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Ad Hoc File Systems for High-Performance Computing

Journal of computer science & Technology 2020年第1期35卷 4-26页

作者： AndréBrinkmann Kathryn Mohror Weikuan Yu Philip Carns Toni Cortes Scott A.Klasky Alberto Miranda Franz-Josef Pfreundt Robert B.Ross Marc-AndréVef Zentrum für Datenverarbeitung Johannes Gutenberg University MainzMainz 55128Germany Center for Applied Scientific Computing Lawrence Livermore National LaboratoryLivermoreCA 94550U.S.A Department of Computer Science Florida State UniversityTallahasseeFL 32306U.S.A Mathematics and Computer Science Division Argonne National LaboratoryLemontIL 60439U.S.A Department of Computer Architecture Universitat Politecnica de CatalunyaBarcelona 08034Spain Computer Science and Mathematics Division Oak Ridge National LaboratoryOak RidgeTN 37831U.S.A Computer Science Department Barcelona Supercomputing CenterBarcelona 08034Spain Fraunhofer Institute for Industrial Mathematics ITWM Fraunhofer-Platz 1Kaiserslautern 67663Germany

Storage backends of parallel compute clusters are still based mostly on magnetic disks,while newer and faster storage technologies such as flash-based SSDs or non-volatile random access memory(NVRAM)are deployed within compute *** these new storage technologies into scientific workflows is unfortunately today a mostly manual task,and most scientists therefore do not take advantage of the faster storage *** approach to systematically include nodelocal SSDs or NVRAMs into scientific workflows is to deploy ad hoc file systems over a set of compute nodes,which serve as temporary storage systems for single applications or longer-running *** paper presents results from the Dagstuhl Seminar 17202"Challenges and Opportunities of User-Level File Systems for HPC"and discusses application scenarios as well as design strategies for ad hoc file systems using node-local storage *** discussion includes open research questions,such as how to couple ad hoc file systems with the batch scheduling environment and how to schedule stage-in and stage-out processes of data between the storage backend and the ad hoc file *** presented are strategies to build ad hoc file systems by using reusable components for networking and how to improve storage device *** interfaces and semantics are presented,for example those used by the three ad hoc file systems BeeOND,GekkoFS,and *** presentation covers a range from file systems running in production to cutting-edge research focusing on reaching the performance limits of the underlying devices.

关键词： parallel architectures distributed file system high-performance computing burst buffer POSIX(portable operating system interface)

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What to Do When the Users of an Ontology Merging System Want the Impossible? Towards Determining Compatibility of Generic Merge Requirements 22nd

What to Do When the Users of an Ontology Merging System Want...

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22nd International Conference on Knowledge Engineering and Knowledge Management, EKAW 2020

作者： Babalou, Samira Grygorova, Elena König-Ries, Birgitta Heinz-Nixdorf Chair for Distributed Information Systems Institute for Computer Science Friedrich Schiller University Jena Jena Germany

ISBN: (纸本)9783030612436

Ontology merging systems enable the reusability and interoperability of existing knowledge. Ideally, they allow their users to specify which characteristics the merged ontology should have. In prior work, we have identified Generic Merge Requirements (GMRs) reflecting such characteristics. However, not all of them can be met simultaneously. Thus, if a system allows users to select which GMRs should be met, it needs a way to deal with incompatible GMRs. In this paper, we analyze in detail which GMRs are (in-)compatible, and propose a graph based approach to determining and ranking maximum compatible supersets of user-specified GMRs. Our analysis shows that this is indeed feasible to detect the compatible supersets of the given GMRs that can be fulfilled simultaneously. This approach is implemented in the open source Merger tool. © 2020, Springer Nature Switzerland AG.

关键词： Reusability

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NEURAL PROGRAM SYNTHESIS WITH QUERY

arXiv

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arXiv 2022年

作者： Huang, Di Zhang, Rui Hu, Xing Zhang, Xishan Jin, Pengwei Li, Nan Du, Zidong Guo, Qi Chen, Yunji SKL of Computer Architecture Institute of Computing Technology CAS China University of Chinese Academy of Sciences China University of Science and Technology of China China Cambricon Technologies China

Aiming to find a program satisfying the user intent given input-output examples, program synthesis has attracted increasing interest in the area of machine learning. Despite the promising performance of existing methods, most of their success comes from the privileged information of well-designed input-output examples. However, providing such input-output examples is unrealistic because it requires the users to have the ability to describe the underlying program with a few input-output examples under the training distribution. In this work, we propose a query-based framework that trains a query neural network to generate informative input-output examples automatically and interactively from a large query space. The quality of the query depends on the amount of the mutual information between the query and the corresponding program, which can guide the optimization of the query framework. To estimate the mutual information more accurately, we introduce the functional space (F-space) which models the relevance between the input-output examples and the programs in a differentiable way. We evaluate the effectiveness and generalization of the proposed query-based framework on the Karel task and the list processing task. Experimental results show that the query-based framework can generate informative input-output examples which achieve and even outperform well-designed input-output examples. Copyright © 2022, The Authors. All rights reserved.

