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EGAGP: An enhanced genetic algorithm for producing efficient graph partitions 4

EGAGP: An enhanced genetic algorithm for producing efficient...

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4th international conference on Networking, Systems and Security, NSysS 2017

作者： Shahriar, Fahim Nesar, Aakib Bin Mahbub, Naweed Mohammad Shatabda, Swakkhar Department of Computer Science and Engineering United International University House 80 Road 8A Satmasjid Road Dhanmondi Dhaka1209 Bangladesh

ISBN: (纸本)9781509032600

Graph partitioning is a well-known problem which has varied applications such as scientific computing, distributed computing, social network analysis, task scheduling in multi-processor systems, data mining, cloud computing and many other domains. In this paper, we propose EGAGP, an enhanced genetic algorithm for producing efficient graph partitions. Keeping real world applications in mind, our algorithm takes into account the capacity limitations of individual partitions to ensure balanced partitioning. this approach enables a large variety of applications for this algorithm, the most significant of which is in mobile cloud computing. Our algorithm can be used in efficient deployment of software components in cloud architecture as it is efficient and fast and it also ensures feasibility by only allowing partition sizes up to designated limits. We have achieved significant improvement over the previous state-of-the-art methods in terms of runtime and objective of graph partitioning cost. Our method is based on dividing the total execution time among primary and secondary populations and it resulted in an efficient algorithm. Several standard benchmark graph instances were used in our work to compare the performance of the algorithm. Our proposed method EGAGP is able to produce feasible and good quality results and outperforms the state-of-the-art methods in terms of time and quality of the solutions generated. © 2017 IEEE.

关键词： Mobile cloud computing

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Runtime Data Layout Scheduling for Machine Learning Dataset 46

Runtime Data Layout Scheduling for Machine Learning Dataset

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46th international conference on parallel Processing Workshops (ICPPW)

作者： You, Yang Demmel, James Univ Calif Berkeley Div Comp Sci Berkeley CA 94720 USA

ISBN: (纸本)9781538610428

Machine Learning (ML) approaches are widely-used classification/regression methods for data mining applications. However, the time-consuming training process greatly limits the efficiency of ML approaches. We use the example of SVM (traditional ML algorithm) and DNN (state-of-the-art ML algorithm) to illustrate the idea in this paper. For SVM, a major performance bottleneck of current tools is that they use a unified data storage format because the data formats can have a significant influence on the complexity of storage and computation, memory bandwidth, and the efficiency of parallel processing. To address the problem above, we study the factors influencing the algorithm's performance and conduct auto-tuning to speed up SVM training. DNN training is even slower than SVM. For example, using a 8-core CPUs to train AlexNet model by CIFAR-10 dataset costs 8.2 hours. CIFAR-10 is only 170 MB, which is not efficient for distributed processing. Moreover, due to the algorithm limitation, only a small batch of data can be processed at each iteration. We focus on finding the right algorithmic parameters and using auto-tuning techniques to make the algorithm run faster. For SVM training, our implementation achieves 1.7-16.3x speedup (6.8x on average) against the non-adaptive case (using the worst data format) for various datasets. For DNN training on CIFAR-10 dataset, we reduce the time from 8.2 hours to only roughly 1 minute. We use the benchmark of dollars per speedup to help the users to select the right deep learning hardware.

关键词： parallel auto-tuning machine learning

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Combinatorial Modeling Approach to Find Rational Ways of Energy Development with Regard to Energy Security Requirements 6th

Combinatorial Modeling Approach to Find Rational Ways of Ene...

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6th international conference on Numerical Analysis and applications (NAA)

作者： Edelev, Alexey Sidorov, Ivan RAS ESI SB Lermonotva Str 130 Irkutsk Russia RAS ISDCT SB Lermonotva Str 134 Irkutsk Russia

ISBN: (纸本)9783319570990;9783319570983

this paper describes the model, methods and tools to find rational ways of the energy development with regard to energy security requirements. As known, energy security is directly related to the uninterrupted energy supply. It is important to choose rational ways of the energy development with ensuring energy security in the future. A number of the specific external condition combinations of energy sector operation and development taking into account uncertainties and other factors leads to a huge possible energy sector states set. therefore it cannot be processed in reasonable time. To overcome this issue an approach of combinatorial modeling is applied to manage the growing size of the energy sector states set.

