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2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing最新文献

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Fault-Tolerant Global Load Balancing in X10 X10中的容错全局负载均衡
2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing Pub Date : 2014-09-01 DOI: 10.1109/SYNASC.2014.69
Marco Bungart, Claudia Fohry, Jonas Posner
{"title":"Fault-Tolerant Global Load Balancing in X10","authors":"Marco Bungart, Claudia Fohry, Jonas Posner","doi":"10.1109/SYNASC.2014.69","DOIUrl":"https://doi.org/10.1109/SYNASC.2014.69","url":null,"abstract":"Scalability postulates fault tolerance to be effective. We consider a user-level fault tolerance technique to cope with permanent node failures. It is supported by X10, one of the major Partitioned Global Address Space (PGAS) languages. In Resilient X10, an exception is thrown when a place (node) fails. This paper investigates task pools, which are often used by irregular applications to balance their load. We consider global load balancing with one worker per place. Each worker maintains a private task pool and supports cooperative work stealing. Tasks may generate new tasks dynamically, are free of side-effects, and their results are combined by reduction. Our first contribution is a task pool algorithm that can handle permanent place failures. It is based on snapshots that are regularly written to other workers and are updated in the event of stealing. Second, we implemented the algorithm in the Global Load Balancing framework GLB, which is part of the standard library of X10. We ran experiments with the Unbalanced Tree Search (UTS) and Between ness Centrality (BC) benchmarks. With 64 places on 4 nodes, for instance, we observed an overhead of about 4% for using fault-tolerant GLB instead of GLB. The protocol overhead for a place failure was neglectable.","PeriodicalId":150575,"journal":{"name":"2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130831303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Genetic Improvement of Programs 程序的遗传改良
2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing Pub Date : 2014-09-01 DOI: 10.1109/SYNASC.2014.10
W. Langdon
{"title":"Genetic Improvement of Programs","authors":"W. Langdon","doi":"10.1109/SYNASC.2014.10","DOIUrl":"https://doi.org/10.1109/SYNASC.2014.10","url":null,"abstract":"Genetic programming can optimise software, including: evolving test benchmarks, generating hyper-heuristics by searching meta-heuristics, generating communication protocols, composing telephony systems and web services, generating improved hashing and C++ heap managers, redundant programming and even automatic bug fixing. Particularly in embedded real-time or mobile systems, there may be many ways to trade off expenses (such as time, memory, energy, power consumption) vs. Functionality. Human programmers cannot try them all. Also the best multi-objective Pareto trade off may change with time, underlying hardware and network connection or user behaviour. It may be GP can automatically suggest different trade offs for each new market. Recent results include substantial speed up by evolving a new version of a program customised for a special case.","PeriodicalId":150575,"journal":{"name":"2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130620435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 34
Performance Improvements for the "Linear Nonadiabatic Nonradial Waves" Pulsational Model “线性非绝热非径向波”脉动模型的性能改进
2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing Pub Date : 2014-09-01 DOI: 10.1109/SYNASC.2014.71
Mihai Ovidiu Tirsa, E. Slusanschi, M. Suran
{"title":"Performance Improvements for the \"Linear Nonadiabatic Nonradial Waves\" Pulsational Model","authors":"Mihai Ovidiu Tirsa, E. Slusanschi, M. Suran","doi":"10.1109/SYNASC.2014.71","DOIUrl":"https://doi.org/10.1109/SYNASC.2014.71","url":null,"abstract":"Aster seismology is an emerging branch of astrophysics that studies the interior and global parameters of pulsating stars, based on their natural oscillation frequency. This work proposes different methods for increasing the performance of LNAWENR (Linear Non Adiabatic Non Radial WavEs), a computational intensive pulsational model that studies stars based on their seismic properties. As part of the aster seismological package ROMOSC, LNAWENR is one of the several non-adiabatic models in use now by the international astrophysics and space science community. The model was implemented to study data from NASA's CoRoT mission. The improved version aims to be used for NASA's KEPLER mission. In this context, we employed several serial and parallel code optimizations. The programming frameworks used for the parallel optimizations are Open MP and Open CL.","PeriodicalId":150575,"journal":{"name":"2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121623378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Using Domain Specific Hierarchical Good Practice for Ranking Service Compositions 使用特定领域的分层良好实践对服务组合进行排序
