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Artykuły w czasopismach na temat „Parallel and distributed multi-Level programming”

Autor: Grafiati

Data publikacji: 12 października 2024

Data aktualizacji: 31 lipca 2025

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Yanhaona, Muhammad Nur, Andrew Grimshaw, and Shahriar Hasan Mickey. "HighP5: Programming using Partitioned Parallel Processing Spaces." Journal of the Brazilian Computer Society 30, no. 1 (2024): 653–87. https://doi.org/10.5753/jbcs.2024.4345.

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HighP5 is a new high-level parallel programming language designed to help software developers to achieve three objectives simultaneously: programmer productivity, program portability, and superior program performance. HighP5 enables this by fostering a new programming paradigm that we call hardware-cognizant parallel programming. The paradigm uses a uniform hardware abstraction and a declarative programming syntax to allow programmers to write hardware feature-sensitive efficient programs without delving into the detail of those feature implementations. This paper is the first comprehensive de

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Zhunissov, N. M., A. T. Bayaly, and E. T. Satybaldy. "THE POSSIBILITIES OF USING PARALLEL PROGRAMMING USING PYTHON." Q A Iasaýı atyndaǵy Halyqaralyq qazaq-túrіk ýnıversıtetіnіń habarlary (fızıka matematıka ınformatıka serııasy) 28, no. 1 (2024): 105–14. http://dx.doi.org/10.47526/2024-1/2524-0080.09.

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This article explores the development of parallel software applications using the Python programming language. Parallel programming is becoming increasingly important in the information technology world as multi-core processors and distributed computing become more common. Python provides developers with a variety of tools and libraries for creating parallel applications, including threads, processes, and asynchronous programming. This topic covers the basics of parallel programming in Python, including the principles of thread and process management, error handling, synchronization mechanisms

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Youssef, Bassil. "Implementation of Computational Algorithms using Parallel Programming." International Journal of Trend in Scientific Research and Development 3, no. 3 (2019): 704–10. https://doi.org/10.31142/ijtsrd22947.

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Parallel computing is a type of computation in which many processing are performed concurrently often by dividing large problems into smaller ones that execute independently of each other. There are several different types of parallel computing. The first one is the shared memory architecture which harnesses the power of multiple processors and multiple cores on a single machine and uses threads of programs and shared memory to exchange data. The second type of parallel computing is the distributed architecture which harnesses the power of multiple machines in a networked environment and uses

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Deshpande, Ashish, and Martin Schultz. "Efficient Parallel Programming with Linda." Scientific Programming 1, no. 2 (1992): 177–83. http://dx.doi.org/10.1155/1992/829092.

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Linda is a coordination language inverted by David Gelernter at Yale University, which when combined with a computation language (like C) yields a high-level parallel programming language for MIMD machines. Linda is based on a virtual shared associative memory containing objects called tuples. Skeptics have long claimed that Linda programs could not be efficient on distributed memory architectures. In this paper, we address this claim by discussing C-Linda's performance in solving a particular scientific computing problem, the shallow water equations, and make comparisons with alternatives ava

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RAUBER, THOMAS, and GUDULA RÜNGER. "A DATA RE-DISTRIBUTION LIBRARY FOR MULTI-PROCESSOR TASK PROGRAMMING." International Journal of Foundations of Computer Science 17, no. 02 (2006): 251–70. http://dx.doi.org/10.1142/s0129054106003814.

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Multiprocessor task (M-task) programming is a suitable parallel programming model for coding application problems with an inherent modular structure. An M-task can be executed on a group of processors of arbitrary size, concurrently to other M-tasks of the same application program. The data of a multiprocessor task program usually include composed data structures, like vectors or arrays. For distributed memory machines or cluster platforms, those composed data structures are distributed within one or more processor groups. Thus, a concise parallel programming model for M-tasks requires a stand

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Aversa, R., B. Di Martino, N. Mazzocca, and S. Venticinque. "A Skeleton Based Programming Paradigm for Mobile Multi-Agents on Distributed Systems and Its Realization within the MAGDA Mobile Agents Platform." Mobile Information Systems 4, no. 2 (2008): 131–46. http://dx.doi.org/10.1155/2008/745406.

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Parallel programming effort can be reduced by using high level constructs such as algorithmic skeletons. Within the MAGDA toolset, supporting programming and execution of mobile agent based distributed applications, we provide a skeleton-based parallel programming environment, based on specialization of Algorithmic Skeleton Java interfaces and classes. Their implementation include mobile agent features for execution on heterogeneous systems, such as clusters of WSs and PCs, and support reliability and dynamic workload balancing. The user can thus develop a parallel, mobile agent based applicat

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Wan, Xijun. "Research Overview of Intelligent Computing Platform Technology." Applied and Computational Engineering 151, no. 1 (2025): 41–50. https://doi.org/10.54254/2755-2721/2025.22841.

