检索结果-内蒙古大学图书馆

Analysis of computational science and engineering SW Data Format for Multi-physics and Visualization

KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS 2020年第2期14卷 889-906页

作者： Ryu, Gimyeong Kim, Jaesung Lee, Jongsuk Ruth Korea Inst Sci & Technol Informat Div Natl Supercomp Daejeon South Korea

Analysis of multi-physics systems and the visualization of simulation data are crucial and difficult in computational science and engineering. In Korea, Korea Institute of science and Technology Information KISTI developed EDISON, a web-based computational science simulation platform, and it is now the ninth year since the service started. Hitherto, the EDISON platform has focused on providing a robust simulation environment and various computational science analysis tools. However, owing to the increasing issues in collaborative research, data format standardization has become more important. In addition, as the visualization of simulation data becomes more important for users to understand, the necessity of analyzing input / output data information for each software is increased. Therefore, it is necessary to organize the data format and metadata for the representative software provided by EDISON. In this paper, we analyzed computational fluid dynamics (CFD) and computational structural dynamics (CSD) simulation software in the field of mechanical engineering where several physical phenomena (fluids, solids, etc.) are complex. Additionally, in order to visualize various simulation result data, we used existing web visualization tools developed by third parties. In conclusion, based on the analysis of these data formats, it is possible to provide a foundation of multi-physics and a web-based visualization environment, which will enable users to focus on simulation more conveniently.

关键词： computational science and engineering EDISON data format metadata visualization environment

来源：评论

学校读者我要写书评

暂无评论

Parallel Algorithms in computational science and engineering 1

引用

丛书名： Modeling and Simulation in science, engineering and Technology

2020年

作者： Ananth Grama Ahmed H. Sameh

ISBN: (数字)9783030437367

ISBN: (纸本)9783030437350;9783030437381

This contributed volume highlights two areas of fundamental interest in high-performance computing: core algorithms for important kernels and computationally demanding applications. The first few chapters explore algorithms, numerical techniques, and their parallel formulations for a variety of kernels that arise in applications. The rest of the volume focuses on state-of-the-art applications from diverse domains. By structuring the volume around these two areas, it presents a comprehensive view of the application landscape for high-performance computing, while also enabling readers to develop new applications using the kernels. Readers will learn how to choose the most suitable parallel algorithms for any given application, ensuring that theory and practicality are clearly connected. Applications using these techniques are illustrated in detail, including:;will be an ideal reference for applied mathematicians, engineers, computer scientists, and other researchers who utilize high-performance computing in their work.

关键词： computational science and engineering Linear Algebra Mathematical Applications in Computer science Numerical Analysis

来源：评论

学校读者我要写书评

暂无评论

Provenance Data in the Machine Learning Lifecycle in computational science and engineering 14

Provenance Data in the Machine Learning Lifecycle in Computa...

引用

14th IEEE/ACM Workshop on Workflows in Support of Large-Scale science (WORKS)

作者： Souza, Renan Azevedo, Leonardo Lourenco, Vitor Soares, Elton Thiago, Raphael Brandao, Rafael Civitarese, Daniel Brazil, Emilio Vital Moreno, Marcio Valduriez, Patrick Mattoso, Marta Cerqueira, Renato Netto, Marco A. S. IBM Res Rio De Janeiro Brazil Univ Fed Rio de Janeiro Rio De Janeiro Brazil Univ Montpellier INRIA Montpellier France Univ Montpellier LIRMM Montpellier France

ISBN: (纸本)9781728159973

Machine Learning (ML) has become essential in several industries. In computational science and engineering (CSE), the complexity of the ML lifecycle comes from the large variety of data, scientists' expertise, tools, and workflows. If data are not tracked properly during the lifecycle, it becomes unfeasible to recreate a ML model from scratch or to explain to stakeholders how it was created. The main limitation of provenance tracking solutions is that they cannot cope with provenance capture and integration of domain and ML data processed in the multiple workflows in the lifecycle, while keeping the provenance capture overhead low. To handle this problem, in this paper we contribute with a detailed characterization of provenance data in the ML lifecycle in CSE;a new provenance data representation, called PROV-ML, built on top of W3C PROV and ML Schema;and extensions to a system that tracks provenance from multiple workflows to address the characteristics of ML and CSE, and to allow for provenance queries with a standard vocabulary. We show a practical use in a real case in the O&G industry, along with its evaluation using 48 GPUs in parallel.