2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing Pub Date : 2014-09-01 DOI: 10.1109/SYNASC.2014.35
A. Marginean, I. A. Letia, S. Zaporojan
{"title":"Using Domain Specific Hierarchical Good Practice for Ranking Service Compositions","authors":"A. Marginean, I. A. Letia, S. Zaporojan","doi":"10.1109/SYNASC.2014.35","DOIUrl":"https://doi.org/10.1109/SYNASC.2014.35","url":null,"abstract":"We propose a method for ranking the service compositions according to the good practice of each domain. Knowledge about good practice is modeled in a hierarchical manner inspired from Hierarchical Task Networks. In describing the good practice knowledge we give a model for HTN in N3 notation and we enhanced it with an importance value. Each candidate service composition is checked against good practice in a model checking style. A candidate composition is a sequence of services. The candidate composition is compared to the constraints defined in good practice and is considered good if for each simple task the most important constraints are fulfilled.","PeriodicalId":150575,"journal":{"name":"2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116865306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
A Practical Approach on Cleaning-Up Large Data Sets 大型数据集清理的实用方法
2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing Pub Date : 2014-09-01 DOI: 10.1109/SYNASC.2014.45
Marius Barat, Dumitru-Bogdan Prelipcean, Dragos Gavrilut
{"title":"A Practical Approach on Cleaning-Up Large Data Sets","authors":"Marius Barat, Dumitru-Bogdan Prelipcean, Dragos Gavrilut","doi":"10.1109/SYNASC.2014.45","DOIUrl":"https://doi.org/10.1109/SYNASC.2014.45","url":null,"abstract":"In this paper we propose a noise detection system based on similarities between instances. Having a data set with instances that belongs to multiple classes, a noise instance denotes a wrongly classified record. The similarity between different labeled instances is determined computing distances between them using several metrics among the standard ones. In order to ensure that this approach is computational feasible for very large data sets, we compute distances between pairs of different labels instances that have a certain degree of similarity. This speed-up is possible through a new clustering method called BDT Clustering presented within this paper, which is based on a supervised learning algorithm.","PeriodicalId":150575,"journal":{"name":"2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133205334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Implementing Reasoning Modules in Implicit Induction Theorem Provers 在隐式归纳定理证明中实现推理模块
2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing Pub Date : 2014-09-01 DOI: 10.1109/SYNASC.2014.26
Sorin Stratulat
{"title":"Implementing Reasoning Modules in Implicit Induction Theorem Provers","authors":"Sorin Stratulat","doi":"10.1109/SYNASC.2014.26","DOIUrl":"https://doi.org/10.1109/SYNASC.2014.26","url":null,"abstract":"We detail the integration in SPIKE, an implicit induction theorem prover, of two reasoning modules operating over naturals combined with interpreted symbols. The first integration schema is à la Boyer-Moore, based on the combination of a congruence closure procedure with a decision procedure for linear arithmetic over rationals/reals. The second follows a 'black-box' approach and is based on external SMT solvers. It is shown that the two extensions significantly increase the power of SPIKE, their performances are compared when proving a non-trivial application.","PeriodicalId":150575,"journal":{"name":"2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121366408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Opinion Influence Analysis in Online Forum Threads 网络论坛话题的意见影响分析
2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing Pub Date : 2014-09-01 DOI: 10.1109/SYNASC.2014.38
Dumitru-Clementin Cercel, Stefan Trausan-Matu