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With the explosive growth of data and the increasing complexity of computing tasks, traditional computing models can no longer meet the demands. Parallel and distributed processing technologies have become key forces driving innovation in information technology. This paper reviews the research progress of intelligent computing platform technologies, focusing on parallel processing and distributed processing technologies. It primarily examines the basic principles and applications of multi-core processor technology, large-scale parallel algorithms, parallel programming, industrial computer netw

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Gorodnyaya, Lidia. "FUNCTIONAL PROGRAMMING FOR PARALLEL COMPUTING." Bulletin of the Novosibirsk Computing Center. Series: Computer Science, no. 45 (2021): 29–48. http://dx.doi.org/10.31144/bncc.cs.2542-1972.2021.n45.p29-48.

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The paper is devoted to modern trends in the application of functional programming to the problems of organizing parallel computations. Functional programming is considered as a meta-paradigm for solving the problems of developing multi-threaded programs for multiprocessor complexes and distributed systems, as well as for solving the problems associated with rapid IT development. The semantic and pragmatic principles of functional programming and consequences of these principles are described. The paradigm analysis of programming languages and systems is used, which allows assessing their simi

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Spahi, Enis, and D. Altilar. "ITU-PRP: Parallel and Distributed Computing Middleware for Java Developers." International Journal of Business & Technology 3, no. 1 (2014): 2–13. http://dx.doi.org/10.33107/ijbte.2014.3.1.01.

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ITU-PRP provides a Parallel Programming Framework for Java Developers on which they can adapt their sequential application code to operate on a distributed multi-host parallel environment. Developers would implement parallel models, such as Loop Parallelism, Divide and Conquer, Master-Slave and Fork-Join by the help of an API Library provided under framework. Produced parallel applications would be submitted to a middleware called Parallel Running Platform (PRP), on which parallel resources for parallel processing are being organized and performed. The middleware creates Task Plans (TP) accord

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Городняя, Лидия Васильевна. "Perspectives of Functional Programming of Parallel Computations." Russian Digital Libraries Journal 24, no. 6 (2022): 1090–116. http://dx.doi.org/10.26907/1562-5419-2021-24-6-1090-1116.

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The article is devoted to the results of the analysis of modern trends in functional programming, considered as a metaparadigm for solving the problems of organizing parallel computations and multithreaded programs for multiprocessor complexes and distributed systems. Taking into account the multi-paradigm nature of parallel programming, the paradigm analysis of languages and functional programming systems is used. This makes it possible to reduce the complexity of the problems being solved by methods of decomposition of programs into autonomously developed components, to evaluate their simila

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TRINDER, P. W. "Special Issue High Performance Parallel Functional Programming." Journal of Functional Programming 15, no. 3 (2005): 351–52. http://dx.doi.org/10.1017/s0956796805005496.

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Engineering high-performance parallel programs is hard: not only must a correct, efficient and inherently-parallel algorithm be developed, but the computations must be effectively and efficiently coordinated across multiple processors. It has long been recognised that ideas and approaches drawn from functional programming may be particularly applicable to parallel and distributed computing (e.g. Wegner 1971). There are several reasons for this suitability. Concurrent stateless computations are much easier to coordinate, high-level coordination abstractions reduce programming effort, and declar

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LUKE, EDWARD A., and THOMAS GEORGE. "Loci: a rule-based framework for parallel multi-disciplinary simulation synthesis." Journal of Functional Programming 15, no. 3 (2005): 477–502. http://dx.doi.org/10.1017/s0956796805005514.

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We present a rule-based framework for the development of scalable parallel high performance simulations for a broad class of scientific applications (with particular emphasis on continuum mechanics). We take a pragmatic approach to our programming abstractions by implementing structures that are used frequently and have common high performance implementations on distributed memory architectures. The resulting framework borrows heavily from rule-based systems for relational database models, however limiting the scope to those parts that have obvious high performance implementation. Using our ap

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Nayaka, Premkumar S. J., Sunil Kumar, Aniket Singh, and Mohammad Sohail. "MPI for SPH Methods and Parallel Computing on CPUs and GPUs." International Journal of Microsystems and IoT 2, no. 9 (2024): 1162–69. https://doi.org/10.5281/zenodo.14066770.

