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A Knowledge Graph-Based Deep Learning Framework for Efficient Content Similarity Search of Sustainable Development Goals Data

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Data Intelligence 2023年第3期5卷 663-684页

作者： Irene Kilanioti George A.Papadopoulos School of Electrical and Computer Engineering National Technical University of Athens9 Heroon Polytechneiou St.Zografou Campus Athens15780Greece Department of Computer Science University of Cyprus1 University AvenueAglantziaCY-2109NicosiaCyprus

Sustainable development denotes the enhancement ofliving standards in the present without compromising future generations'*** Development Goals(SDGs)quantify the accomplishment of sustainable development and pave the way for a world worth living in for future *** can contribute to the achievement of the SDGs by guiding the actions of practitioners based on the analysis of SDG data,as intended by this *** propose a framework of algorithms based on dimensionality reduction methods with the use of Hilbert Space Filling Curves(HSFCs)in order to semantically cluster new uncategorised SDG data and novel indicators,and efficiently place them in the environment of a distributed knowledge graph ***,a framework of algorithms for insertion of new indicators and projection on the HSFC curve based on their transformer-based similarity assessment,for retrieval of indicators and loadbalancing along with an approach for data classification of entrant-indicators is ***,a thorough case study in a distributed knowledge graph environment experimentally evaluates our *** results are presented and discussed in light of theory along with the actual impact that can have for practitioners analysing SDG data,including intergovernmental organizations,government agencies and social welfare *** approach empowers SDG knowledge graphs for causal analysis,inference,and manifold interpretations of the societal implications of SDG-related actions,as data are accessed in reduced retrieval *** facilitates quicker measurement of influence of users and communities on specific goals and serves for faster distributed knowledge matching,as semantic cohesion of data is preserved.

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A MVCC Approach to parallelizing Interoperability of Consortium Blockchain 22nd

A MVCC Approach to Parallelizing Interoperability of Consort...

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22nd international conference on parallel and distributed computing, applications and technologies (PDCAT 2021)

作者： Lin, Weiyi Qu, Qiang Ning, Li Fan, Jianping Jiang, Qingshan Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Huawei Cloud Blockchain Lab Shenzhen Peoples R China

ISBN: (纸本)9783030967727;9783030967710

Driven in part of the rapid growth of consortium blockchain applications, blockchain interoperability becomes extremely essential to exchange transactional data among decentralized applications. To ensure the data integrity of transactions, the state-of-the-art studies of the blockchain interoperability apply data locks, which however severely decrease system efficiency. To boost interoperability performance, this paper proposes a novel approach based on multi-version concurrency control to parallelize interoperable transactions, which aims high transaction processing throughput while ensuring data integrity. the experimental evaluation with the Smallbank benchmark shows that the proposed method achieves up to 4x performance increase (in terms of processed transactions per second, TPS) compared with the existing methods, and moreover, it decreases the average latency with 58%.

关键词： Blockchain interoperability MVCC Data parallel Transaction integrity

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A parallel Peak Extraction Algorithm Based on Computational Intensity Prediction Using a Machine Learning Model 10

A Parallel Peak Extraction Algorithm Based on Computational ...

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10th international conference on Agro-Geoinformatics, Agro-Geoinformatics 2022

作者： Lin, Liyang Gao, Fan Yue, Peng School of Remote Sensing and Information Engineering Wuhan University Hubei Wuhan China Hubei Wuhan China

ISBN: (数字)9781665470780

ISBN: (纸本)9781665470780

To improve the efficiency of geospatial big data analysis, parallel computing technologies have been widely used in the processing of geospatial data. It is necessary to balance the computational load on each processor during parallel computing. this often requires the prediction of the computational intensity (CI). the existing CI prediction researches are often based on prior knowledge and empirical formulas which requires manual setting and calibration of parameters. this paper discusses the way of model construction and parallelism for a raster algorithm, peak point extraction(PPE), based on the machine learning-based construction of a CI prediction model. the computational intensity of the spatial domain is predicted by a machine learning method, and the spatial domain is divided in balance to improve the parallel performance of the raster algorithm. three datasets are used to test the parallel effect. Under 24 processes, the speedup ratio achieved by our method ranges from 20.6 to 16.8, and the parallel efficiency is 0.8 to 0.7. While the speedup ratio achieved by the traditional parallel method ranges from 14.3 to 4.6, and the parallel efficiency is 0.6 to 0.2. the results demonstrate the effectiveness of the approach. © 2022 IEEE.

