Bibliografías temáticas / Sequential processing (Computer science)

Literatura académica sobre el tema "Sequential processing (Computer science)"

Autor: Grafiati
Publicado: 4 de junio de 2021
Última modificación: 31 de enero de 2023

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Artículos de revistas sobre el tema "Sequential processing (Computer science)"

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Carmesin, H. O. y H. Schwegler. "Parallel versus sequential processing of relational stimulus structures". Biological Cybernetics 71, n.º 6 (octubre de 1994): 523–29. http://dx.doi.org/10.1007/bf00198470.

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Carmesin, H. O. y H. Schwegler. "Parallel versus sequential processing of relational stimulus structures". Biological Cybernetics 71, n.º 6 (1 de octubre de 1994): 523–29. http://dx.doi.org/10.1007/s004220050111.

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Lee, Yong-Joo y Paul Zipkin. "Processing Networks with Inventories: Sequential Refinement Systems". Operations Research 43, n.º 6 (diciembre de 1995): 1025–36. http://dx.doi.org/10.1287/opre.43.6.1025.

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Korde, P. S. y P. B. Khanale. "Cache Oblivious Matrix Multiplication Algorithm using Sequential Access Processing". Research Journal of Information Technology 3, n.º 1 (1 de enero de 2011): 61–67. http://dx.doi.org/10.3923/rjit.2011.61.67.

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LeBron Paige, A., Ö. Özdamar y R. E. Delgado. "Two-dimensional spectral processing of sequential evoked potentials". Medical & Biological Engineering & Computing 34, n.º 3 (mayo de 1996): 239–43. http://dx.doi.org/10.1007/bf02520080.

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Sharma, Shalini y Angshul Majumdar. "Sequential Transform Learning". ACM Transactions on Knowledge Discovery from Data 15, n.º 5 (26 de junio de 2021): 1–18. http://dx.doi.org/10.1145/3447394.

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This work proposes a new approach for dynamical modeling; we call it sequential transform learning. This is loosely based on the transform (analysis dictionary) learning formulation. This is the first work on this topic. Transform learning, was originally developed for static problems; we modify it to model dynamical systems by introducing a feedback loop. The learnt transform coefficients for the t th instant are fed back along with the t + 1st sample, thereby establishing a Markovian relationship. Furthermore, the formulation is made supervised by the label consistency cost. Our approach keeps the best of two worlds, marrying the interpretability and uncertainty measure of signal processing with the function approximation ability of neural networks. We have carried out experiments on one of the most challenging problems in dynamical modeling - stock forecasting. Benchmarking with the state-of-the-art has shown that our method excels over the rest.
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Zhuo, Youwei, Jingji Chen, Gengyu Rao, Qinyi Luo, Yanzhi Wang, Hailong Yang, Depei Qian y Xuehai Qian. "Distributed Graph Processing System and Processing-in-memory Architecture with Precise Loop-carried Dependency Guarantee". ACM Transactions on Computer Systems 37, n.º 1-4 (junio de 2021): 1–37. http://dx.doi.org/10.1145/3453681.

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To hide the complexity of the underlying system, graph processing frameworks ask programmers to specify graph computations in user-defined functions (UDFs) of graph-oriented programming model. Due to the nature of distributed execution, current frameworks cannot precisely enforce the semantics of UDFs, leading to unnecessary computation and communication. It exemplifies a gap between programming model and runtime execution. This article proposes novel graph processing frameworks for distributed system and Processing-in-memory (PIM) architecture that precisely enforces loop-carried dependency; i.e., when a condition is satisfied by a neighbor, all following neighbors can be skipped. Our approach instruments the UDFs to express the loop-carried dependency, then the distributed execution framework enforces the precise semantics by performing dependency propagation dynamically. Enforcing loop-carried dependency requires the sequential processing of the neighbors of each vertex distributed in different nodes. We propose to circulant scheduling in the framework to allow different nodes to process disjoint sets of edges/vertices in parallel while satisfying the sequential requirement. The technique achieves an excellent trade-off between precise semantics and parallelism—the benefits of eliminating unnecessary computation and communication offset the reduced parallelism. We implement a new distributed graph processing framework SympleGraph, and two variants of runtime systems— GraphS and GraphSR —for PIM-based graph processing architecture, which significantly outperform the state-of-the-art.
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ROBERGE, VINCENT y MOHAMMED TARBOUCHI. "COMPARISON OF PARALLEL PARTICLE SWARM OPTIMIZERS FOR GRAPHICAL PROCESSING UNITS AND MULTICORE PROCESSORS". International Journal of Computational Intelligence and Applications 12, n.º 01 (marzo de 2013): 1350006. http://dx.doi.org/10.1142/s1469026813500065.

