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2011 14th Euromicro Conference on Digital System Design: Architectures, Methods and Tools, DSD 2011

作者： Nery, Alexandre S. Jozwiak, Lech Lindwer, Menno Cocco, Mauro Nedjah, Nadia França, Felipe M.G. LAM - Computer Architecture and Microelectronics Laboratory Systems Engineering and Computer Science Program COPPE Universidade Federal do Rio de Janeiro Brazil Department of Electronics Engineering and Telecommunications Faculty of Engineering Universidade do Estado do Rio de Janeiro Brazil Department of Electrical Engineering - Electronic Systems Eindhoven University of Technology Netherlands Silicon Hive - Intel UMG Netherlands

ISBN: (纸本)9780769544946

Effective exploitation of the application-specific parallel patterns and computation operations through their direct implementation in hardware is the base for construction of high-quality application-specific (re-) configurable application specific instruction set processors (ASIPs) and hardware accelerators for modern highly-demanding applications. Although it receives a lot of attention from the researchers and practitioners, a very important problem of hardware reuse in ASIP and accelerator synthesis is clearly underestimated and does not get enough attention in the published research. This paper is an effect of an industry and academic collaborative research. It analyses the problem of hardware sharing, shows its high practical relevance, as well as a big influence of hardware sharing on the major circuit and system parameters, and its importance for the multi-objective optimization and tradeoff exploitation. It also demonstrates that the state-of-the-art synthesis tools do not sufficiently address this problem and gives several guidelines related to enhancement of the hardware reuse. © 2011 IEEE.

关键词： Multiobjective optimization

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Towards using task similarity to recommend Stack Overflow posts 21

Towards using task similarity to recommend Stack Overflow po...

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21st Ibero-American Conference on Software engineering, CIbSE 2018

作者： Melo, Gláucia Telemaco, Ulisses Oliveira, Toacy Alencar, Paulo Cowan, Don COPPE – Systems Engineering and Computer Science Department UFRJ – Federal University of Rio de Janeiro Rio de Janeiro – RJ Brazil David R. Cheriton School of Computer Science University of Waterloo WaterlooON Canada

ISBN: (纸本)9789584837547

Software development depends on diverse technologies and methods and as a result, software development teams often handle issues in which team members are not experts. In order to address this lack of expertise, developers typically search for information on web-based Q&A sites such as Stack Overflow, a well-known place to find solutions to specific technology-related problems. The access to these web-based Q&A locations is currently not integrated into the software development environment, and because the associations between software development processes and the supporting sources of known solutions, usually referred to as knowledge, is not explicitly modeled and recorded, software developers often need to search for solutions to similar recurring issues multiple times. Moreover, this lack of integration hampers the implementation of a proactive recommender system that can point developers to knowledge that is relevant to their development processes. This research aims at proposing a solution that explicitly associates process elements (such as project tasks) to Stack Overflow posts and presents a recommender system that proactively recommends Stack Overflow posts to developers based on the similarity of project tasks. A literature review was used to find the concepts to define a meta-model for project tasks. This research paper advances the area of software development knowledge reuse by reporting on both the model and the results of experiments performed with real project development data. © 2018 Conferencia Iberoamericana de Software engineering - CIbSE. All Rights Reserved.

关键词： Recommender systems

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SpMT WaveCache: Exploiting Thread-Level Parallelism in WaveScalar

SpMT WaveCache: Exploiting Thread-Level Parallelism in WaveS...