关键词： Energy security Combinatorial modeling distributed computing

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A parallel and Resilient Frontend for High Performance Validation Suites 12th

A Parallel and Resilient Frontend for High Performance Valid...

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12th international conference on High-Performance computing for Computational Science (VECPAR)

作者： Adam, Julien Perache, Marc Paratools SAS Bruyeres Le Chatel France CEA DAM DIF F-91297 Arpajon France

ISBN: (纸本)9783319619828;9783319619811

In any well-structured software project, a necessary step consists in validating results relatively to functional expectations. However, in the high-performance computing (HPC) context, this process can become cumbersome due to specific constraints such as scalability and/or specific job launchers. In this paper we present an original validation front-end taking advantage of HPC resources for HPC workloads. By adding an abstraction level between users and the batch manager, our tool JCHRONOSS, drastically reduces test-suite running time, while taking advantage of distributed resources available to HPC developers. We will first introduce validation work-flow challenges before presenting the architecture of our tool and its contribution to HPC validation suites. Eventually, we present results from real test-cases, demonstrating effective speed-up up to 25x compared to sequential validation time paving the way to more thorough validation of HPC applications.

关键词： Validation Test-suite HPC Scheduling Fault-tolerance parallel Software quality

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Agent-based shop floor schseduling 8th

Agent-based shop floor schseduling

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8th international conference on Industrial applications of Holonic and Multi-Agent Systems, HoloMAS 2017

作者： Klima, Martin Gregor, Jan Harcuba, Ondrej Marik, Vladimir CertiCon a.s. Prague Czech Republic

ISBN: (纸本)9783319646343

Shop floor scheduling problem is known for a long time and is considered an academic exercise for solving by constraint solvers or for linear solvers. In a small production scale it can be solved easily. For a large scale production, the problem becomes too large and we need major heuristics to solve it. We introduce a way to decompose the major problem into smaller sub-problems and to quickly find a satisfying solution using human thinking inspired heuristics. the results combines scalable agent based solution and multiple constraint solver instances running in parallel. © Springer international Publishing AG 2017.

关键词： distributed computer systems

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Incorporation of probabilistic solar irradiance and normally distributed load for the assesment of ATC 8

Incorporation of probabilistic solar irradiance and normally...

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8th international conference on computing, Communication and Networking technologies (ICCCNT)

作者： Kumar, Arpit Bag, Baidyanath NIT Kurukshetra Dept Elect Engn Kurukshetra Haryana India

ISBN: (纸本)9781509030385

In deregulated electricity market determination of available transfer capability (ATC) in advance becomes necessary to use whole existing transmission network efficiently and economically. this work considers optimal power flow (OPF) based method to estimate ATC when probabilistic solar power is injected into the system as active power source. Novel voltage sensitivity indices are considered for the optimal placement of solar power generation into the transmission network. Probabilistic demand is incorporated by considering load variations as normally distributed random variables. Monte Carlo sampling (MCS) and Latin Hypercube sampling (LHS) techniques are considered to extract samples from the normally distributed load samples. Simulation result shows a significant reduction in ATC values occur when probabilistic load is taken into account, as compare to the steady load.

关键词： Available Transfer Capability (ATC) Beta Probability distributed Function (PDT) Latin Hypercube sampling Optimal Power Flow (OPT) Solar irradiance modelling Probabilistic load IEEE 24 RTS

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An Embedded Agent-Based Intelligent Industrial Wireless Sensor Network 8th

An Embedded Agent-Based Intelligent Industrial Wireless Sens...

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8th international conference on Industrial applications of Holonic and Multi-Agent Systems (HoloMAS)

作者： Taboun, Mohammed S. Brennan, Robert W. Univ Calgary Calgary AB Canada

ISBN: (纸本)9783319646350;9783319646343

Advances in cyber-physical systems and the introduction of Industry 4.0 have opened the door for interconnectivity in the industrial automation paradigm. One of the emerging technologies proven to be useful in factory automation is wireless sensor networks. In dynamic situations, wireless sensor networks need to be able to self-reconfigure while maintaining data integrity and efficiency. One solution popular with researchers is the use of multi-agent systems to manage wireless sensor networks. Typically, software agents are located on a server or cloud environment. Recent advances in microcomputers have made it feasible to embed these agents on the devices they control. this requires new reconfiguration and network management protocols. In this paper, an embedded agent architecture for wireless sensor network is proposed and an application specific example is given for an oil and gas refinery. An experiment is also conducted to investigate the effect of cluster sizes and signal frequency on the ratio of lost signals in a wireless sensor network cluster.

