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检索条件"任意字段=12th Euromicro Conference on Parallel, Distributed and Network-Based Processing"

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Graph Database based Knowledge Graph Storage and Query for Power Equipment Management 12

Graph Database Based Knowledge Graph Storage and Query for P...

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12th IEEE PES Asia-Pacific Power and Energy Engineering conference, APPEEC 2020

作者： Tang, Yachen Liu, Tingting He, Ming Wang, Qiang Zhang, Huamin Liu, Guangyi Dai, Renchang Geiri North America San JoseCA United States State Grid Sichuan Electric Power Company Chengdu Sichuan China

ISBN: (纸本)9781728157481

the knowledge graph is a graph-based data structure that mines the value of data from a large number of associations. therefore, it is necessary to find a database that can support the expression, storage, and query of associated data as a way of storing knowledge graph. Different than the normally used relational database and RDF tabular storage, the graph database stores data in 'vertex' and 'edge' as basic storage units, which can realize distributed storage and parallel processing of massive data with complex associations. the graph database utilizes the characteristics of physical 'pointing' between nodes to provide 'no index' association operations for adjacent nodes and has technical advantages in applications of network-structured data. this paper proposes a knowledge graph storage and query method based on the graph database, and compares the storage and query performance between the general storage format of RDF and graph database based on a constructed power equipment management knowledge graph. © 2020 IEEE.

关键词： Graph Databases

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Performance Meets Programmabilty: Enabling Native Python MPI Tasks In PyCOMPSs

Performance Meets Programmabilty: Enabling Native Python MPI...

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euromicro conference on parallel, distributed and network-based processing

作者： Hatem Elshazly Francesc Lordan Jorge Ejarque Rosa M. Badia Department of Computer Sciences Barcelona Supercomputing Center (BSC) Barcelona Spain

ISBN: (数字)9781728165820

ISBN: (纸本)9781728165837

the increasing complexity of modern and future computing systems makes it challenging to develop applications that aim for maximum performance. Hybrid parallel programming models offer new ways to exploit the capabilities of the underlying infrastructure. However, the performance gain is sometimes accompanied by increased programming complexity. We introduce an extension to PyCOMPSs, a high-level task-based parallel programming model for Python applications, to support tasks that use MPI natively as part of the task model. Without compromising application's programmability, using Native MPI tasks in PyCOMPSs offers up to 3x improvement in total performance for compute intensive applications and up to 1.9x improvement in total performance for I/O intensive applications over sequential implementation of the tasks.

关键词： Task analysis parallel processing Python Computational modeling Runtime parallel programming

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Target Localization based on Arbitrary Angle Bounding Box for Remote Sensing Image 12

Target Localization Based on Arbitrary Angle Bounding Box fo...

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12th International conference on Digital Image processing (ICDIP)

作者： Li, Yinhua Wan, Shouhong Jin, Peiquan Li, Xingyue Univ Sci & Technol China Sch Comp Sci & Technol Huangshan St Hefei 230027 Peoples R China Chinese Acad Sci Key Lab Electromagnet Space Informat Hefei 230027 Peoples R China

ISBN: (纸本)9781510638464

State-of-the-art object detection networks have reduced the running time and get better detection results. However, for remote sensing image scenes, in a certain projection direction, the remote sensing image target will be tilted, the positioning of the horizontal bounding box used by the exit detection algorithm will cause a lot of overlap between the target bounding boxes, after using NMS (Non-maximum suppression), it will lead to the lost of the target. In this paper, we propose a Rotated Faster R-CNN(R-FRCNN) that is a target positioning method based on arbitrary angle bounding box, which can perform non-redundant positioning on the target, thus can reduce the rate of missed detection when the target is densely distributed or the angle of the object is arbitrary. Compared with traditional and state-of-the art object detection algorithms, our approach obtain the superior performance.

关键词： Arbitrary angle bounding box target localization anchor box design remote sensing image

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Recursive Task Generation for Scalable SDF Graph Execution on Multicore Processors

Recursive Task Generation for Scalable SDF Graph Execution o...