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computer science and Information engineering, CSIE, WRI World Congress on FLAGGED

作者： Songwen Pei Baifeng Wu Min Du Gang Chen Leandro A.J. Marzulo Felipe M.G. Franca School of Computer Science Fudan University Shanghai China Systems Engineering and Computer Science Program COPPE Rio de Janeiro Brazil

Speculative multithreading (SpMT) increases the performance by means of executing multiple threads speculatively to exploit thread-level parallelism. By combining software and hardware approaches, we have improved the capabilities of previous WaveScalar ISA on the basis of transactional memory system for the WaveCache Architecture. Threads are extracted at the course of static compiling, and speculatively executed as a thread-level transaction that is supported by extra hardware components, such as thread-context-table (TCT) and thread-memory-history (TMH). We have evaluated the SpMT WaveCache with 6 real benchmarks from SPEC, Mediabench and Mibench. On the whole, the SpMT WaveCache outperforms superscalar architecture ranging from 2times to 3times, and great performance gains are achieved over original WaveCache and transactional WaveCache as well.

关键词： Yarn Parallel processing Multithreading Hardware computer science computer architecture Instruction sets Out of order program processors Protocols

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Odyssey process reuse: A component-based software process line approach 20

Odyssey process reuse: A component-based software process li...

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20th International Conference on Enterprise Information systems, ICEIS 2018

作者： Teixeira, Eldânae Nogueira Vasconcelos, Aline Werner, Cláudia Systems Engineering and Computer Science Program COPPE/UFRJ ZIP Code: 21945-970 P.O. Box 68511 Rio de Janeiro RJ Brazil Federal Fluminense Institute of Education Science and Technology Campos dos Goytacazes Goytacazes RJ Brazil

ISBN: (纸本)9789897582981

It is expected that managing process variations and organizing process domain knowledge in a reusable way can provide support to handle complexity in software process definition. In this context, the purpose of this paper is to describe a systematic software process reuse methodology, by combining process reuse techniques, such as Software Process Line and Component Based Process Definition, aiming to increase reuse possibilities. SPrL approach manages the variability aspect inherent to software process domain and CBPD focuses on modularizing the domain process information into process components. The proposed SPrL modelling metamodel and notation address reusable process elements, explicitly representing the variability concept in both process domain structure and behaviour. Based on the results of the evaluation studies, it was possible to get evidences of the approach feasibility, with a higher expressiveness when using the process variability notation proposed, which allow that more semantic concepts inherent to SPrL scenarios can be graphically described. Also, the set of heuristics to support mappings among artefacts in distinct abstraction levels was considered useful to keep the traceability of variability properties, relationships and restrictions. Further research is being conducted to explore ways to support project managers during the decision-making in new software process definitions. © 2018 by SCITEPRESS - science and Technology Publications, Lda.

关键词： Decision making

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RUL Estimation for Power Electronic Devices Using RNNs

RUL Estimation for Power Electronic Devices Using RNNs

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2024 Prognostics and System Health Management Conference, PHM 2024

作者： Cai, Congrui Lu, Zhonghai School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Embedded Systems Master Program Sweden School of Electrical Engineering and Computer Science Department of Electrical Engineering KTH Royal Institute of Technology Sweden

ISBN: (纸本)9798350360585

Recurrent Neural Networks (RNNs) are commonly used in data-driven approaches to estimate the Remaining Useful Lifetime (RUL) of power electronic devices. RNNs are preferred because their intrinsic feedback mechanisms are better suited to model time-series data. However, the impact of RNN complexity on estimation accuracy is rarely discussed in the literature. This issue is important because choosing a lower-complexity model that delivers the same or similar performance as a higher-complexity model can increase implementation efficiency. In the paper, we use three RNN models, namely, the vanilla version, LSTM (Long Short Term Memory) and GRU (Gated Recurrent Unit) to conduct RUL estimation for power electronic devices. We use two accelerated aging datasets, one dataset targeting the package failure of MOSFETs, and the other dataset targeting package failure of power diodes. Our study shows that a lower-complexity RNN does not necessarily deliver a lower performance. Similarly, a higher-complexity model does not assure a higher performance. As such, our work highlights the importance of selecting a proper neural network for RUL estimation not biased towards complex models. This is especially useful and important for implementing such RUL estimation techniques in embedded resource-constrained and speed-limited computins platforms. © 2024 IEEE.