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In this paper, we present a parallel implementation of the particle swarm optimization (PSO) on graphical processing units (GPU) using CUDA. By fully utilizing the processing power of graphic processors, our implementation (CUDA-PSO) provides a speedup of 167× compared to a sequential implementation on CPU. This speedup is significantly superior to what has been reported in recent papers and is achieved by four optimizations we made to better adapt the parallel algorithm to the specific architecture of the NVIDIA GPU. However, because today's personal computers are usually equipped with a multicore CPU, it may be unfair to compare our CUDA implementation to a sequential one. For this reason, we implemented a parallel PSO for multicore CPUs using MPI (MPI-PSO) and compared its performance against our CUDA-PSO. The execution time of our CUDA-PSO remains 15.8× faster than our MPI-PSO which ran on a high-end 12-core workstation. Moreover, we show with statistical significance that the results obtained using our CUDA-PSO are of equal quality as the results obtained by the sequential PSO or the MPI-PSO. Finally, we use our parallel PSO for real-time harmonic minimization of multilevel power inverters with 20 DC sources while considering the first 100 harmonics and show that our CUDA-PSO is 294× faster than the sequential PSO and 32.5× faster than our parallel MPI-PSO.
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CHANG, C. Y. y K. YAO. "SYSTOLIC ARRAY PROCESSING OF THE SEQUENTIAL DECODING ALGORITHM". International Journal of High Speed Computing 01, n.º 03 (septiembre de 1989): 465–80. http://dx.doi.org/10.1142/s0129053389000251.

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Ha, Ok-Kyoon, Keonpyo Lee, Wan-Jin Kim y Kun Su Yoon. "Effective Parallelization Method for Object Recognition in 2D Sonar Images Based on Task Partitioning". Scientific Programming 2019 (3 de marzo de 2019): 1–9. http://dx.doi.org/10.1155/2019/8908950.

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Techniques for analyzing and avoiding hazardous objects and situations on the seabed are being developed to ensure the safety of ships and submersibles from various hazards. Improvements in accuracy and real-time response are critical for underwater object recognition, which rely on underwater sonar detection to remove noises and analyze the data. Therefore, parallel processing is being introduced for real-time processing of two-dimensional (2D) underwater sonar detector images for seabed monitoring. However, this requires optimized parallel processing between the modules for image processing and the data processing of a vast amount of data. This study proposes an effective parallel processing method, called Task Partitioning, based on central and graphical processing units for monitoring and identifying underwater objects in real time based on 2D-imaging sonar. The practicality of the proposed method is evaluated experimentally by comparing it to the sequential processing method. The experimental results show that the Task Partitioning method significantly improves the processing time for sonar images because it reduces the average execution time to 1% and 5% of the sequential processing method and general parallelization, respectively.
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Tesis sobre el tema "Sequential processing (Computer science)"

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Parashkevov, Atanas. "Advances in space and time efficient model checking of finite state systems". Title page, contents and abstract only, 2002. http://web4.library.adelaide.edu.au/theses/09PH/09php223.pdf.

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Bibliography: leaves 211-220 This thesis examines automated formal verification techniques and their associated space and time implementation complexity when applied to finite state concurrent systems. The focus is on concurrent systems expressed in the Communicating Sequential Processes (CSP) framework. An approach to the compilation of CSP system descriptions into boolean formulae in the form of Ordered Binary Decision Diagrams (OBDD) is presented, further utilised by a basic algorithm that checks a refinement or equivalence relation between a pair of processes in any of the three CSP semantic models. The performance bottlenecks of the basic refinement checking algorithms are identified and addressed with the introduction of a number of novel techniques and algorithms. Algorithms described in this thesis are implemented in the Adelaide Tefinement Checking Tool.
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Bari, Himanshu. "Design and implementation of a library to support the Common Component Architecture (CCA) over Legion". Diss., Online access via UMI:, 2004. http://wwwlib.umi.com/dissertations/fullcit/1424173.