引用

euromicro conference on parallel, distributed and network-based processing

作者： Georgios Georgakarakos Johan Lilius Faculty of Science and Engineering Åbo Akademi University Turku Finland

ISBN: (数字)9781728165820

ISBN: (纸本)9781728165837

Dataflow modelling is a popular technique for describing parallel algorithms. Using dataflow, algorithm parallelism can be modelled and analysed efficiently at a high level of abstraction. However, challenges arise when translating dataflow semantics into executable code, mainly due to scheduling and synchronization overheads. Invoking task programming models in order to generate efficient code from dataflow representations has been proposed as a promising methodology to optimise the translation *** this paper, we propose recursive task execution as an optimisation for the dataflow-based code generation process. Our approach is based on extracting synchronous dataflow graph information in order to reduce scheduling overheads and improve load balancing when executing task-based code on multicore processors. We use PREESM dataflow-based prototyping framework to implement and test our concept. Results show that our proposed optimisation enhances code scalability therefore enabling higher application throughput.

关键词： Task analysis Multicore processing Programming Binary trees parallel processing Runtime Synchronization

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RSMCC: Enabling Ring-based Software Managed Cache-Coherent Embedded SoCs

RSMCC: Enabling Ring-based Software Managed Cache-Coherent E...

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euromicro conference on parallel, distributed and network-based processing

作者： Georgios Kornaros Electrical and Computer Engineering Department Hellenic Mediterranean University Heraklion Crete Greece

ISBN: (数字)9781728165820

ISBN: (纸本)9781728165837

Modern embedded heterogeneous Systems-on-Chip (SoCs) integrate differentiated memory hierarchy which require the programmer to undertake mostly simple, software-driven coherence protocols to optimize data-parallel applications. this paper presents a hybrid ring-based cache coherent multi-core architecture and a framework to develop memory hierarchy protocols customized to system constraints and workload needs. the ring protocol is developed in software over a typical mesh network-on-Chip (NoC) which is used to convey cache coherent messages. Management and system monitoring operations utilize the NoC hardware routing protocol to achieve speed and minimize software interference and overheads. the software cache coherent management protocol lays on top of a typical shared memory programming model and facilitates easy user-level control and integration with user application, while removing concerns for data allocation for scratchpad-based systems.

关键词： Protocols Coherence Software Hardware Memory management System-on-chip Multicore processing

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A Hybrid Model for Anomaly-based Intrusion Detection System 15th

A Hybrid Model for Anomaly-Based Intrusion Detection System

引用

15th International conference on Intelligent Information Hiding and Multimedia Signal processing, IIH-MSP 2019, held in conjunction with the 12th International conference on Frontiers of Information Technology, Applications and Tools, FITAT 2019

作者： Ugtakhbayar, N. Usukhbayar, B. Baigaltugs, S. National University of Mongolia Ulaanbaatar Mongolia Mongolian University of Science and Technology Ulaanbaatar Mongolia

ISBN: (纸本)9789811397097

Anomaly-based systems have become critical to the fields of information technology. Since last few years, evolution of anomaly-based intrusion detection system (IDS), improving detection accuracy, and training data preprocessing have been getting specifically important to the researchers of this field. In previous years, a lot have been discussed on the problems in using anomaly-based and hybrid IDSs. Anomaly-based approach is comparatively efficient from signature-based in novel attacks on computer network. However, in some cases, signature-based system is quick in identifying attacks from anomaly systems. In this work, authors have applied preprocessing in KDD 99 and have collected dataset using information gain. Authors have named collected dataset NUM15 as some of the features and redundant data are beside the point which decreases processing time and performance of IDS. After that, naive Bayes and Snort are used to classify the compression results and training the machine in parallel model. this hybrid model combines anomaly and signature detection that can accomplish detection of network anomaly. the results show that the proposed hybrid model can increase the accuracy and can detect novel intrusions. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Intrusion detection

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Scalable Teacher-Forcing networks under Spark Environments for Large-Scale Streaming Problems 12

Scalable Teacher-Forcing Networks under Spark Environments f...

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12th IEEE International conference on Evolving and Adaptive Intelligent Systems (IEEE EAIS)

作者： Za'in, Choiru Ashfahani, Andri Pratama, Mahardhika Lughofer, Edwin Pardede, Eric La Trobe Univ Dept Comp Sci & IT Melbourne Vic Australia Nanyang Technol Univ Sch Comp Sci & Engn Singapore Singapore Johannes Kepler Univ Linz Dept Knowledge Based Math Syst Linz Austria