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Message Passing Interface (MPI) is a standard designed for parallel programming on distributed memory systems, enabling multiple processors to work together by dividing and distributing tasks. This paper presents a comprehensive approach to addressing computational challenges in smoothed particle hydrodynamics (SPH) simulations through a novel MPI-based parallel SPH code. The research emphasizes code optimization for both CPU and GPU architectures, incorporating CUDA parallel programming to enhance GPU performance. Detailed insights into the code design, implementation, algorithm flowchart, an

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POGGI, AGOSTINO, and PAOLA TURCI. "AN AGENT BASED LANGUAGE FOR THE DEVELOPMENT OF DISTRIBUTED SOFTWARE SYSTEMS." International Journal on Artificial Intelligence Tools 05, no. 03 (1996): 347–66. http://dx.doi.org/10.1142/s0218213096000237.

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This paper presents a concurrent object-oriented language, called CUBL, that seems be suitable for the development and maintenance of multi-agent systems. This language is based on objects, called c_units, that act in parallel and communicate with each other through synchronous and asynchronous message passing, and allows the distribution of a program, that is, of its objects on a network of UNIX workstations. This language has been enriched with an agent architecture that offers some of more important features for agent-oriented programming and some advantages as regards the other implemented

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Saint-Jean, A.O. Djungu. "Parallel approximation of RSA encryption." International Journal of Computer Science Issues 17, no. 2 (2020): 19–24. https://doi.org/10.5281/zenodo.3987139.

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RSA is the most popular public key cryptography algorithm. Therefore, one of the major weaknesses of RSA is that it requires a lot of computing time compared to secret hey cryptography algorithms. For example in hardware, some authors claim that RSA is around 1000 times slower than DES (Data Encryption Standard). In addition, current consumer architectures embed several computing units, distributed on processors and possibly on graphics cards. These resources are now easily exploitable thanks to parallel programming interfaces like OpenMP or CUDA. This article proposes parallel versions of RSA

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TSVENGER, I. G. "APPLICATION OF PARALLEL PROGRAMMING METHODS IN SIMINTECH." Herald of Technological University 27, no. 4 (2024): 127–33. http://dx.doi.org/10.55421/1998-7072_2024_27_4_127.

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The article discusses an alternative approach to creating projects that require a large amount of calculations in the SimInTech environment. At the same time, it is proposed to use parallel programming methods and a master/slave model of interaction between projects, as they are more suitable for the tasks of studying and optimizing the parameters of complex systems. In general, parallel programming is becoming increasingly relevant in design systems due to the increase in computer power, the development of parallel computing technologies, the increasing complexity of design systems and the de

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Liu, Rui Tao, and Xiu Jian Lv. "MapReduce-Based Ant Colony Optimization Algorithm for Multi-Dimensional Knapsack Problem." Applied Mechanics and Materials 380-384 (August 2013): 1877–80. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.1877.

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This paper uses MapReduce parallel programming mode to make the Ant Colony Optimization (ACO) algorithm parallel and bring forward the MapReduce-based improved ACO for Multi-dimensional Knapsack Problem (MKP). A variety of techniques, such as change the probability calculation of the timing, roulette, crossover and mutation, are applied for improving the drawback of the ACO and complexity of the algorithm is greatly reduced. It is applied to distributed parallel as to solve the large-scale MKP in cloud computing. Simulation experimental results show that the algorithm can improve the defects o

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Abdessamad, Klilou, and Arsalane Assia. "Parallel implementation of pulse compression method on a multi-core digital signal processor." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 6 (2020): 6541–48. https://doi.org/10.11591/ijece.v10i6.pp6541-6548.

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Pulse compression algorithm is widely used in radar applications. It requires a huge processing power in order to be executed in real time. Therefore, its processing must be distributed along multiple processing units. The present paper proposes a real time platform based on the multi-core digital signal processor (DSP) C6678 from Texas Instruments (TI). The objective of this paper is the optimization of the parallel implementation of pulse compression algorithm over the eight cores of the C6678 DSP. Two parallelization approaches were implemented. The first approach is based on the open multi

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Di Martino, Beniamino, Sergio Briguglio, Gregorio Vlad, and Giuliana Fogaccia. "Workload Decomposition Strategies for Shared Memory Parallel Systems with OpenMP." Scientific Programming 9, no. 2-3 (2001): 109–22. http://dx.doi.org/10.1155/2001/891073.