关键词： Extraction

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the Effect of a Face Wall on a Cellular Structure During Bending 10th

The Effect of a Face Wall on a Cellular Structure During Ben...

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10th EAI international conference on Mobility, IoT and Smart Cities, Mobility IoT 2023

作者： Monkova, Katarina Pavol Monka, Peter Korol, Martin Torok, Jozef Beno, Pavel TU Kosice Faculty of Manufacturing Technologies with a Seat in Presov Presov Slovakia TBU in Zlin Faculty of Technology Zlin Czech Republic TU Kosice Faculty of Manufacturing Technologies with a Seat in Presov Presov Slovakia Faculty of Technology Technical University in Zvolen Zvolen Slovakia

ISBN: (纸本)9783031565328

Industry 4.0 enabled great development in the field of technology, but it also brought with it new challenges not only in the field of digitization but also in the field of developing new materials. Scientists have realized that there are a large number of materials in nature that have good properties and are light at the same time. the chapter deals with the investigation of the influence of the front wall on the cell structure of the ‘Schwarz P’ type during bending. Porous specimens were designed in a 30% volume ratio with 10 × 10 × 10 mm unit cells distributed regularly in all three orthogonal axes. the total volume of the structure was 20 × 30 × 250 mm. they were made of plastic material PLA (polylactic acid) by FFF (fused filament fabrication) technology. Samples were made with one or two front walls in a sandwich manner, or without a wall. the three-point bending experimental test made it possible to record the dependence of the force load on the displacement. the measured data were processed and then the maximum bending stresses were calculated. the results clearly show the influence of the front wall, with the maximum stresses increasing with the number of walls, and this trend was best described by a second-order polynomial equation. © the Author(s).

关键词： Polynomials

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HPCCT 2022 - 2022 6th High Performance computing and Cluster technologies conference

HPCCT 2022 - 2022 6th High Performance Computing and Cluster...

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6th High Performance computing and Cluster technologies conference, HPCCT 2022

ISBN: (纸本)9781450396646

the proceedings contain 10 papers. the topics discussed include: massively parallel acceleration of unstructured DSMC computing;parallel simulation of the aerodynamic characteristics of a blunt cone in multiple flow regimes;management of an academic HPC & research computing facility: the ULHPC experience 2.0;parallel implementation and verification of implicit unified gas kinetic scheme;research on mesh partition algorithm of unstructured high-order method with complex reconstruction template;parallel implementation for dynamic mesh optimization on distributed computer system;development of an improved occluded person re-identification system using deep learning;compact update algorithm for numerical schemes with cross stencil for data access locality;topic tracking algorithm based on topic structure characteristics;and the use of the wearable system based on intelligent computer technology in taekwondo training.

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A method for modelling and executing customized pipelines in serverless computing

A method for modelling and executing customized pipelines in...

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2023 IEEE international conference on Bioinformatics and Biomedicine, BIBM 2023

作者： Cinaglia, Pietro Cannataro, Mario Magna Graecia University of Catanzaro Department of Health Sciences Italy Magna Graecia University of Catanzaro Data Analytics Research Center Department of Medical and Surgical Sciences Italy