ISBN: (纸本)9781728143842

Large-scale data streams remains an open issue in the existing literature. It features a never ending information flow, mostly going beyond the capacity of a single processing node. Nonetheless, algorithmic development of large-scale streaming algorithms under distributed platforms faces major challenge due to the scalability issue. the network complexity exponentially grows with the increase of data batches, leading to an accuracy loss if the model fusion phase is not properly designed. A large-scale streaming algorithm, namely Scalable Teacher Forcing network (ScatterNet), is proposed here. ScatterNet has an elastic structure to handle the concept drift in the local scale within the data batch or in the global scale across batches. It is built upon the teacher forcing concept providing a short-term memory aptitude. ScatterNet features the data-free model fusion approach which consists of the zero-shot merging mechanism and the online model selection. Our numerical study demonstrates the moderate improvement of prediction accuracy by ScatterNet while gaining competitive advantage in terms of the execution time compared to its counterpart.

关键词： Large-scale data stream analytics Spark distributed Learning Lifelong learning

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Implementation and Optimization of a 1D2V PIC Method for Nonlinear Kinetic Models on GPUs

Implementation and Optimization of a 1D2V PIC Method for Non...

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euromicro conference on parallel, distributed and network-based processing

作者： Matthias Korch Philipp Raithel Tim Werner Department of Computer Science University of Bayreuth Bayreuth Germany

ISBN: (数字)9781728165820

ISBN: (纸本)9781728165837

this paper considers the parallel numerical simulation of the time evolution of galaxies and globular clusters on GPUs. the model used is the Einstein-Vlasov system, which is designed, in particular, to study the formation of black holes and spacetime singularities in a general relativistic ***, a reference implementation is derived using NVIDIA CUDA as programming model, which is then optimized in several steps. Bottlenecks are identified by profiling, and different approaches, namely particle sort, improved treatment of atomic operations, and kernel fusion are investigated to overcome these bottlenecks. Each optimized variant is evaluated in relation to the other variants using detailed runtime experiments and profiling results. Using in the order of 10 7 to 10 8 particles, speedups between 1.84 and 2.38 w.r.t. the reference implementation have been observed.

关键词： Graphics processing units Kernel Mathematical model Numerical models Computational modeling Measurement Arrays

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Performance study of HPC applications on an Arm-based cluster using a generic efficiency model

Performance study of HPC applications on an Arm-based cluste...

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euromicro conference on parallel, distributed and network-based processing

作者： Fabio Banchelli Kilian Peiro Andrea Querol Guillem Ramirez-Gargallo Guillem Ramirez-Miranda Joan Vinyals Pablo Vizcaino Marta Garcia-Gasulla Filippo Mantovani Barcelona Supercomputing Center

ISBN: (数字)9781728165820

ISBN: (纸本)9781728165837

HPC systems and parallel applications are increasing their complexity. therefore the possibility of easily study and project at large scale the performance of scientific applications is of paramount importance. In this paper we describe a performance analysis method and we apply it to four complex HPC applications. We perform our study on a pre-production HPC system powered by the latest Arm-based CPUs for HPC, the Marvell thunderX2. For each application we spot inefficiencies and factors that limit their scalability. the results show that in several cases the bottlenecks do not come from the hardware but from the way applications are programmed or the way the system software is configured.

关键词： Measurement Performance analysis Tools Scalability Hardware Computer architecture Libraries

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TLB-based Block-Grain Classification of Private Data

TLB-based Block-Grain Classification of Private Data

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euromicro conference on parallel, distributed and network-based processing

作者： Bhargavi R. Upadhyay Alberto Ros N.S. Murty Bengaluru Amrita Vishwa Vidyapeetham INDIA Universidad de Murcia Murcia Spain Amrita Vishwa Vidyapeetham Bengaluru INDIA

ISBN: (数字)9781728165820

ISBN: (纸本)9781728165837

Sequential and parallel applications use most of the data as private in a multi-core system. Recent proposals made use of this observation to reduce the area of the coherence directories or the memory access latency. the driving force of these proposals is the classification of private/shared memory data. the effectiveness of these proposals depends on the number of detected private data. the existing proposals perform the private/shared classification at page granularity, leading to a noticeable amount of miss-classified memory blocks. We propose a mechanism that works on block granularity using the translation lookaside buffer (TLB) to make accurate detection of private data, which increases the effectiveness of proposals relying on a private/shared classification. Simulation results show that the block-grain approach obtains 17.0% more accessed private miss data than the page-grain approach, which translates to an improvement in system performance by 6.02% compared to a page-grain approach.

关键词： Coherence Protocols Proposals Optimization Hardware System performance distributed databases

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