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A crucial issue in parallel programming (both for distributed and shared memory architectures) is work decomposition. Work decomposition task can be accomplished without large programming effort with use of high-level parallel programming languages, such as OpenMP. Anyway particular care must still be payed on achieving performance goals. In this paper we introduce and compare two decomposition strategies, in the framework of shared memory systems, as applied to a case study particle in cell application. A number of different implementations of them, based on the OpenMP language, are discussed

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Klilou, Abdessamad, and Assia Arsalane. "Parallel implementation of pulse compression method on a multi-core digital signal processor." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 6 (2020): 6541. http://dx.doi.org/10.11591/ijece.v10i6.pp6541-6548.

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Pulse compression algorithm is widely used in radar applications. It requires a huge processing power in order to be executed in real time. Therefore, its processing must be distributed along multiple processing units. The present paper proposes a real time platform based on the multi-core digital signal processor (DSP) C6678 from Texas Instruments (TI). The objective of this paper is the optimization of the parallel implementation of pulse compression algorithm over the eight cores of the C6678 DSP. Two parallelization approaches were implemented. The first approach is based on the open multi

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Czarnul, Paweł, Jerzy Proficz, and Krzysztof Drypczewski. "Survey of Methodologies, Approaches, and Challenges in Parallel Programming Using High-Performance Computing Systems." Scientific Programming 2020 (January 29, 2020): 1–19. http://dx.doi.org/10.1155/2020/4176794.

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This paper provides a review of contemporary methodologies and APIs for parallel programming, with representative technologies selected in terms of target system type (shared memory, distributed, and hybrid), communication patterns (one-sided and two-sided), and programming abstraction level. We analyze representatives in terms of many aspects including programming model, languages, supported platforms, license, optimization goals, ease of programming, debugging, deployment, portability, level of parallelism, constructs enabling parallelism and synchronization, features introduced in recent ve

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Amela, Ramon, Cristian Ramon-Cortes, Jorge Ejarque, Javier Conejero, and Rosa M. Badia. "Executing linear algebra kernels in heterogeneous distributed infrastructures with PyCOMPSs." Oil & Gas Science and Technology – Revue d’IFP Energies nouvelles 73 (2018): 47. http://dx.doi.org/10.2516/ogst/2018047.

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Python is a popular programming language due to the simplicity of its syntax, while still achieving a good performance even being an interpreted language. The adoption from multiple scientific communities has evolved in the emergence of a large number of libraries and modules, which has helped to put Python on the top of the list of the programming languages [1]. Task-based programming has been proposed in the recent years as an alternative parallel programming model. PyCOMPSs follows such approach for Python, and this paper presents its extensions to combine task-based parallelism and thread-

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BAHGAT, REEM, OSAMA MOSTAFA, and GEORGE A. PAPADOPOULOS. "CONCURRENT ABDUCTIVE LOGIC PROGRAMMING IN PANDORA." International Journal on Artificial Intelligence Tools 10, no. 03 (2001): 387–406. http://dx.doi.org/10.1142/s021821300100057x.

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The extension of logic programming with abduction (ALP) allows a form of hypothetical reasoning. The advantages of abduction lie in the ability to reason with incomplete information and the enhancement of the declarative representation of problems. On the other hand, concurrent logic programming is a framework which explores AND-parallelism and/or OR-parallelism in logic programs in order to efficiently execute them on multi-processor / distributed machines. The aim of our work is to study a way to model abduction within the framework of concurrent logic programming, thus taking advantage of t

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Jones, Jeff. "Mechanisms Inducing Parallel Computation in a Model of Physarum polycephalum Transport Networks." Parallel Processing Letters 25, no. 01 (2015): 1540004. http://dx.doi.org/10.1142/s0129626415400046.

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The giant amoeboid organism true slime mould Physarum polycephalum dynamically adapts its body plan in response to changing environmental conditions and its protoplasmic transport network is used to distribute nutrients within the organism. These networks are efficient in terms of network length and network resilience and are parallel approximations of a range of proximity graphs and plane division problems. The complex parallel distributed computation exhibited by this simple organism has since served as an inspiration for intensive research into distributed computing and robotics within the

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Nielsen, Ida M. B., and Curtis L. Janssen. "Multicore Challenges and Benefits for High Performance Scientific Computing." Scientific Programming 16, no. 4 (2008): 277–85. http://dx.doi.org/10.1155/2008/450818.

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Until recently, performance gains in processors were achieved largely by improvements in clock speeds and instruction level parallelism. Thus, applications could obtain performance increases with relatively minor changes by upgrading to the latest generation of computing hardware. Currently, however, processor performance improvements are realized by using multicore technology and hardware support for multiple threads within each core, and taking full advantage of this technology to improve the performance of applications requires exposure of extreme levels of software parallelism. We will her

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Huang, Xiaobing, Tian Zhao, and Yu Cao. "PIR." International Journal of Multimedia Data Engineering and Management 5, no. 3 (2014): 1–27. http://dx.doi.org/10.4018/ijmdem.2014070101.

