the proceedings contain 27 papers. the special focus in this conference is on parallel and distributedcomputing. the topics include: parallelization of the k-means Algorithm in a Spectral Clustering Chain on CPU-GPU ...
ISBN:
(纸本)9783030715922
the proceedings contain 27 papers. the special focus in this conference is on parallel and distributedcomputing. the topics include: parallelization of the k-means Algorithm in a Spectral Clustering Chain on CPU-GPU Platforms;Management of Heterogeneous Cloud Resources with Use of the PPO;An Open-Source Virtualization Layer for CUDA Applications;high Performance Portable Solver for Tridiagonal Toeplitz systems of Linear Equations;highPerMeshes – A Domain-Specific Language for Numerical Algorithms on Unstructured Grids;Implementation and Evaluation of CUDA-Unified Memory in Numba;Performance Evaluation of Java/PCJ Implementation of parallel Algorithms on the Cloud;parallelizing Automatic Temporal Cognitive Tool for Large-Scale Online Learning Analytics;Experiments Using a Software-distributed Shared Memory, MPI and 0MQ over Heterogeneous computing Resources;ants-Review: A Privacy-Oriented Protocol for Incentivized Open Peer Reviews on Ethereum;on the Provenance Extraction Techniques from Large Scale Log Files: A Case Study for the Numerical Weather Prediction Models;Improving Existing WMS for Reduced Makespan of Workflows with Lambda;predicting Hard Disk Failures in Data Centers Using Temporal Convolutional Neural Networks;On the Detection of Silent Data Corruptions in HPC Applications Using Redundant Multi-threading;analysis of Genome Architecture Mapping Data with a Machine Learning and Polymer-Physics-Based Tool;A New parallel Methodology for the Network Analysis of COVID-19 Data;next Generation Blockchain-Based Financial Services;a Digital Voting System for the 21st Century;trustless, Censorship-Resilient and Scalable Votings in the Permission-Based Blockchain Model;p2T: Pay to Transport;Balanced and Compressed Coordinate Layout for the Sparse Matrix-Vector Product on GPUs.
In this study we examine the coarse-grained approach to parallelization of the branch-and-bound algorithm. Our approach is that we split a mixed-integer programming problem into a predefined set of subproblems by fixi...
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Traditional high performance computing is based on massively parallel processor (MPP) supercomputers or high-end workstation clusters connected with high-speed networks. these approaches require a tight-coupled federa...
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Traditional high performance computing is based on massively parallel processor (MPP) supercomputers or high-end workstation clusters connected with high-speed networks. these approaches require a tight-coupled federation of computing resources that result in high cost and complex administration involvement. Today, the ubiquitous World Wide Web provides a new opportunity and paradigm for high performance distributedcomputing with millions of Internet connected computers. We present a novel approach to achieve high performance distributedcomputing in the Internet withdistributed object technology: JAM (Java Applet in Massively parallelcomputing). Our study provides the common features of this problem domain and case studies for the application of the proposed approach. Withthe massive availability of Internet computers in this approach, we could have the most powerful high performance distributedcomputing scheme that has never been achieved for our problem domain.
the proceedings contain 52 papers. the special focus in this conference is on Advanced Concepts for Intelligent Vision systems. the topics include: Two-Camera Synchronization and Trajectory Reconstruction for a Touch ...
ISBN:
(纸本)9783030014483
the proceedings contain 52 papers. the special focus in this conference is on Advanced Concepts for Intelligent Vision systems. the topics include: Two-Camera Synchronization and Trajectory Reconstruction for a Touch Screen Usability Experiment;comparison of Co-segmentation Methods for Wildlife Photo-identification;an Efficient Agglomerative Algorithm Cooperating with Louvain Method for Implementing Image Segmentation;robust Feature Descriptors for Object Segmentation Using Active Shape Models;foreground Background Segmentation in Front of Changing Footage on a Video Screen;Multi-organ Segmentation of Chest CT Images in Radiation Oncology: Comparison of Standard and Dilated UNet;Diffuse Low Grade Glioma NMR Assessment for Better Intra-operative Targeting Using Fuzzy Logic;identification of Saimaa Ringed Seal Individuals Using Transfer Learning;enhanced Codebook Model and Fusion for Object Detection with Multispectral Images;Matrix Descriptor of Changes (MDC): Activity Recognition Based on Skeleton;Unsupervised Perception Model for UAVs Landing Target Detection and Recognition;parallel and distributed Local Fisher Discriminant Analysis to Reduce Hyperspectral Images on Cloud computing Architectures;bayesian Vehicle Detection Using Optical Remote Sensing Images;Integrating UAV in IoT for RoI Classification in Remote Images;Enhanced Line Local Binary Patterns (EL-LBP): An Efficient Image Representation for Face Recognition;Single Sample Face Recognition by Sparse Recovery of Deep-Learned LDA Features;recursive Chaining of Reversible Image-to-Image Translators for Face Aging;automatically Selecting the Best Pictures for an Individualized Child Photo Album;face Detection in Painting Using Deep Convolutional Neural Networks;robust Geodesic Skeleton Estimation from Body Single Depth;person Re-Identification with a Body Orientation-Specific Convolutional Neural Network;person Re-identification Using Group Context.