关键词： Long short-term memory

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Propositional dynamic logic with storing, recovering and parallel composition

Propositional dynamic logic with storing, recovering and par...

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作者： Benevides, Mario R.F. De Freitas, Renata Petrucio, Viana Computer Science Department Systems and Computer Engineering Program Federal University of Rio de Janeiro Brazil Institute of Mathematics Fluminense Federal University Brazil

This work extends Propositional Dynamic Logic (PDL) with parallel composition operator and four atomic programs which formalize the storing and recovering of elements in data structures. A generalization of Kripke semantics is proposed that instead of using set of possible states it uses structured sets of possible states. This new semantics allows for representing data structures and using the five new operator one is capable of reasoning about the manipulation of these data structures. The use of the new language (PRSPDL) is illustrated with some examples. We present sound and complete set of axiom schemata and inference rules to prove all the valid formulas for a restricted fragment called RSPDLo. © 2011 Elsevier B.V. All rights reserved.

关键词： Data structures

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An efficient parallel architecture for ray-tracing

An efficient parallel architecture for ray-tracing

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作者： Nery, Alexandre S. Nedjah, Nadia França, Felipe M.G. LAM - Computer Architecture and Microeletronics Laboratory Systems Engineering and Computer Science Program COPPE Universidade Federal Do Rio de Janeiro Rio de Janeiro RJ Brazil Department of Electronics Engineering and Telecommunications Faculty of Engineering Universidade Do Estado Do Rio de Janeiro Rio de Janeiro RJ Brazil

Real time rendering of three-dimensional scenes in high photorealistic details is a hard task, such as in the ray tracing rendering algorithm. In general, the performance achieved by a sequential software-based implementation of ray tracing is far from satisfactory. However, parallel implementations of ray tracing have been enabling reasonable real time performance, as the algorithm is embarrassingly parallel. Thus, a custom parallel design in hardware is likely to achieve an even higher performance. In this paper, we propose a hardware parallel architecture capable of dealing with the main desirable features of ray tracing, such as shadows and reflection effects, imposing low area cost and a promising rendering performance. Such architecture, called GridRT, is based on the Uniform Grid acceleration structure and is intended to deliver massive parallelism through parallel ray-triangle intersection tests as well as parallel processing of many rays. A hardware implementation of the proposed architecture is presented, together with some performance results and resources requirements. The rendering is reduced by 80% using a grid configuration of eight processing elements. © Springer science+Business Media, LLC 2011.

关键词： Field programmable gate arrays (FPGA)

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Software process performance improvement using data provenance and ontology

Software process performance improvement using data provenan...

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International Conference on Business Process Management, BPM 2016

作者： Costa, Gabriella Castro Barbosa Werner, Cláudia M. L. Braga, Regina Systems Engineering and Computer Science Department Federal University of Rio de Janeiro COPPE Rio de JaneiroRJ Brazil Computer Science Department Federal University of Juiz de Fora Juiz de ForaMG Brazil

ISBN: (纸本)9783319454672

Organizations are investing on process definition and improvement in order to enhance their products’ quality. In the software processes context, this is not different. A practice to support software processes continuous improvement is to reuse the knowledge acquired in previous process executions. After defining measures to the software processes performance, an analysis of process execution data can be done, in order to detect process enhancement points. One way to capture these process execution data is using data provenance models. Thus, these data can be analyzed, using information derivation mechanisms, such as inference engines for ontologies. This paper aims to describe and evaluate an approach to support software process execution analysis to improve process performance, using data provenance and ontologies. A pilot case study was conducted with software processes used in two software development companies. With this study, implicit information was derived and can be used for improving process performance. © Springer International Publishing Switzerland 2016.