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Multimedia Information Retrieval (MIR) is a problem domain that includes programming tasks such as salient feature extraction, machine learning, indexing, and retrieval. There are a variety of implementations and algorithms for these tasks in different languages and frameworks, which are difficult to compose and reuse due to the interface and language incompatibility. Due to this low reusability, researchers often have to implement their experiments from scratch and the resulting programs cannot be easily adapted to parallel and distributed executions, which is important for handling large dat

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Silva, Luis M., JoÃo Gabriel Silva, and Simon Chapple. "Implementation and Performance of DSMPI." Scientific Programming 6, no. 2 (1997): 201–14. http://dx.doi.org/10.1155/1997/452521.

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Distributed shared memory has been recognized as an alternative programming model to exploit the parallelism in distributed memory systems because it provides a higher level of abstraction than simple message passing. DSM combines the simple programming model of shared memory with the scalability of distributed memory machines. This article presents DSMPI, a parallel library that runs atop of MPI and provides a DSM abstraction. It provides an easy-to-use programming interface, is fully, portable, and supports heterogeneity. For the sake of flexibility, it supports different coherence protocols

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Fan, Wenfei, Tao He, Longbin Lai, et al. "GraphScope." Proceedings of the VLDB Endowment 14, no. 12 (2021): 2879–92. http://dx.doi.org/10.14778/3476311.3476369.

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GraphScope is a system and a set of language extensions that enable a new programming interface for large-scale distributed graph computing. It generalizes previous graph processing frameworks (e.g. , Pregel, GraphX) and distributed graph databases ( e.g ., Janus-Graph, Neptune) in two important ways: by exposing a unified programming interface to a wide variety of graph computations such as graph traversal, pattern matching, iterative algorithms and graph neural networks within a high-level programming language; and by supporting the seamless integration of a highly optimized graph engine in

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Sapaty, P. S. "A language to comprehend and manage distributed worlds." Mathematical machines and systems 3 (2022): 9–27. http://dx.doi.org/10.34121/1028-9763-2022-3-9-27.

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The paper presents and discusses the details of the Spatial Grasp Language (SGL), including its philosophy, methodology, syntax, semantics, and implementation in distributed systems. As a key element of the developed Spatial Grasp Model and Technology, SGL has been used in nu-merous applications and publications, including seven books. This inspired us to devote the cur-rent paper exclusively to the main features of this language and comparison with other lan-guages as a tribute to its impact on the Distributed Management Project at the National Acade-my of Sciences, with strong international

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Ramon-Cortes, Cristian, Ramon Amela, Jorge Ejarque, Philippe Clauss, and Rosa M. Badia. "AutoParallel: Automatic parallelisation and distributed execution of affine loop nests in Python." International Journal of High Performance Computing Applications 34, no. 6 (2020): 659–75. http://dx.doi.org/10.1177/1094342020937050.

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The last improvements in programming languages and models have focused on simplicity and abstraction; leading Python to the top of the list of the programming languages. However, there is still room for improvement when preventing users from dealing directly with distributed and parallel computing issues. This paper proposes and evaluates AutoParallel, a Python module to automatically find an appropriate task-based parallelisation of affine loop nests and execute them in parallel in a distributed computing infrastructure. It is based on sequential programming and contains one single annotation

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FRÜHWIRTH, THOM. "Parallelism, concurrency and distribution in constraint handling rules: A survey." Theory and Practice of Logic Programming 18, no. 5-6 (2018): 759–805. http://dx.doi.org/10.1017/s1471068418000078.

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AbstractConstraint Handling Rules (CHR) is both an effective concurrent declarative programming language and a versatile computational logic formalism. In CHR, guarded reactive rules rewrite a multi-set of constraints. Concurrency is inherent, since rules can be applied to the constraints in parallel. In this comprehensive survey, we give an overview of the concurrent, parallel as well as distributed CHR semantics, standard and more exotic, that have been proposed over the years at various levels of refinement. These semantics range from the abstract to the concrete. They are related by formal

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Yang, Guoshan, Xumin Liu, Wei Zhang, and Zhengxiong Ma. "Multi-stage planning and calculation method of power system considering energy storage selection." Journal of Physics: Conference Series 2814, no. 1 (2024): 012037. http://dx.doi.org/10.1088/1742-6596/2814/1/012037.