{"title":"Opinion Influence Analysis in Online Forum Threads","authors":"Dumitru-Clementin Cercel, Stefan Trausan-Matu","doi":"10.1109/SYNASC.2014.38","DOIUrl":"https://doi.org/10.1109/SYNASC.2014.38","url":null,"abstract":"This paper treats the phenomenon of opinion influence in online forum threads. Influence among users' opinions is analyzed by taking into consideration the changes in their opinions. Therefore, a change in a user's opinion is modeled as a change of his/her posts' polarity. The hypothesis that underlies our research is that users' opinions may change over time as a consequence of the interactions between them in online discussions such as online forum threads. Moreover, a user's new post in an online forum thread is considered to have an influence on all the posts sent by other users in reaction to this. Our approach to the opinion influence phenomenon that arises in online forum threads is based on Natural Language Processing techniques, Latent Semantic Analysis and Post-Level Sentiment Analysis. The results obtained by us show that all the previous posts that contain opinions have an influence, more or less significant, on a new post in the same online forum thread.","PeriodicalId":150575,"journal":{"name":"2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115981599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Multi-phase Identification in Microstructures Images Using a GPU Accelerated Fuzzy C-Means Segmentation 基于GPU加速模糊c均值分割的微结构图像多相识别
2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing Pub Date : 2014-09-01 DOI: 10.1109/SYNASC.2014.86
D. Onchis, D. Frunzaverde, Mihail Gaianu, Relu Ciubotariu
{"title":"Multi-phase Identification in Microstructures Images Using a GPU Accelerated Fuzzy C-Means Segmentation","authors":"D. Onchis, D. Frunzaverde, Mihail Gaianu, Relu Ciubotariu","doi":"10.1109/SYNASC.2014.86","DOIUrl":"https://doi.org/10.1109/SYNASC.2014.86","url":null,"abstract":"This paper presents an effective algorithm for the identification of multiple phases in microstructures images. The procedure is based on an efficient image segmentation using the fuzzy c-means algorithm. Furthermore, the algorithm is accelerated on a GPU cluster in order to obtain optimal computing times for large size images. The results are compared on the same experimental images with the ones obtained from a commercial software and the accuracy of the proposed algorithm is demonstrated.","PeriodicalId":150575,"journal":{"name":"2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116151843","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 3
Branch Differences and Lambert W 分支差异与Lambert W
2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing Pub Date : 2014-09-01 DOI: 10.1109/SYNASC.2014.16
D. J. Jeffrey, J. Jankowski
{"title":"Branch Differences and Lambert W","authors":"D. J. Jeffrey, J. Jankowski","doi":"10.1109/SYNASC.2014.16","DOIUrl":"https://doi.org/10.1109/SYNASC.2014.16","url":null,"abstract":"The Lambert W function possesses branches labelled by an index k. The value of W therefore depends upon the value of its argument z and the value of its branch index. Given two branches, labelled n and m, the branch difference is the difference between the two branches, when both are evaluated at the same argument z. It is shown that elementary inverse functions have trivial branch differences, but Lambert W has nontrivial differences. The inverse sine function has real-valued branch differences for real arguments, and the natural logarithm function has purely imaginary branch differences. The Lambert W function, however, has both real-valued differences and complex-valued differences. Applications and representations of the branch differences of W are given.","PeriodicalId":150575,"journal":{"name":"2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125130677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Simulation-Extrapolation Gaussian Processes for Input Noise Modeling 输入噪声建模的模拟-外推高斯过程
2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing Pub Date : 2014-09-01 DOI: 10.1109/SYNASC.2014.33
B. Bócsi, Hunor Jakab, L. Csató
{"title":"Simulation-Extrapolation Gaussian Processes for Input Noise Modeling","authors":"B. Bócsi, Hunor Jakab, L. Csató","doi":"10.1109/SYNASC.2014.33","DOIUrl":"https://doi.org/10.1109/SYNASC.2014.33","url":null,"abstract":"Input noise is common in situations when data either is coming from unreliable sensors or previous outputs are used as current inputs. Nevertheless, most regression algorithms do not model input noise, inducing thus bias in the regression. We present a method that corrects this bias by repeated regression estimations. In simulation extrapolation we perturb the inputs with additional input noise and by observing the effect of this addition on the result, we estimate what would the prediction be without the input noise. We extend the examination to a non-parametric probabilistic regression, inference using Gaussian processes. We conducted experiments on both synthetic data and in robotics, i.e., Learning the transition dynamics of a dynamical system, showing significant improvements in the accuracy of the prediction.","PeriodicalId":150575,"journal":{"name":"2014 16th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128624880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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