关键词： Machine Learning Lifecycle Workflow Provenance computational science and engineering

来源：评论

学校读者我要写书评

暂无评论

Effectiveness analysis of web based simulation for computational science and engineering on Improvement EDISON Platform 3

Effectiveness analysis of web based simulation for computati...

引用

3rd IEEE International Conference on Smart Cloud (SmartCloud)

作者： Kwon, Yejin Jeon, Inho Lee, Jongsuk R. Seo, Jerry H. Korea Inst Sci & Technol Informat Natl Inst Supercomp Daejeon South Korea Korea Inst Sci & Technol Informat Networking Ctr Computat Sci Platform Daejeon South Korea

ISBN: (纸本)9781538680001

The EDSION platform has been providing users with computational science and engineering (CSE) software as a web-based service to enable Open science activation and education. To make available computational science and engineering simulation systems, we provide system services in eight applied disciplines, and we have tried to provide an effective platform for users, reflecting the characteristics of each applied disciplines. As a result, we have designed and constructed a workbench-based simulation service that can reflect the type of software and the differentiation of the pre/post processor tools according to the applied disciplines provided to the users, and we compared the improved simulation system with the existing simulation service system. A simulation execution environment that provides a workbench-based CSE simulation can be provided a various user interface environment according to various user's requirements. In addition, the number of additional development nodes in required for pre-processing and post-processing can be reduced, supporting a virtuous cycle simulation development ecosystem that can reduce the burden on developers who develop CSE applications.

关键词： computational science and engineering simulation platform service configuration web service user interface

来源：评论

学校读者我要写书评

暂无评论

Capturing Provenance for Runtime Data Analysis in computational science and engineering Applications 7th

Capturing Provenance for Runtime Data Analysis in Computatio...

引用

7th International Provenance and Annotation Workshop (IPAW)

作者： Silva, Vitor Souza, Renan Camata, Jose de Oliveira, Daniel Valduriez, Patrick Coutinho, Alvaro L. G. A. Mattoso, Marta Univ Fed Rio de Janeiro COPPE Rio De Janeiro Brazil IBM Res Rio De Janeiro Brazil Univ Fed Juiz de Fora Juiz De Fora Brazil Fluminense Fed Univ Niteroi RJ Brazil INRIA Montpellier France LIRMM Montpellier France

ISBN: (纸本)9783319983790;9783319983783

Capturing provenance data for runtime analysis has several challenges in high performance computational science engineering applications. The main issues are avoiding significant overhead in data capture, loading and runtime query support;and coupling provenance capture mechanisms with applications built with highly efficient numerical libraries, and visualization frameworks targeted to high performance environments. This work presents DfA-prov, an approach to capture provenance data and domain data aiming at high performance applications.

关键词： Provenance User steering computational science and engineering HPC

来源：评论

学校读者我要写书评

暂无评论

Research and Education in computational science and engineering

引用

SIAM REVIEW 2018年第3期60卷 707-754页

作者： Ruede, Ulrich Willcox, Karen McInnes, Lois Curfman De Sterck, Hans Univ Erlangen Nurnberg Lehrstuhl Informat D-91058 Erlangen Germany MIT Ctr Computat Engn 77 Massachusetts Ave Cambridge MA 02139 USA Argonne Natl Lab Dept Math & Comp Sci 9700 S Cass Ave Argonne IL 60439 USA Monash Univ Sch Math Sci Melbourne Vic 3800 Australia

This report presents challenges, opportunities, and directions for computational science and engineering (CSE) research and education for the next decade. Over the past two decades the field of CSE has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment, alone is equipped to answer. CSE provides scientists and engineers with algorithmic inventions and software systems that, transcend disciplines and scales. CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society, and the CSE community is at the core of this transformation. However, a combination of disruptive developments-including the architectural complexity of extreme-scale computing, the data revolution and increased attention to data-driven discovery, and the specialization required to follow the applications to new frontiers-is redefining the scope and reach of the CSE endeavor. With these many current and expanding opportunities for the CSE field, there is a growing demand for CSE graduates and a need to expand CSE educational offerings. This need includes CSE programs at both the undergraduate and graduate levels, as well as continuing education and professional development programs, exploiting the synergy between computational science and data science. Yet, as institutions consider new and evolving educational programs, it is essential to consider the broader research challenges and opportunities that provide the context for CSE education and workforce development.