Cloud computing builds on the latest achievements of diverse research areas, such as Grid computing, Service-oriented computing, business processes and virtualization. Managing such heterogeneous environments requires...
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Cloud computing builds on the latest achievements of diverse research areas, such as Grid computing, Service-oriented computing, business processes and virtualization. Managing such heterogeneous environments requires sophisticated interoperation of adaptive coordinating components. In this paper we introduce an SLA-aware Service Virtualization architecture that provides non-functional guarantees in the form of Service Level Agreements and consists of a three-layered infrastructure including agreement negotiation, service brokering and on demand deployment. In order to avoid costly SLA violations, flexible and adaptive SLA attainment strategies are used with a failure propagation approach. We demonstrate the advantages of our proposed solution with a biochemical case study in a Cloud simulation environment.
We propose a lightweight and adaptive distributed compressed sensing (DCS) with multi-sensor collaboration based on multiagent deep reinforcement learning (LADICS-MARL). To efficiently acquire data generated by sensor...
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ISBN:
(纸本)9781665404242
We propose a lightweight and adaptive distributed compressed sensing (DCS) with multi-sensor collaboration based on multiagent deep reinforcement learning (LADICS-MARL). To efficiently acquire data generated by sensor nodes deployed over a wide area and for long periods, we previously proposed a lightweight and adaptive compressed sensing method based on deep learning for edge devices, called LACSLE that changes the compression ratio in real-time according to the data between one sender and one receiver using pre-trained deep learning model. LADICS-MARL is an extension for multiple senders and one receiver and supports DCS through which multiple compressed data are simultaneously reconstructed. Multiple sensor nodes cooperate based on multiagent reinforcement learning to estimate the optimal compression ratio for all senders according to each corresponding data, as well as the transmitted compressed data from other sensor nodes. In addition, a gateway optimizes the combination of groups where some compressed data are reconstructed simultaneously. A performance evaluation using acceleration data from multiple sensor terminals acquired on a bridge suggests that the multiagent-based LADICS-MARL can reconstruct original data from less compressed data compared to the single-agent-based LACSLE under the threshold of reconstruct error.
distributed software transactional memory is an emerging, alternative concurrency control model for distributedsystems promising to alleviate the difficulties of lock-based distributed synchronization. We consider th...
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ISBN:
(纸本)9783642400476
distributed software transactional memory is an emerging, alternative concurrency control model for distributedsystems promising to alleviate the difficulties of lock-based distributed synchronization. We consider the multi-versioning (MV) model to avoid unnecessary aborts. MV schemes inherently guarantee commits of read-only transactions, but limit the concurrency of write transactions. In this paper we propose CRF (Commutative Requests First), a new scheduler tailored for enhancing concurrency of write transactions. CRF relies on the notion of commutative transactions, namely conflicting transactions that leave the state of the shared data-set consistent even if validated and committed concurrently. CRF is responsible to detect conflicts among commutative and non-commutative write transactions and then schedules them according to the execution state. We assess the goodness of the approach by an extensive evaluation of a fully implementation of CRF. the tests reveal that CRF improves throughput over a state-of-the-art DTM solution.
this book constitutes revised selected papers from the workshops held at the 28thinternational European conference on parallel and distributedcomputing, Euro-Par 2022, which took place in Glasgow, UK, in A...
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ISBN:
(数字)9783031312090
ISBN:
(纸本)9783031312083
this book constitutes revised selected papers from the workshops held at the 28thinternational European conference on parallel and distributedcomputing, Euro-Par 2022, which took place in Glasgow, UK, in August 22–26, 2022;Out of a total of 35 submissions 24 papers have been accepted, 19 of these are included in this book.;they stem from the following workshops:;- Workshop on Algorithms, Models and Tools for parallelcomputing on Heterogeneous Platforms (HeteroPar);- Workshop on Asynchronous Many-Task systems for Exascale (AMTE);- Workshop on Domain Specific Languages for High-Performance computing (DSL-HPC);- Workshop on distributed and Heterogeneous Programming in C and C++ (DHPCC++);- Workshop on Resiliency in High Performance computing in Clouds, Grids, and Clusters (Resilience);In addition, the proceedings alsocontains 6 extended abstracts from the PhD Symposium.
We consider a distributed stream processing application, expressed as a data-flow graph with operators as vertices connected by streams and deployed over a cluster of compute nodes, where a small subset of the operato...
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