关键词： Ontology

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Biomedical data and AI

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science China Life sciences 2025年第5期68卷 1536-1540页

作者： Hao Xu Shibo Zhou Zefeng Zhu Vincenzo Vitelli Liangyi Chen Ziwei Dai Ning Yang Luhua Lai Shengyong Yang Sergey Ovchinnikov Zhuoran Qiao Sirui Liu Chen Song Jianfeng Pei Han Wen Jianfeng Feng Yaoyao Zhang Zhengwei Xie Yang-Yu Liu Zhiyuan Li Fulai Jin Hao Li Mohammad Lotfollahi Xuegong Zhang Ge Yang Shihua Zhang Ge Gao Pulin Li Qi Liu Jing-Dong Jackie Han Peking-Tsinghua Center for Life Sciences (CLS) Academy for Advanced Interdisciplinary StudiesPeking University Center for Quantitative Biology (CQB) Academy for Advanced Interdisciplinary StudiesPeking University Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program Academy for Advanced Interdisciplinary StudiesPeking University Department of Physics University of Chicago School of Life Sciences Southern University of Science and Technology Peking University Chengdu Academy for Advanced Interdisciplinary Biotechnologies College of Chemistry and Molecular Engineering Peking University Department of Biotherapy Cancer Center and State Key Laboratory of BiotherapyWest China HospitalSichuan University Department of Biology Massachusetts Institute of Technology Lambic Therapeutics Inc. Changping Laboratory Al for Science Institute Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Fudan University Department of Obstetrics and Gynecology West China Second University HospitalSichuan University Peking University International Cancer Institute and Peking University-Yunnan Baiyao International Medical Institute and State Key Laboratory of Natural and Biomimetic Drugs Department of Molecular and Cellular PharmacologySchool of Pharmaceutical SciencesPeking University Health Science CenterPeking University Channing Division of Network Medicine Department of MedicineBrigham and Women's Hospital and Harvard Medical School Center for Artificial Intelligence and Modeling the Carl R.Woese Institute for Genomic BiologyUniversity of Illinois Urbana-Champaign Department of Genetics and Genome Sciences School of Medicine and Department of Computer and Data Sciences and Department of Population and Quantitative Health SciencesCase Western Reserve University Department of Biochemistry and Biophysics University of California Sanger Institute Department of Automation Tsinghua University State Key Laboratory of Multimodal Artificial Intelligence Systems I

The development of artificial intelligence(AI) and the mining of biomedical data complement each other. From the direct use of computer vision results to analyze medical images for disease screening, to now integrating biological knowledge into models and even accelerating the development of new AI based on biological discoveries, the boundaries of both are constantly expanding, and their connections are becoming closer.

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DARTS-Drone and Artificial Intelligence Reconsolidated Technological Solution for Increasing the Oil and Gas Pipeline Resilience

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International Journal of Disaster Risk science 2022年第5期13卷 810-821页

作者： Premkumar Ravishankar Seokyon Hwang Jing Zhang Ibrahim X.Khalilullah Berna Eren-Tokgoz Department of Industrial and Systems Engineering Lamar UniversityBeaumontTX 77710USA Construction Management Program Lamar UniversityBeaumontTX 77710USA Department of Computer Science Lamar UniversityBeaumontTX 77710USA

The need for safe operation and effective maintenance of pipelines grows as oil and gas demand ***,it is increasingly imperative to monitor and inspect the pipeline system,detect causes contributing to developing pipeline damage,and perform preventive maintenance in a timely ***,pipeline inspection is performed at pre-determined intervals of several months,which is not sufficiently robust in terms of *** research proposes a drone and artificial intelligence reconsolidated technological solution(DARTS) by integrating drone technology and deep learning *** solution is aimed to detect the targeted potential root problems-pipes out of alignment and deterioration of pipe support system-that can cause critical pipeline failures and predict the progress of the detected problems by collecting and analyzing image data *** test results show that DARTS can be effectively used to support decision making for preventive pipeline maintenance to increase pipeline system s afety and resilience.

关键词： Artifcial intelligence Asset management Drone application Midstream industry Pipeline resilience Predictive maintenance

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