2015 International Conference on High Performance Computing & Simulation (HPCS)最新文献_第8页

Effective topic modeling for email 有效的电子邮件主题建模

2015 International Conference on High Performance Computing & Simulation (HPCS) Pub Date : 2015-07-20 DOI: 10.1109/HPCSim.2015.7237060

Hiep Hong, Teng-Sheng Moh

{"title":"Effective topic modeling for email","authors":"Hiep Hong, Teng-Sheng Moh","doi":"10.1109/HPCSim.2015.7237060","DOIUrl":"https://doi.org/10.1109/HPCSim.2015.7237060","url":null,"abstract":"Emails have been increasingly popular and have become an indispensible tool for communication and document exchange. Because of its convenience, people use emails every day at work, at school, and for personal matters. Consequently, the number of emails people receive daily keeps on increasing, causing them to spend more time organizing the emails. People often need to classify and move email into folders so that they can go back and read them later. Most email client tools available today allow the users to filter and organize emails by defining rules on how to handle incoming emails. However, this manual process requires users to know their expected emails very well, and to make good use of these tools users need to understand how filtering rules work and how to apply them correctly. In reality, most users do not know what their incoming emails will be. The work described in this paper aims to take the burden of organizing emails away from users by using the Latent Dirichlet Allocation (LDA) [10] to automatically extract topics from emails and group them into folders of common topics. Experiments have shown that the proposed method is able to correctly group emails in appropriate topics with 77% accuracy.","PeriodicalId":134009,"journal":{"name":"2015 International Conference on High Performance Computing & Simulation (HPCS)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129000049","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: 6

Toward a fully parallel multigrid in time algorithm in PETSc environment: A case study in ocean models PETSc环境下的全并行多网格时间算法研究——以海洋模型为例

2015 International Conference on High Performance Computing & Simulation (HPCS) Pub Date : 2015-07-20 DOI: 10.1109/HPCSim.2015.7237098

L. Carracciuolo, L. D’Amore, Valeria Mele

{"title":"Toward a fully parallel multigrid in time algorithm in PETSc environment: A case study in ocean models","authors":"L. Carracciuolo, L. D’Amore, Valeria Mele","doi":"10.1109/HPCSim.2015.7237098","DOIUrl":"https://doi.org/10.1109/HPCSim.2015.7237098","url":null,"abstract":"We consider linear systems that arise from the discretization of evolutionary models. Typically, solution algorithms are based on a time-stepping approach, solving for one time step after the other. Parallelism is limited to the spatial dimension only. Because time is sequential in nature, the idea of simultaneously solving along time steps is not intuitive. One approach to achieve parallelism in time direction is MGRIT algorithm [7], based on multigrid reduction (MGR) techniques. Here we refer to this approach as MGR-1D. Other kind of approach is the space-time multigrid, where time is simply another dimension in the grid. Analougsly, we refer to this approach as MGR-4D. In this work, motivated by the need of maximizing the availability of new algorithms to climate science, we propose a new parallel approach that mixes both the MGR-1D idea and classical space multigrid methods. We refer to it as the MGR3D+1 approach. Moreover, we discuss their implementation in the high performance scientific library PETSc, as starting point to develope more efficient and scalable algorithms in ocean models.","PeriodicalId":134009,"journal":{"name":"2015 International Conference on High Performance Computing & Simulation (HPCS)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129371258","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: 8

On the run-time cost of distributed-memory communications generated using the polyhedral model 关于使用多面体模型生成的分布式内存通信的运行时成本

2015 International Conference on High Performance Computing & Simulation (HPCS) Pub Date : 2015-07-20 DOI: 10.1109/HPCSim.2015.7237034

Ana Moreton-Fernandez, Arturo González-Escribano, D. Ferraris

引用次数: 4

NoC-centric partitioning and reconfiguration technologies for the efficient sharing of multi-core programmable accelerators 面向多核可编程加速器的高效共享的以noc为中心的分区和重构技术