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Zhang, Shujian. "Evaluation in built-in self-test". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp02/NQ34293.pdf.

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Moffat, Nicholas. "Identifying and exploiting symmetry for CSP refinement checking". Thesis, University of Oxford, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.711620.

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Pajic, Slobodan. "Sequential quadratic programming-based contingency constrained optimal power flow". Link to electronic thesis, 2003. http://www.wpi.edu/Pubs/ETD/Available/etd-0430103-152758.

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Simpson, Andrew C. "Safety through security". Thesis, University of Oxford, 1996. http://ora.ox.ac.uk/objects/uuid:4a690347-46af-42a4-91fe-170e492a9dd1.

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In this thesis, we investigate the applicability of the process algebraic formal method Communicating Sequential Processes (CSP) [Hoa85] to the development and analysis of safetycritical systems. We also investigate how these tasks might be aided by mechanical verification, which is provided in the form of the proof tool Failures-Divergences Refinement (FDR) [Ros94]. Initially, we build upon the work of [RWW94, Ros95], in which CSP treatments of the security property of non-interference are described. We use one such formulation to define a property called protection, which unifies our views of safety and security. As well as applying protection to the analysis of safety-critical systems, we develop a proof system for this property, which in conjunction with the opportunity for automated analysis provided by FDR, enables us to apply the approach to problems of a sizable complexity. We then describe how FDR can be applied to the analysis of mutual exclusion, which is a specific form of non-interference. We investigate a number of well-known solutions to the problem, and illustrate how such mutual exclusion algorithms can be interpreted as CSP processes and verified with FDR. Furthermore, we develop a means of verifying the faulttolerance of such algorithms in terms of protection. In turn, mutual exclusion is used to describe safety properties of geographic data associated with Solid State Interlocking (SSI) railway signalling systems. We show how FDR can be used to describe these properties and model interlocking databases. The CSP approach to compositionality allows us to decompose such models, thus reducing the complexity of analysing safety invariants of SSI geographic data. As such, we describe how the mechanical verification of Solid State Interlocking geographic data, which was previously considered to be an intractable problem for the current generation of mechanical verification tools, is computationally feasible using FDR. Thus, the goals of this thesis are twofold. The first goal is to establish a formal encapsulation of a theory of safety-critical systems based upon the relationship which exists between safety and security. The second goal is to establish that CSP, together with FDR, can be applied to the modelling of Solid State Interlocking geographic databases. Furthermore, we shall attempt to demonstrate that such modelling can scale up to large-scale systems.
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Koufogiannakis, Christos. "Approximation algorithms for covering problems". Diss., [Riverside, Calif.] : University of California, Riverside, 2009. http://proquest.umi.com/pqdweb?index=0&did=1957320821&SrchMode=2&sid=1&Fmt=2&VInst=PROD&VType=PQD&RQT=309&VName=PQD&TS=1268338860&clientId=48051.

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Thesis (Ph. D.)--University of California, Riverside, 2009.
Includes abstract. Title from first page of PDF file (viewed March 11, 2010). Available via ProQuest Digital Dissertations. Includes bibliographical references (p. 70-77). Also issued in print.
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Bari, Wasimul. "Analyzing binary longitudinal data in adaptive clinical trials /". Internet access available to MUN users only, 2003. http://collections.mun.ca/u?/theses,167453.

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Thomas, Jonathan. "Asynchronous Validity Resolution in Sequentially Consistent Shared Virtual Memory". Fogler Library, University of Maine, 2001. http://www.library.umaine.edu/theses/pdf/Thomas.pdf.

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Shao, Yang. "Sequential organization in computational auditory scene analysis". Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1190127412.

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Libros sobre el tema "Sequential processing (Computer science)"

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Berman, Kenneth A. Fundamentals of sequential and parallel algorithms. Boston: PWS Pub., 1997.