关键词： Machine learning

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Classification and Categorization of COVID-19 Outbreak in Pakistan

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computers, Materials & Continua 2021年第10期69卷 1253-1269页

作者： Amber Ayoub Kainaat Mahboob Abdul Rehman Javed Muhammad Rizwan Thippa Reddy Gadekallu Mustufa Haider Abidi Mohammed Alkahtani Department of Computer Science Kinnaird College for WomenLahore54000Pakistan Department of Cyber Security Air UniversityIslamabadPakistan School of Information Technology and Engineering Vellore Institute of TechnologyTamil NaduIndia Raytheon Chair for Systems Engineering Advanced Manufacturing InstituteKing Saud UniversityRiyadh11421Saudi Arabia Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia

Coronavirus is a potentially fatal disease that normally occurs in mammals and ***,in humans,the virus spreads through aerial droplets of any type of fluid secreted from the body of an infected *** is a family of viruses that is more lethal than other unpremeditated *** December 2019,a new variant,i.e.,a novel coronavirus(COVID-19)developed in Wuhan province,*** January 23,2020,the number of infected individuals has increased rapidly,affecting the health and economies of many countries,including *** objective of this research is to provide a system to classify and categorize the COVID-19 outbreak in Pakistan based on the data collected every day from different regions of *** research also compares the performance of machine learning classifiers(i.e.,Decision Tree(DT),Naive Bayes(NB),Support Vector Machine,and Logistic Regression)on the COVID-19 dataset collected in *** to the experimental results,DT and NB classifiers outperformed the other *** addition,the classified data is categorized by implementing a Bayesian Regularization Artificial Neural Network(BRANN)*** results demonstrate that the BRANN classifier outperforms state-of-the-art classifiers.

关键词： COVID-19 pandemic neural network BRANN machine learning

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Challenges and Opportunities of DevOps in Cyber-Physical Production Systems Engineering

Challenges and Opportunities of DevOps in Cyber-Physical Pro...

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Industrial Cyber-Physical Systems (ICPS)

作者： István Koren Felix Rinker Kristof Meixner Jasminka Matevska Jörg Walter Chair of Process and Data Science RWTH Aachen University Aachen Germany Christian Doppler Laboratory SQI Institute of Information Systems Engineering TU Wien Vienna Austria School of Electrical Engineering and Computer Science City University of Applied Sciences Bremen Germany Distributed Computing and Communication OFFIS - Institute for Information Technology Oldenburg Germany

DevOps is a set of practices that combines software development and operations to enable a continuous software product life cycle to improve the quality of software systems. Although DevOps is considered successful for typical software systems, it has not yet been widelyadopted in the area of - Physlcal Production Systems (CPPSs) that integrate physical components with computer-based control and communication systems. Related to industrial settings, many new challenges arise, like long-term investments, missing flexibility in asset-heavy production environments, and the inherent physicality of hardware. This paper examines the use of the DevOps methodology in the manufacturing domain. It identifies and discusses the unique challenges and describes first solution proposals to overcome those challenges, based on literature and experiences from the industry. The article provides useful guidance to researchers and practitioners on potential pitfalls and exciting opportunities.

关键词： Production systems Data collection Software systems Hardware Safety Stakeholders Security

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Potential Use of Human Bio-Signals for Indoor Air Quality Control Principles in Residential Buildings

SSRN

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SSRN 2023年

作者： Gong, Minghuan Li, Yixiao Choi, Joon-Ho Imani, Saba Dai, Haoyue Building Science School of Architecture University of Southern California United States Computer Science Viterbi School of Engineering University Southern California United States Information Sciences Institute Viterbi School of Engineering University Southern California United States The University of Arizona United States

This study aimed to explore the correlation between indoor air quality (IAQ) parameters and human physiological responses. Twelve participants volunteered, and sensors were used to collect data for five days. Bio-signals such as heart rate, skin temperature, stress level, and electrodermal activity were collected from smartwatches, and IAQ evaluation and thermal comfort questionnaires were completed every two hours. The study found that heart rate was most associated with indoor PM2.5 and CO2 concentrations, while stress level was most associated with IAQ evaluation based on stepwise linear regression analysis. Electrodermal activity was most associated with IAQ evaluation based on random forest analysis, and skin temperature was most associated with thermal comfort. Relative humidity was most associated with IAQ evaluation based on stepwise linear regression analysis, and indoor CO2 concentration was most associated with IAQ evaluation based on random forest analysis. The study findings suggest the importance of customized models that consider individual differences in analyzing the correlation between IAQ parameters and human bio-signals. Future studies should include a larger and more diverse sample size, conducted over different seasons to improve the accuracy of research results. The findings can be used to develop IAQ control models that utilize bio-signals to enhance thermal comfort and indoor air quality in residential and commercial buildings. This research provides insights into the significance of IAQ for human health and wellness, and its technical principles are applicable in the environmental controls, especially for residential buildings. © 2023, The Authors. All rights reserved.

关键词： Thermal comfort

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Overlooked Aspects of Data Governance: Workflow Framework For Enterprise Data Deduplication

Overlooked Aspects of Data Governance: Workflow Framework Fo...