ISBN: (纸本)9798350337488

Serverless computing is an emerging cloud service for executing distributed applications on cloud architecture. the possibility of performing functions without the need to manage any type of infrastructure has made this methodology particularly adopted in several fields, e.g., data processing and above all in parallel computing. the processing of large-scale genomic data needs many computational resources, resulting highly time-consuming. therefore, the need of higher computing capabilities has translated into the increasing use of this technology. In this paper, we present a method for modelling and executing customized pipelines in serverless computing. We applied this one to the transcript-level expression analysis of samples from RNA sequencing (RNA-seq), by focusing on the most computationally expensive step: the mapping of reads to a reference genome. Our method has been implemented as an Amazon Web Services (AWS) Lambda function, that is deployed within our own serverless architecture. the parallel instances invoked in AWS Lambda are with negligible latencies, being managed by the provider, therefore, the average computational time are similar among experiments on similar samples. We denoted a relevant advantage in running time, by measuring an improvement up to 79.84% and 90.10% on the concurrent analysis of 10 samples, compared to the local environments having the following specifications: CPU 3.8 GHz 8 vcores and CPU 3.8 GHz 16 vcores, respectively. © 2023 IEEE.

关键词： AWS bioinformatics parallel analysis pipeline serverless

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An Effective and Reliable Cross-Blockchain Data Migration Approach 22nd

An Effective and Reliable Cross-Blockchain Data Migration Ap...

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22nd international conference on parallel and distributed computing, applications and technologies (PDCAT 2021)

作者： Zhang, Mengqiu Qu, Qiang Ning, Li Fan, Jianping Yang, Ruijie Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Huawei Cloud Blockchain Lab Shenzhen Peoples R China

ISBN: (纸本)9783030967727;9783030967710

As blockchain is widely applied, various decentralized applications would inevitably encounter data migration problems, for reasons, such as the multilevel blockchain scenarios, the exhaustion of blockchain disk space and the swap of the rapidly evolving blockchain engines. In order to proceed the applications smoothly, it is necessary to migrate original blockchain data to a new blockchain instance, which is the cross-blockchain data migration. However, ensuring the reliability of data provenance and the data consistency, and balancing migration efficiency and historical state granularity, introduce unique challenges over cross-blockchain data migration. this paper proposes an effective and reliable cross-blockchain data migration approach to coping with these challenges. To ensure the reliability, a collective mechanism of controlling, executing and storing procedures is proposed to assort migration transactions between blockchains. Furthermore, we propose two migration schemes in order to adapt decentralized application scenarios. Extensive experiments are conducted to demonstrate the effectiveness of the proposed approach.

关键词： Blockchain Data migration Cross-blockchain distributed transactions Decentralized applications

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IMpart: A Partitioning-based parallel Approach to Accelerate Influence Maximization 29

IMpart: A Partitioning-based Parallel Approach to Accelerate...

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29th Annual IEEE international conference on High Performance computing, Data, and Analytics (HiPC)

作者： Barik, Reet Minutoli, Marco Halappanavar, Mahantesh Kalyanaraman, Ananth Washington State Univ Pullman WA 99164 USA Pacific Northwest Natl Lab Richland WA 99352 USA

ISBN: (纸本)9781665494236

Influence maximization (IM) is a fundamental operation among graph problems that involve simulating a stochastic diffusion process on real-world networks. Given a graph G(V, E), the objective is to identify a small set of key influential "seeds"i.e., a fixed-size set of k nodes, which when influenced is likely to lead to the maximum number of nodes in the network getting influenced. the problem has numerous applications including (but not limited to) viral marketing in social networks, epidemic control in contact networks, and in finding influential proteins in molecular networks. Despite its importance, application of influence maximization at scale continues to pose significant challenges. While the problem is NP-hard, efficient approximation algorithms that use greedy hill climbing are used in practice. However those algorithms consume hours of multithreaded execution time even on modest-sized inputs with hundreds of thousands of nodes. In this paper, we present IMpart, a partitioning-based approach to accelerate greedy hill climbing based IM approaches on both shared and distributed memory computers. In particular, we present two parallel algorithmsone that uses graph partitioning (IMpart-metis) and another that uses community-aware partitioning (IMpart-gratis)with provable guarantees on the quality of approximation. Experimental results show that our approaches are able to deliver two to three orders of magnitude speedup over a state-of-the-art multithreaded hill climbing implementation with negligible loss in quality. For instance, on one of the modest-sized inputs (Slashdot: 73K nodes;905K edges), our partitioning-based shared memory implementation yields 4610x speedup, reducing the runtime from 9h 36m to 7 seconds on 128 threads. Furthermore, our distributed memory implementation enhances problem size reach to graph inputs with x10(6) nodes and x10(8) edges and enables sub-minute computation of IM solutions.