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Bhavikatti, S. S. Structural optimisation using sequential linear programming. New Delhi: Vikas Publishing House Pvt., 2003.

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Kronsjö, Lydia I. Computational complexity of sequential and parallel algorithms. Chichester: Wiley, 1986.

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Kapralski, Adam. Sequential and parallel processing in depth search machines. Singapore: World Scientific, 1994.

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KEK), Gijutsu Kōryūkai (1995. Gijutsu Kōryūkai hōkokushū: Proceedings of the Meeting on the Technical Study at KEK : KEK, Tsukuba, Japan, November 28-29, 1995. Tsukuba-shi: National Laboratory for High Energy Physics, 1996.

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KEK), Gijutsu Kōryūkai (1998. Gijutsu Kōryūkai hōkokushū: Proceedings of the Meeting on the Technical Study at KEK : KEK, Tsukuba, Japan, February 12-13, 1998. Tsukuba-shi: High Energy Accelerator Research Organization, 1998.

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Kokosiński, Zbigniew. Układy generatorów obiektów kombinatorycznych dla systemów sekwencyjnych i równoległych. Kraków: Politechnika Krakowska im. Tadeusza Kościuszki, 1993.

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Kronsjö, Lydia. Computational complexity of sequential and parallel algorithms. Chichester: Wiley, 1987.

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Kumar, Pradeep. Pattern discovery using sequence data mining: Applications and studies. Hershey, PA: Information Science Reference, 2012.

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Vajteršic, Marián. Algorithms for Elliptic Problems: Efficient Sequential and Parallel Solvers. Dordrecht: Springer Netherlands, 1993.

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Capítulos de libros sobre el tema "Sequential processing (Computer science)"

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Weik, Martin H. "sequential processing". En Computer Science and Communications Dictionary, 1551. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_17020.

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Weik, Martin H. "sequential batch processing". En Computer Science and Communications Dictionary, 1550. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_17006.

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Weik, Martin H. "sequential-by-key processing". En Computer Science and Communications Dictionary, 1550. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_17008.

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Kremer, Stefan C. y John F. Kolen. "Dynamical Recurrent Networks for Sequential Data Processing". En Lecture Notes in Computer Science, 107–22. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/10719871_8.

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Hammerton, James A. y Barry L. Kalman. "Holistic Symbol Processing and the Sequential RAAM: An Evaluation". En Lecture Notes in Computer Science, 298–312. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/10719871_21.

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Koerner, Edgar y Ursula Koerner. "Concurrent parallel-sequential processing in gamma controlled cortical-type networks of spiking neurones". En Lecture Notes in Computer Science, 91–96. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/bfb0020138.

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Grigoryev, Vladimir y Igor Khvorov. "Combined Adaptive Spatial-Temporal Signal Processing System Based on Sequential Circuit with Dependent Component Adaptation". En Lecture Notes in Computer Science, 621–35. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23126-6_56.

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Weik, Martin H. "sequential computer". En Computer Science and Communications Dictionary, 1551. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_17011.

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Weik, Martin H. "sequential". En Computer Science and Communications Dictionary, 1550. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_17002.

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Weik, Martin H. "bit sequential". En Computer Science and Communications Dictionary, 128. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_1629.

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Actas de conferencias sobre el tema "Sequential processing (Computer science)"

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Tinetti, Fernando G., Mónica A. Lopez, Pedro G. Cajaraville y Diego L. Rodrigues. "Fortran Legacy Code Performance Optimization: Sequential and Parallel Processing with OpenMP". En 2009 WRI World Congress on Computer Science and Information Engineering. IEEE, 2009. http://dx.doi.org/10.1109/csie.2009.90.

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Xiaowei Qin y Yan Liu. "Matrix-based multidimensional sequential pattern mining algorithm and application". En 2012 International Conference on Computer Science and Information Processing (CSIP). IEEE, 2012. http://dx.doi.org/10.1109/csip.2012.6308994.

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Badarinath, Rakshith, Kai-Wen Tien y Vittaldas Prabhu. "Unified Control of Production, Capacity, and Pre-Emptive Maintenance of Fused Filament Fabrication Process". En ASME 2018 13th International Manufacturing Science and Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/msec2018-6641.