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Abstract Under new power system flexibility, this text proposes a multi-stage random generation-transmission-energy storage, integrated programming method that considers the short-period flexibility demand. The model can accurately reflect the relationship between short-period operation and long-period uncertainty within an extraordinary method and can also correctly evaluate the value of investment flexibility. Based on this, this text proposes a parallel processing solution, which can be separated into subproblems through column generation and shared decomposition and enables simulation calc

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Liu, Gao Ming, Xiao Bo Wang, Wei Song, and Chong Zhan Li. "The Hybrid Parallel Algorithm of Online Verification Based on P2P." Applied Mechanics and Materials 373-375 (August 2013): 1251–55. http://dx.doi.org/10.4028/www.scientific.net/amm.373-375.1251.

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Taking into account the gradually expanded scale of large interconnected power system, especially the UHV synchronous grid successfully puts into operation. Traditional centralized computing will encounter the bottleneck of hardware computing power. A protection setting online checking hybrid parallel algorithm based on P2P is proposed. Peer-to-peer communications using P2P network technology to achieve inter-regional information fast interactive. The design of MPI+OpenMP hybrid parallel programming models and algorithms is emphatically introduced. Online checking two levels parallel of proces

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Cook, Sebastien, and Paulo Garcia. "Arbitrarily Parallelizable Code: A Model of Computation Evaluated on a Message-Passing Many-Core System." Computers 11, no. 11 (2022): 164. http://dx.doi.org/10.3390/computers11110164.

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The number of processing elements per solution is growing. From embedded devices now employing (often heterogeneous) multi-core processors, across many-core scientific computing platforms, to distributed systems comprising thousands of interconnected processors, parallel programming of one form or another is now the norm. Understanding how to efficiently parallelize code, however, is still an open problem, and the difficulties are exacerbated across heterogeneous processing, and especially at run time, when it is sometimes desirable to change the parallelization strategy to meet non-functional

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Finnerty, Patrick, Yoshiki Kawanishi, Tomio Kamada, and Chikara Ohta. "Supercharging the APGAS Programming Model with Relocatable Distributed Collections." Scientific Programming 2022 (September 21, 2022): 1–27. http://dx.doi.org/10.1155/2022/5092422.

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In this article, we present our relocatable distributed collection library. Building on top of the AGPAS for Java library, we provide a number of useful intranode parallel patterns as well as the features necessary to support the distributed nature of the computation through clearly identified methods. In particular, the transfer of distributed collections’ entries between processes is supported via an integrated relocation system. This enables dynamic load-balancing capabilities, making it possible for programs to adapt to uneven or evolving cluster performance. The system we developed makes

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Seki, Kazuhiro, Ryota Jinno, and Kuniaki Uehara. "Parallel Distributed Trajectory Pattern Mining Using Hierarchical Grid with MapReduce." International Journal of Grid and High Performance Computing 5, no. 4 (2013): 79–96. http://dx.doi.org/10.4018/ijghpc.2013100106.

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This paper proposes a new approach to trajectory pattern mining, which attempts to discover frequent movement patterns from the trajectories of moving objects. For dealing with a large volume of trajectory data, traditional approaches quantize them by a grid with a fixed resolution. However, an appropriate resolution often varies across different areas of trajectories. Simply increasing the resolution cannot capture broad patterns and consumes unnecessarily large computational resources. To solve the problem, the authors propose a hierarchical grid-based approach with quadtree search. The appr

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Otto, Steve W. "Parallel Array Classes and Lightweight Sharing Mechanisms." Scientific Programming 2, no. 4 (1993): 203–16. http://dx.doi.org/10.1155/1993/393409.

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We discuss a set of parallel array classes, MetaMP, for distributed-memory architectures. The classes are implemented in C++ and interface to the PVM or Intel NX message-passing systems. An array class implements a partitioned array as a set of objects distributed across the nodes – a "collective" object. Object methods hide the low-level message-passing and implement meaningful array operations. These include transparent guard strips (or sharing regions) that support finite-difference stencils, reductions and multibroadcasts for support of pivoting and row operations, and interpolation/contra

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Sahu, Muktikanta, Rupjit Chakraborty, and Gopal Krishna Nayak. "A task-level parallelism approach for process discovery." International Journal of Engineering & Technology 7, no. 4 (2018): 2446. http://dx.doi.org/10.14419/ijet.v7i4.14748.