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Intelligent Computing, Communication, Networking and Services (ICCNS), International Conference on

作者： Otmane Azeroual Anastasija Nikiforova Kewei Sha German Centre for Higher Education Research and Science Studies (DZHW) Berlin Germany Faculty of Science and Technology Institute of Computer Science Chair of Software Engineering University of Tartu Tartu Estonia Task Force “FAIR Metrics and Data Quality” European Open Science Cloud Brussels Belgium College of Science and Engineering University of Houston Clear Lake Houston USA

Data quality in companies is decisive and critical to the benefits their products and services can provide. However, in heterogeneous IT infrastructures where, e.g., different applications for Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), product management, manufacturing, and marketing are used, duplicates, e.g., multiple entries for the same customer or product in a database or information system, occur. There can be several reasons for this, but the result of non-unique or duplicate records is a degraded data quality. This ultimately leads to poorer, inefficient, and inaccurate data-driven decisions. For this reason, in this paper, we develop a conceptual data governance framework for effective and efficient management of duplicate data, and improvement of data accuracy and consistency in large data ecosystems. We present methods and recommendations for companies to deal with duplicate data in a meaningful way.

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Enhancing Local Feature Learning for 3D Point Cloud Processing using Unary-Pairwise Attention 32

Enhancing Local Feature Learning for 3D Point Cloud Processi...

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32nd British Machine Vision Conference, BMVC 2021

作者： Xiu, Haoyi Liu, Xin Wang, Weimin Kim, Kyoung-Sook Shinohara, Takayuki Chang, Qiong Matsuoka, Masashi Department of Architecture and Building Engineering Tokyo Institute of Technology Tokyo Japan Artificial Intelligence Research Center AIST Tokyo Japan DUT-RU International School of Information Science and Engineering Dalian University of Technology Dalian China Department of Computer Science Tokyo Institute of Technology Tokyo Japan

We present a simple but effective attention named the unary-pairwise attention (UPA) for modeling the relationship between 3D point clouds. Our idea is motivated by the analysis that the standard self-attention (SA) that operates globally tends to produce almost the same attention maps for different query positions, revealing difficulties for learning query-independent and query-dependent information jointly. Therefore, we reformulate the SA and propose query-independent (Unary) and query-dependent (Pairwise) components to facilitate the learning of both terms. In contrast to the SA, the UPA ensures query dependence via operating locally. Extensive experiments show that the UPA outperforms the SA consistently on various point cloud understanding tasks including shape classification, part segmentation, and scene segmentation. Moreover, simply equipping the popular PointNet++ method with the UPA even outperforms or is on par with the state-of-the-art attention-based approaches. In addition, the UPA systematically boosts the performance of both standard and modern networks when it is integrated into them as a compositional module. © 2021. The copyright of this document resides with its authors.

关键词： computer vision

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Development of an Automated Process Chain for Hybrid Additive Manufacturing using Laser Powder Bed Fusion

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Procedia CIRP 2022年 112卷 358-363页

作者： Lukas Langer Matthias Schmitt Georg Schlick Johannes Schilp Fraunhofer IGCV (Research Institute for Casting Composite and Processing Technology) Am Technologiezentrum 10 86159 Augsburg University of Augsburg Chair of Digital Manufacturing Department of Applied Computer Science Universitätsstraße 2 86159 Augsburg Germany

Additive Manufacturing (AM) offers great potential for producing complex parts. However, the economical fabrication depends among others on the part height. Hence, the combination of a conventionally manufactured base body and AM offers potential to reduce part costs. This combination is called Hybrid Additive Manufacturing (HAM) and requires additional clamping mechanisms and a positioning system in the laser powder bed fusion process. Concepts for both requirements will be investigated within this paper. In order to increase flexibility and automation a concept for an automated process chain will be developed. The requirements and properties of the process chain will be discussed.

关键词： Hybrid Additive Manufacturing Automation Subtractive Manufacturing Clamping Positioning Metrology

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Multi-material additive manufacturing of thermocouples by laser-based powder bed fusion

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Procedia CIRP 2022年 112卷 346-351页

作者： Christopher Singer Matthias Schmitt Georg Schlick Johannes Schilp Fraunhofer IGCV (Research Institute for Casting Composite and Processing Technology) Am Technologiezentrum 10 86159 Augsburg University of Augsburg Chair of Digital Manufacturing Department of Applied Computer Science Universitätsstraße 2 86159 Augsburg Germany

Multi-material additive manufacturing by laser-based powder bed fusion (PBF-LB) enables arbitrary material composition in components and thus enables the manufacturing of so-called smart parts. By combining different materials sensoric structures can be implemented into components. This paper investigates the possibilities to manufacture thermocouples (TC) consisting of two nickel-based alloys by the means of PBF-LB. These alloys are qualified to achieve sufficient relative densities for the thermocouples. Furthermore, the electrical conductivity of the parts is measured and compared to literature values. Finally, additively manufactured thermocouples are tested in comparison to conventional thermocouples in the temperature range from 50 to 350°C.

关键词： metal additive manufacturing sensor printing thermocouples smart parts laser-based powder bed fusion laser beam melting multi-material

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