关键词： community detection graph partitioning greedy hill climbing Influence maximization parallel seed selection

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A PGAS-Based Implementation for the parallel Minimum Spanning Tree Algorithm 13th

A PGAS-Based Implementation for the Parallel Minimum Spannin...

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13th international conference on Large-Scale ScientificComputations (LSSC)

作者： Bejanyan, Vahag Astsatryan, Hrachya Natl Acad Sci Republ Armenia Inst Informat & Automat Problems 1 Paruyr Sevak St Yerevan 0014 Armenia

ISBN: (纸本)9783030975494;9783030975487

the minimum spanning tree is a critical problem for many applications in network analysis, communication network design, and computer science. the parallel implementation of minimum spanning tree algorithms increases the simulation performance of large graph problems using high-performance computational resources. the minimum spanning tree algorithms generally use traditional parallel programming models for distributed and shared memory systems, like Massage Passing Interface or OpenMP. Furthermore, the partitioned global address space model offers new capabilities in the form of asynchronous computations on distributed shared memory, positively affecting the performance and scalability of the algorithms. the paper aims to present a new minimum spanning tree algorithm implemented in a partitioned global address space model. the experiments with diverse parameters have been conducted to study the efficiency of the asynchronous implementation of the algorithm.

关键词： Minimum spanning tree PGAS model parallel algorithms Large-scale graphs HPC

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Low Latency Execution Guarantee Under Uncertainty in Serverless Platforms 22nd

Low Latency Execution Guarantee Under Uncertainty in Serverl...

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22nd international conference on parallel and distributed computing, applications and technologies (PDCAT 2021)

作者： HoseinyFarahabady, M. Reza Taheri, Javid Zomaya, Albert Y. Tari, Zahir Univ Sydney Ctr Distributed & High Performance Comp Sch Comp Sci Sydney NSW Australia Karlstad Univ Dept Math & Comp Sci Karlstad Sweden RMIT Univ Sch Comp Technol Melbourne Vic Australia

ISBN: (纸本)9783030967727;9783030967710

Serverless computing recently emerged as a new run-time paradigm to disentangle the client from the burden of provisioning physical computing resources, leaving such difficulty on the service provider's side. However, an unsolved problem in such an environment is how to cope with the challenges of executing several co-running applications while fulfilling the requested Quality of Service (QoS) level requested by all application owners. In practice, developing an efficient mechanism to reach the requested performance level (such as p-99 latency and throughput) is limited to the awareness (resource availability, performance interference among consolidation workloads, etc.) of the controller about the dynamics of the underlying platforms. In this paper, we develop an adaptive feedback controller for coping with the buffer instability of serverless platforms when several collocated applications are run in a shared environment. the goal is to support a low-latency execution by managing the arrival event rate of each application when shared resource contention causes a significant throughput degradation among workloads with different priorities. the key component of the proposed architecture is a continues management of server-side internal buffers for each application to provide a low-latency feedback control mechanism based on the requested QoS level of each application (e.g., buffer information) and the worker nodes throughput. the empirical results confirm the response stability for high priority workloads when a dynamic condition is caused by low priority applications. We evaluate the performance of the proposed solution with respect to the response time and the QoS violation rate for high priority applications in a serverless platform with four worker nodes set up in our in-house virtualized cluster. We compare the proposed architecture against the default resource management policy in Apache OpenWhisk which is extensively used in commercial serverless platforms. th

关键词： Dynamic controller of computer systems Serverless computing Virtualized platforms Quality of Service (QoS)

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