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Building process models from the available data in the event logs is the primary objective of Process discovery. Alpha algorithm is one of the popular algorithms accessible for ascertaining a process model from the event logs in process mining. The steps involved in the Alpha algorithm are computationally rigorous and this problem further manifolds with the exponentially increasing event log data. In this work, we have exploited task parallelism in the Alpha algorithm for process discovery by using MPI programming model. The proposed work is based on distributed memory parallelism available in

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KAKULAVARAPU, PRASAD, OLIVIER C. MAQUELIN, JOSÉ NELSON AMARAL, and GUANG R. GAO. "DYNAMIC LOAD BALANCERS FOR A MULTITHREADED MULTIPROCESSOR SYSTEM." Parallel Processing Letters 11, no. 01 (2001): 169–84. http://dx.doi.org/10.1142/s0129626401000506.

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Designing multi-processor systems that deliver a reasonable price-performance ratio using off-the-shelf processor and compiler technologies is a major challenge. For an important class of applications, it is critical to explore fine-grain parallelism to achieve reasonable performance. In such parallel systems it is essential to efficiently manage communication latencies, bandwidth, and synchronization overheads. In this paper we study load balancing strategies for the runtime system of a multi-threaded system. EARTH (Efficient Architecture for Running Threads) is a multi-threaded programming a

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Haveraaen, Magne. "Machine and Collection Abstractions for User-Implemented Data-Parallel Programming." Scientific Programming 8, no. 4 (2000): 231–46. http://dx.doi.org/10.1155/2000/485607.

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Data parallelism has appeared as a fruitful approach to the parallelisation of compute-intensive programs. Data parallelism has the advantage of mimicking the sequential (and deterministic) structure of programs as opposed to task parallelism, where the explicit interaction of processes has to be programmed. In data parallelism data structures, typically collection classes in the form of large arrays, are distributed on the processors of the target parallel machine. Trying to extract distribution aspects from conventional code often runs into problems with a lack of uniformity in the use of th

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DATTOLO, ANTONINA, and VINCENZO LOIA. "DISTRIBUTED INFORMATION AND CONTROL IN A CONCURRENT HYPERMEDIA-ORIENTED ARCHITECTURE." International Journal of Software Engineering and Knowledge Engineering 10, no. 03 (2000): 345–69. http://dx.doi.org/10.1142/s0218194000000158.

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The market for parallel and distributed computing systems keeps growing. Technological advances in processor power, networking, telecommunication and multimedia are stimulating the development of applications requiring parallel and distributed computing. An important research problem in this area is the need to find a robust bridge between the decentralisation of knowledge sources in information-based systems and the distribution of computational power. Consequently, the attention of the research community has been directed towards high-level, concurrent, distributed programming. This work pro

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Piotrowski, M., G. A. McGilvary, M. Mewissen, et al. "Exploiting Parallel R in the Cloud with SPRINT." Methods of Information in Medicine 52, no. 01 (2013): 80–90. http://dx.doi.org/10.3414/me11-02-0039.

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SummaryBackground: Advances in DNA Microarray devices and next-generation massively parallel DNA sequencing platforms have led to an exponential growth in data availability but the arising opportunities require adequate computing resources. High Performance Computing (HPC) in the Cloud offers an affordable way of meeting this need.Objectives: Bioconductor, a popular tool for high-throughput genomic data analysis, is distributed as add-on modules for the R statistical programming language but R has no native capabilities for exploiting multiprocessor architectures. SPRINT is an R package that e

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Huh, Joonmoo, and Deokwoo Lee. "Effective On-Chip Communication for Message Passing Programs on Multi-Core Processors." Electronics 10, no. 21 (2021): 2681. http://dx.doi.org/10.3390/electronics10212681.

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Shared memory is the most popular parallel programming model for multi-core processors, while message passing is generally used for large distributed machines. However, as the number of cores on a chip increases, the relative merits of shared memory versus message passing change, and we argue that message passing becomes a viable, high performing, and parallel programming model. To demonstrate this hypothesis, we compare a shared memory architecture with a new message passing architecture on a suite of applications tuned for each system independently. Perhaps surprisingly, the fundamental beha

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Sujit R Wakchaure, Et al. "MR-AT: Map Reduce based Apriori Technique for Sequential Pattern Mining using Big Data in Hadoop." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 9 (2023): 4258–67. http://dx.doi.org/10.17762/ijritcc.v11i9.9877.

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One of the most well-known and widely implemented data mining methods is Apriori algorithm which is responsible for mining frequent item sets. The effectiveness of the Apriori algorithm has been improved by a number of algorithms that have been introduced on both parallel and distributed platforms in recent years. They are distinct from one another on account of the method of load balancing, memory system, method of data degradation, and data layout that was utilised in their implementation. The majority of the issues that arise with distributed frameworks are associated with the operating cos

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Cieplak, Tomasz, Tomasz Rymarczyk, and Grzegorz Kłosowski. "USING MICROSERVICES ARCHITECTURE AS ANALYTICAL SYSTEM FOR ELECTRICAL IMPEDANCE TOMOGRAPHY IMAGING." Informatics Control Measurement in Economy and Environment Protection 8, no. 1 (2018): 52–55. http://dx.doi.org/10.5604/01.3001.0010.8652.