2015 International Conference on High Performance Computing & Simulation (HPCS) Pub Date : 2015-07-20 DOI: 10.1109/HPCSim.2015.7237107

Marco Balboni, D. Bertozzi

引用次数: 0

How advanced cloud technologies can impact and change HPC environments for simulation 先进的云技术如何影响和改变模拟的HPC环境

2015 International Conference on High Performance Computing & Simulation (HPCS) Pub Date : 2015-07-20 DOI: 10.1109/HPCSim.2015.7237116

M. Mancini, G. Aloisio

引用次数: 3

Revisiting co-scheduling for upcoming ExaScale systems 重新考虑即将推出的ExaScale系统的协同调度

2015 International Conference on High Performance Computing & Simulation (HPCS) Pub Date : 2015-07-20 DOI: 10.1109/HPCSim.2015.7237117

Stefan Lankes

引用次数: 0

Tracing long running applications: A case study using Gromacs 跟踪长时间运行的应用程序:使用gromac的案例研究

2015 International Conference on High Performance Computing & Simulation (HPCS) Pub Date : 2015-07-20 DOI: 10.1109/HPCSim.2015.7237031

M. Wagner, J. Doleschal, A. Knüpfer

引用次数: 4

A runtime/memory trade-off of the continous Ziggurat method on GPUs gpu上连续Ziggurat方法的运行时/内存权衡

2015 International Conference on High Performance Computing & Simulation (HPCS) Pub Date : 2015-07-20 DOI: 10.1109/HPCSim.2015.7237018

C. Riesinger, T. Neckel

引用次数: 0

Active learning for support vector regression in radiation shielding design 辐射屏蔽设计中支持向量回归的主动学习

2015 International Conference on High Performance Computing & Simulation (HPCS) Pub Date : 2015-07-20 DOI: 10.1109/HPCSim.2015.7237055

Paulina Duckic, Krešimir Trontl, M. Matijević

引用次数: 1

In search of the best MPI-OpenMP distribution for optimum Intel-MIC cluster performance 寻找最佳的MPI-OpenMP分布以获得最佳的Intel-MIC集群性能

2015 International Conference on High Performance Computing & Simulation (HPCS) Pub Date : 2015-07-20 DOI: 10.1109/HPCSim.2015.7237072

G. Utrera, Marisa Gil, X. Martorell

{"title":"In search of the best MPI-OpenMP distribution for optimum Intel-MIC cluster performance","authors":"G. Utrera, Marisa Gil, X. Martorell","doi":"10.1109/HPCSim.2015.7237072","DOIUrl":"https://doi.org/10.1109/HPCSim.2015.7237072","url":null,"abstract":"Applications for HPC platforms are mainly based on hybrid programming models: MPI for communication and OpenMP for task and fork-join parallelism to exploit shared memory communication inside a node. On the basis of this scheme, much research has been carried out to improve performance. Some examples are: the overlap of communication and computation, or the increase of speedup and bandwidth on new network fabrics (i.e. Infiniband and 10GB or 40GB ethernet). Henceforth, as far as computation and communication are concerned, the HPC platforms will be heterogeneous with high-speed networks. And, in this context, an important issue is to decide how to distribute the workload among all the nodes in order to balance the application execution as well as choosing the most appropriate programming model to exploit parallelism inside the node. In this paper we propose a mechanism to balance dynamically the work distribution among the heterogeneous components of an heterogeneous cluster based on their performance characteristics. For our evaluations we run the miniFE mini-application of the Mantevo suite benchmark, in a heterogeneous Intel MIC cluster. Experimental results show that making an effort to choose the appropriate number of threads can improve performance significantly over choosing the maximum available number of cores in the Intel MIC.","PeriodicalId":134009,"journal":{"name":"2015 International Conference on High Performance Computing & Simulation (HPCS)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124393442","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: 6