关键词： Embedded multi-agent systems Wireless sensor networks distributed intelligent control

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20th international conference on Advanced Computer System, ACS 2016

20th International Conference on Advanced Computer System, A...

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20th international conference on Advanced Computer System, ACS 2016

ISBN: (纸本)9783319484280

the proceedings contain 32 papers. the special focus in this conference is on Artificial Intelligence, Multimedia Systems and Software technologies. the topics include: On Fuzzy RDM-arithmetic;hidden Markov models with affix based observation in the field of syntactic analysis;an experiment on numeric, linguistic and color coded rating scale comparison;comparison of RDM complex interval arithmetic and rectangular complex arithmetic;homogeneous ensemble selection - experimental studies;deterministic method for the prediction of time series;a study on directionality in the Ulam square with the use of the Hough transform;real-time system of delivering water-capsule for firefighting;subject-specific methodology in the frequency scanning phase of SSVEP-based BCI;S-boxes cryptographic properties from a statistical angle;data scheme conversion proposal for information security monitoring systems;non-standard certification models for pairing based cryptography;the use of the objective digital image quality assessment criterion indication to create panoramic photographs;accuracy of high-end and self-build eye-tracking systems;mouth features extraction for emotion analysis;parallel facial recognition system based on 2DHMM;system of acoustic assistance in spatial orientation for the blind;performance and energy efficiency in distributed computing;the approach to web services composition;loop nest tiling for image processing and communication applications;the method of evaluating the usability of the website based on logs and user preferences and ontology-based approaches to big data analytics.

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An Efficient parallel Optimization for Co-Authorship Network Analysis

An Efficient Parallel Optimization for Co-Authorship Network...

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IEEE international conference on parallel and distributed computing, applications and technologies (PDCAT)

作者： C.R. Valencio J.C. Freitas R.C.G. de Souza L.A. Neves G.F.D. Zafalon W. Tenorio A.C. Colombini Institute of Biosciences Humanities and Exact Sciences (Ibilce) SP Brazil Federal University of São Carlos (UFSCAR) São Carlos SP Brazil Federal University of São Carlos SP Brazil

Co-authorship analysis in science and technology partnerships provides a vision of cooperation patterns between individuals and organizations and is still widely used to understand and assess scientific collaboration patterns. this analysis is conducted by means of bibliometry, which is the quantitative study of scientific production. However, with the evolution of database management systems, there was a significant increase in the volume of stored data, which could difficult the analysis. In this context, the developed work presents an efficient parallel optimization of bibliometric information, in order to allow this scientific analysis in a Big Data environment. Our results show that the time taken to calculate the transitivity value using the sequential approach grows 4.08 times faster than the parallel proposed approach when the number of nodes tends to infinity; the time taken to calculate the average distance and diameter values using the sequential approach grows 5.27 times faster than the parallel proposed approach when the number of nodes tends to infinity. Also, the results found present good values of speed up and efficiency.

关键词： Collaboration Databases Bibliometrics Production Big Data Measurement Data mining

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the 8th international Workshop on Information Quality and Quality of Service for Pervasive computing 2017 - welcome and committees

The 8th International Workshop on Information Quality and Qu...

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IEEE Annual conference on Pervasive computing and Communications Workshops (PerCom)

Pervasive computing provides an exciting paradigm for supporting anywhere anytime services, and is built on the tremendous advances made in a broad spectrum of technologies including wireless communication, wireless and sensor networking, mobile and distributed computing, as well as signal and information processing. Pervasive computing enables computers to interact with the real world in a ubiquitous and natural manner. the objective of the 8th IEEE PerCom international Workshop on Information Quality and Quality of Service for Pervasive computing (IQ2S 2017) is to provide a forum to exchange ideas, present results, share experience, and enhance collaborations among researchers, professionals, and application developers in various aspects of Quality of Information, Quality of Experience, and Quality of Service for pervasive computing in network contexts including wireless, mobile and sensor networks.

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