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An image reconstruction with use of EIT method has been found useful in many areas of medical, industrial and environmental applications. Papers show that computational systems used for image reconstructions are utilizing parallel and distributed computations and multi-tier architecture, as well as monolithic architecture. The aim of our research is to define an analytical system architecture that will be able to combine a variety of image reconstruction algorithms with their representations in different programming languages. Based on examples described in different proceedings and research p

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Liu, Zonglin, and Olaf Stursberg. "Distributed control of networked systems with coupling constraints." at - Automatisierungstechnik 67, no. 12 (2019): 1007–18. http://dx.doi.org/10.1515/auto-2019-0085.

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Abstract This paper proposes algorithms for the distributed solution of control problems for networked systems with coupling constraints. This type of problem is practically relevant, e. g., for subsystems which share common resources, or need to go through a bottleneck, while considering non-convex state constraints. Centralized solution schemes, which typically first cast the non-convexities into mixed-integer formulations that are then solved by mixed-integer programming, suffer from high computational complexity for larger numbers of subsystems. The distributed solution proposed in this pa

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Pryadko, S. A., A. S. Krutogolova, A. S. Uglyanitsa, and A. E. Ivanov. "Multi-core processors use for numerical problems solutions." Radio industry (Russia) 30, no. 4 (2020): 98–105. http://dx.doi.org/10.21778/2413-9599-2020-30-4-98-105.

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Problem statement. The use of programming technologies on modern multicore systems is an integral part of an enterprise whose activities involve multitasking or the need to make a large number of calculations over a certain time. The article discusses the development of such technologies aimed at increasing the speed of solving various issues, for example, numerical modeling.Objective. Search for alternative ways to increase the speed of calculations by increasing the number of processors. As an example of increasing the calculation speed depending on the number of processors, the well-known h

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Prudhvi Naayini, Prudhvi Naayini. "Parallel Computing Data Processing: Frameworks, Implementations, and Case Studies." International Journal of Advances in Engineering and Management 7, no. 4 (2025): 405–15. https://doi.org/10.35629/5252-0704405415.

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Parallelcomputinghasbecomefundamentalinprocessing the massive data volumes generated in modern science andindustry.Thispaperpresentsacomprehensivesurv ey and practical review of parallel computing in data processing, examining key frameworks (MPI, OpenMP, CUDA, Hadoop MapReduce, Apache Spark, etc.), implementations, and real- world case studies. We discuss the architectures underlying shared-memory and distributed-memory systems and illustrate how parallelism on CPUs and GPUs is exploited for highperformancecomputing(HPC)andbigdataanalytics. Wereview theoretical foundations (including Amdahl’s

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Mochurad, L. I., and M. V. Mamchur. "PARALLEL AND DISTRIBUTED COMPUTING TECHNOLOGIES FOR AUTONOMOUS VEHICLE NAVIGATION." Radio Electronics, Computer Science, Control, no. 4 (January 3, 2024): 111. http://dx.doi.org/10.15588/1607-3274-2023-4-11.

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Context. Autonomous vehicles are becoming increasingly popular, and one of the important modern challenges in their development is ensuring their effective navigation in space and movement within designated lanes. This paper examines a method of spatial orientation for vehicles using computer vision and artificial neural networks. The research focused on the navigation system of an autonomous vehicle, which incorporates the use of modern distributed and parallel computing technologies. Objective. The aim of this work is to enhance modern autonomous vehicle navigation algorithms through p

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Zsók, Viktória, and Zoltán Porkoláb. "Rapid prototyping for distributed D-Clean using C++ templates." Annales Universitatis Scientiarum Budapestinensis de Rolando Eötvös Nominatae. Sectio computatorica, no. 37 (2012): 19–46. https://doi.org/10.71352/ac.37.019.

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Earlier we have designed two coordination languages, D-Clean and D-Box for high-level process description and communication coordination of functional programs distributed over a cluster. D-Clean is the high level coordination language for functional distributed computations. The language coordinates the pure functional computational nodes required by language primitives, and it controls the dataflow in a distributed processnetwork. In order to achieve parallel features, D-Clean extends the lazy functional programming language Clean with new language primitives. Every D-Clean construct generat

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