm to standard greedy list-scheduling heuristics and show that, compared to LPT, resource-based algorithms generate significantly shorter schedules.

关键词： parallel machines Orthogonal resource Burst buffers Rigid jobs Approximation algorithm

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Accelerating Transformer architectures for Automatic Modulation Classification via Gated Activation Patch Selection 10

Accelerating Transformer Architectures for Automatic Modulat...

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10th international conference on Computer and Communications, ICCC 2024

作者： Pu, Xitong Luo, Chunbo Yin, Yihao Luo, Yang School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China

this paper presents a novel approach to Automatic Modulation Classification (AMC) that leverages a Gated Activation Patch Selection (GAPS) mechanism to enhance the efficiency of Transformer architectures. Our method addresses the computational challenges associated with Transformer-based AMC models by filtering out less informative signal patches before processing. the GAPS module utilizes convolutional layers to extract key features from the input signal and quantifies the importance of each patch through adaptive aggregation. By employing a Transformer encoder, the selected critical patches are transformed into embeddings, facilitating self-attention computations. Extensive experiments demonstrate that our method not only maintains competitive classification performance but also significantly reduces computational complexity, resulting in faster training and lower inference latency. Notably, our method achieves a 17.94% FLOPs reduction without any loss in performance, along with a similar degree of training acceleration, while the model's accuracy decreases by only 1.50% when the input signal length is reduced by 50%. © 2024 IEEE.

关键词： NP-hard

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10th international conference on Cloud Computing and Services Science, CLOSER 2020

10th International Conference on Cloud Computing and Service...

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10th international conference on Cloud Computing and Services Science, CLOSER 2020

ISBN: (纸本)9783030723682

the proceedings contain 14 papers. the special focus in this conference is on Cloud Computing and Services Science. the topics include: Investigating IoT Application Behaviour in Simulated Fog Environments;a Case for User-Defined Governance of Pure Edge Data-Driven Applications;cluster-Agnostic Orchestration of Containerised Applications;self-healing in the Scope of Software-Based Computer and Mobile Networks;relevance of Near-Term Quantum Computing in the Cloud: A Humanities Perspective;a Framework for Comparative Evaluation of High-Performance Virtualized Networking Mechanisms;cloud Computing for Enabling Big Data Analysis;A Multi-cloud parallel Selection Approach for Unlinked Microservice Mapped to Budget’s Quota: the PUM2Q;Live Migration Timing Optimization Integration with VMware Environments;using Self-Organizing Maps for the Behavioral Analysis of Virtualized Network Functions;from DevOps to NoOps: Is It Worth It?;fuzzy Container Orchestration for Self-adaptive Edge architectures.

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Comparative Study on Stroke Lesion Core Segmentation in CTP Images 10

Comparative Study on Stroke Lesion Core Segmentation in CTP ...

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10th IEEE international conference on Intelligent Computing and Information Systems, ICICIS 2021

作者： Esawy, Amira Fawzi, Sahar Elattar, Mustafa Nile University Medical Imaging and Image Processing Group Center of Informatics Science Giza Egypt

ISBN: (纸本)9781665440769

Automatic segmentation of ischemic stroke using Computed Tomography Perfusion (CTP) images becomes an essential tool for quantification of the extension of stroke in early stages because of its availability, speed, and low cost. In this paper, we combined non-contrast CT scans which help in showing the core of the lesion along with CTP perfusion maps that show the abnormality of perfusion to enhance the core segmentation task. We utilized the performance of Unet, ResUnet, and ResUnet++ architectures on the ISLES 2018 dataset to use a single architecture for direct segmentation. Data augmentation helped in increasing the training data, overcoming overfitting issues, and teaching the neural network the properties of invariance and robustness. Unet with data augmentation achieved a dice coefficient equal to 0.65 while ResUnet++ achieved a dice coefficient equal to 0.55 without using data augmentation. © 2021 IEEE.

关键词： Image segmentation

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18th international conference on algorithms and architectures for parallel processing, ICA3PP 2018

18th International Conference on Algorithms and Architecture...

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18th international conference on algorithms and architectures for parallel processing - ICA3PP 2018 Collocated Workshops: ICA3PP 2018 Workshop on Intelligent algorithms for Large-scale Complex Optimization Problems, IALCOP 2018, ICA3PP 2018 Workshop on Security and Privacy in Data processing, SPDP 2018

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