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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

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

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

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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

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Proceedings of the 4th International Conference on Advances in computational science and engineering 1

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丛书名： Lecture Notes in Electrical engineering

1000年

作者： Vinesh Thiruchelvam Rayner Alfred Zamhar Iswandono Bin Awang Ismail Haviluddin Haviluddin Aslina Baharum

ISBN: (数字)9789819729777

ISBN: (纸本)9789819729760;9789819729791

This book is the proceedings of the 4th International Conference on Advances in computational science and engineering (ICACSE 2023, December 16–17, 2023, Manila, Philippines) and contains the selected peer-reviewed papers which reflect recent achievements in the field of application of the computational methods and algorithms in scientific research and engineering design. The papers presented covered topics such as advances in system integration, high-performance computing, modeling, and simulation, big data analytics, big data visualization, advanced networking and applications, cybersecurity, augmented and virtual reality, artificial intelligence and robotics, soft computing data science, and intelligent knowledge discovery. The book is useful, interesting, and informative for a wide range of scientists, engineers, and students.

关键词： computational Intelligence computational science and engineering Theoretical, Mathematical and computational Physics

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Research and Education in computational science and engineering

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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

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

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2016年

作者： Linge Svein.

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FIRST INTERNATIONAL WORKSHOP ON SOFTWARE engineering FOR computational science & engineering

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COMPUTING IN science & engineering 2009年第2期11卷 7-11页

作者： Carver, Jeffrey C. Univ Alabama Dept Comp Sci Tuscaloosa AL 35487 USA

In recognition of the general lack of exposure scientists have to software engineering and vice versa, a workshop was held during the 2008 International Conference on Software engineering in Leipzig, Germany. The workshop's goal was to bring together researchers and practitioners from the software engineering and computational science and engineering (CS&E) communities to build a common understanding of the issues involved in the complex process of CS&E software development and identify common themes to pursue in future research.

关键词： computational science and engineering CSE Software engineering CS E Software Development News

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

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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

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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...

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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

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computational and visual electromagnetics using an integrated programming language for undergraduate engineering students

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IEEE TRANSACTIONS ON MAGNETICS 2000年第4期36卷 1000-1003页

作者： Lu, JW Thiel, DV Griffith Univ Sch Microelect Engn Fac Engn Nathan Qld 4111 Australia

Numerical modeling is now an essential part of undergraduate engineering education. This paper reviews the content and delivery of a course for undergraduate engineers, in computational and visual electromagnetics using the integrated programming language, Matlab, A number of numerical methods are discussed including FDM FEM, MOM and BEM during class. Matlab is then used to implement these methods in a series of workshops, laboratories exercises and assignments.

关键词： computational and visual electromagnetics computational science and engineering engineering education integrated programming language

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Introducing computational science methods using parallax

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SIAM REVIEW 1998年第1期40卷 81-86页

作者： Stevenson, DE Clemson Univ Dept Comp Sci Clemson SC 29634 USA

We briefly describe the Clemson computational science and engineering course. We describe a parallax case study for studying floating-point computation. We outline our presentation of error analysis and a slight abstraction of IEEE arithmetic that we call Wilkinson arithmetic. The students are asked to determine how far parallax is usable given the parameters of the model. We provide one analysis of the problem and topical ideas for students.

关键词： computational science and engineering floating-point systems error analysis elementary function evaluation

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