关键词： computational science and engineering education high-performance computing large data analytics predictive science

来源：评论

学校读者我要写书评

暂无评论

Programming for computations - Python : gentle introduction to numerical simulations with Python /

引用

2016年

作者： Linge Svein.

来源：内蒙古大学图书馆图书评论

学校读者我要写书评

暂无评论

Software engineering for computational science and engineering INTRODUCTION

引用

COMPUTING IN science & engineering 2014年第3期16卷 6-9页

作者： Carver, Jeffrey C. Epperly, Tom Univ Alabama Dept Comp Sci Tuscaloosa AL 35487 USA Lawrence Livermore Natl Lab Comp Sci Grp Ctr Appl Sci Comp Livermore CA USA

This special issue contains extensions of the best papers from the 2013 International Workshop on Software engineering for computational science and engineering. In addition to summaries of the included articles, this... 详细信息

关键词： Special Issues And Sections Meetings Scientific Computing Verification And Validation computational science and engineering CSE Scientific Computing Best Practices Agile Programming Debugging

来源：评论

学校读者我要写书评

暂无评论

computational and Analytic Methods in science and engineering 1st ed. 2020

引用

2020年

作者： Christian Constanda

ISBN: (数字)9783030481865

ISBN: (纸本)9783030481858

This contributed volume collects papers presented at a special session of the conference computational and Mathematical Methods in science and engineering (CMMSE) held in Cadiz, Spain from June 30 - July 6, 2019. Covering the applications of integral methods to scientific developments in a variety of fields, ranging from pure analysis to petroleum engineering, the chapters in this volume present new results in both pure and applied mathematics. Written by well-known researchers in their respective disciplines, each chapter shares a common methodology based on a combination of analytic and computational tools. This approach makes the collection a valuable, multidisciplinary reference on how mathematics can be applied to various real-world processes and phenomena.;will be ideal for applied mathematicians, physicists, and research engineers.

关键词： computational science and engineering Numerical Analysis Mathematical Modeling and Industrial Mathematics

来源：评论

学校读者我要写书评

暂无评论

Predictive Data Analysis Platform, for Optimizing and Automating the Distribution of Car Insurance Products, Based on Telematic Data 24th

Predictive Data Analysis Platform, for Optimizing and Automa...

引用

24th International TRIZ Future Conference

作者： Barna, Erik Barcau, Emanuel Ravaru, Raul Life Is Hard Software Co Floresti Romania

ISBN: (纸本)9783031759253;9783031759239;9783031759222

The purpose of this article is to present an AI technology based innovative approach, involved in a platform for digitizing processes in the Car Insurance Business field, which allows the end user (the broker of insurance or the insurer) to base his decisions on robust information to help him make a robust business forecast. Predictive analytics for insurance entails the use of special technology to sift through and analyze historical telematics data and consumer trends in effort to project future behavior. Obviously combining the AI based IT technologies with mathematical and statistical models, the integrated digitalized platform presented in this article involve also both Data Modeling and Deep Learning. Practically, the software platform presented in this article represents the backbone of any insurance brokerage business, because without such an application it is impossible to manage business processes that have hundreds or even thousands of sales agents. From structural point of view, this platform has a layered structure, the first layer being the basic brokerage application, this being extended with innovative predictive computational modules as upper layers. The technical implications mainly refers to the innovative way of involving in the digitalized system a massive amount of telematics data. The expected business implications consists in offering, by an innovative digitalized solution, the possibility for the final client (insurance broker or insurer) to receive information that will help him make a forecast of business.

关键词： computational Models computational science and engineering Telematics Data Mining Clustering Methods

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：