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The quest for smarter manufacturing is motivating the need for operational decisions to be made in real-time to adapt to uncertainties. Prevailing decision-making techniques typically consider each manufacturing function in isolation to reduce the complexity, which in turn leads to sequential decision-making where prior decisions become constraints for subsequent decisions. This paper proposes a unified approach for simultaneously controlling the timing of production events, the timing of maintenance events, and physical processing capacity. Moreover, the control algorithms can be fully distributed and exploit physics-based models for processes and remaining-useful-life of machinery components in real-time decision-making. Fused Filament Fabrication (FFF) additive manufacturing process is used as an example in the paper to demonstrate the unified approach. Dynamics of the resulting unified control system is modeled using non-linear discontinuous differential equations. Computer simulations are used to illustrate dynamic interactions between production and maintenance functions. Benchmarking of the unified control approach for randomly generated datasets show superior performance compared to other commonly used scheduling heuristics by about 48%.
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Azar, Yossi, Uriel Felge, Michal Feldman y Moshe Tennenholtz. "Sequential decision making with vector outcomes". En ITCS'14: Innovations in Theoretical Computer Science. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2554797.2554817.

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Fried, Dror, Axel Legay, Joël Ouaknine y Moshe Y. Vardi. "Sequential Relational Decomposition". En LICS '18: 33rd Annual ACM/IEEE Symposium on Logic in Computer Science. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3209108.3209203.

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Hsu, William, Jim Warren y Patricia Riddle. "Multivariate Sequential Analytics for Treatment Trajectory Forecasting". En ACSW 2019: Australasian Computer Science Week 2019. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3290688.3290724.

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Blum, Avrim, Jamie Morgenstern, Ankit Sharma y Adam Smith. "Privacy-Preserving Public Information for Sequential Games". En ITCS'15: Innovations in Theoretical Computer Science. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2688073.2688100.

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Chen, Weiru, Shanshan Chen y Yang Zhang. "Structural Relation Sequential Patterns Mining". En 2009 International Conference on Research Challenges in Computer Science (ICRCCS). IEEE, 2009. http://dx.doi.org/10.1109/icrccs.2009.75.

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Gradwohl, Ronen, Noam Livne y Alon Rosen. "Sequential Rationality in Cryptographic Protocols". En 2010 IEEE 51st Annual Symposium on Foundations of Computer Science (FOCS). IEEE, 2010. http://dx.doi.org/10.1109/focs.2010.65.

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"Sequential Recommendation with Recurrent Convolutional Model". En 2019 the 9th International Workshop on Computer Science and Engineering. WCSE, 2019. http://dx.doi.org/10.18178/wcse.2019.06.013.

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Informes sobre el tema "Sequential processing (Computer science)"

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Modlo, Yevhenii O., Serhiy O. Semerikov, Pavlo P. Nechypurenko, Stanislav L. Bondarevskyi, Olena M. Bondarevska y Stanislav T. Tolmachev. The use of mobile Internet devices in the formation of ICT component of bachelors in electromechanics competency in modeling of technical objects. [б. в.], septiembre de 2019. http://dx.doi.org/10.31812/123456789/3264.

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Computer simulation of technical objects and processes is one of the components of the system of professional training of a modern electromechanics engineer. It has been established that despite the fact that mobile Internet devices (MID) are actively used by electrical engineers, the methods of using them in the process of bachelor in electromechanics training is considered only in some domestic scientific studies. The article highlights the components of the methods of using MID in the formation of the ICT component of the competence of the bachelor in electromechanics in modeling of technical objects, providing for students to acquire basic knowledge in the field of Computer Science and modern ICT and skills to use programming systems, math packages, subroutine libraries, and the like. For processing tabular data, it is proposed to use various freely distributed tools that do not significantly differ in functionality, such as Google Sheets, Microsoft Excel, for processing text data – QuickEdit Text Editor, Google Docs, Microsoft Word. For 3D-modeling and viewing the design and technological documentation, the proposed comprehensive use of Autodesk tools in the training process.
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