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Algorithms and Architectures for Parallel Processing: 19th International Conference, ICA3PP 2019, Melbourne, VIC, Australia, December 9–11, 2019, Proceedings, Part II de Sheng Wen

Algorithms and Architectures for Parallel Processing: 19th International Conference, ICA3PP 2019, Melbourne, VIC, Australia, December 9–11, 2019, Proceedings, Part II: Lecture Notes in Computer Science, cartea 11945

Editat de Sheng Wen, Albert Zomaya, Laurence T. Yang
en Limba Engleză Paperback – 22 ian 2020
The two-volume set LNCS 11944-11945 constitutes the proceedings of the 19th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2019, held in Melbourne, Australia, in December 2019. The 73 full and 29 short papers presented were carefully reviewed and selected from 251 submissions. The papers are organized in topical sections on: Parallel and Distributed Architectures, Software Systems and Programming Models, Distributed and Parallel and Network-based Computing, Big Data and its Applications, Distributed and Parallel Algorithms, Applications of Distributed and Parallel Computing, Service Dependability and Security, IoT and CPS Computing, Performance Modelling and Evaluation.
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Specificații

ISBN-13: 9783030389604
ISBN-10: 303038960X
Pagini: 699
Ilustrații: XXI, 699 p. 297 illus., 245 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 1 kg
Ediția:1st ed. 2020
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Theoretical Computer Science and General Issues

Locul publicării:Cham, Switzerland

Cuprins

PPS: A Low-Latency and Low-Complexity switching architecture based on packet prefetch and arbitration prediction.- SWR: Using Windowed Reordering to Achieve Fast and Balanced Heuristic for Streaming Vertex-Cut Graph Partitioning.- Flexible Data Flow Architecture for Embedded Hardware Accelerators.- HBL-Sketch: a New Three-tier Sketch for Accurate Network Measurement.- Accelerating Large Integer Multiplication Using Intel AVX-512IFMA.- A Communication-Avoiding Algorithm for Molecular Dynamics Simulation.- Out-of-Core GPU-Accelerated Causal Structure Learning.- Accelerating Lattice Boltzmann Method by Fully Exposing Vectorizable Loops.- A Solution for High Availability Memory Access.- Verication of Microservices Using Metamorphic Testing.- 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.- Distributed & Parallel & Network-based Computing Impromptu Rendezvous Based Multi-Threaded Algorithm for Shortest Lagrangian Path Problem on Road Networks.- FANG: Fast and E cient 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.- Multitask Assignment Algorithm Based on Decision Tree in Spatial Crowdsourcing Environment.- TIMOM: a novel time in uence 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 Veri able 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.- Applications of Distributed & Parallel Computing.- An Open Identity Authentication Scheme Based on Blockchain.- RBAC-GLA role-based access control gasless architecture of consortium blockchain.- Developing Patrol Strategies for the Cooperative Opportunistic Criminals.- Deep Learning vs. Traditional Probabilistic Models: Case Study on Short Inputs for Password Guessing.