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Journal articles on the topic 'Distributed Parallel Application'

Author: Grafiati

Published: 28 September 2024

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1

Spahi, Enis, and D. Altilar. "ITU-PRP: Parallel and Distributed Computing Middleware for Java Developers." International Journal of Business & Technology 3, no. 1 (November 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) according to application’s parallel model, assigns best available resource Hosts, in order to perform fast parallel processing. Task Plans will be created dynamically in real time according to resources actual utilization status or availability, instead of predefined/preconfigured task plans. ITU-PRP achieves better efficiency on parallel processing over big data sets and distributes divided base data to multiple hosts to be operated by Coarse-Grained parallelism. According to this model distributed parallel tasks would operate independently with minimal interaction until processing ends.

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Sikora, Andrzej, and Ewa Niewiadomska-Szynkiewicz. "Parallel and Distributed Simulation of Ad Hoc Networks." Journal of Telecommunications and Information Technology, no. 3 (June 26, 2023): 76–84. http://dx.doi.org/10.26636/jtit.2009.3.943.

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Modeling and simulation are traditional methods used to evaluate wireless network design. This paper addresses issues associated with the application of parallel discrete event simulation to mobile ad hoc networks design and analysis. The basic characteristics and major issues pertaining to ad hoc networks modeling and simulation are introduced. The focus is on wireless transmission and mobility models. Particular attention is paid to the MobASim system, a Javabased software environment for parallel and distributed simulation of mobile ad hoc networks. We describe the design, performance and possible applications of presented simulation software.

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César, Eduardo, Anna Morajko, Tomàs Margalef, Joan Sorribes, Antonio Espinosa, and Emilio Luque. "Dynamic Performance Tuning Supported by Program Specification." Scientific Programming 10, no. 1 (2002): 35–44. http://dx.doi.org/10.1155/2002/549617.

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Performance analysis and tuning of parallel/distributed applications are very difficult tasks for non-expert programmers. It is necessary to provide tools that automatically carry out these tasks. These can be static tools that carry out the analysis on a post-mortem phase or can tune the application on the fly. Both kind of tools have their target applications. Static automatic analysis tools are suitable for stable application while dynamic tuning tools are more appropriate to applications with dynamic behaviour. In this paper, we describe KappaPi as an example of a static automatic performance analysis tool, and also a general environment based on parallel patterns for developing and dynamically tuning parallel/distributed applications.

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VADHIYAR, SATHISH S., and JACK J. DONGARRA. "SRS: A FRAMEWORK FOR DEVELOPING MALLEABLE AND MIGRATABLE PARALLEL APPLICATIONS FOR DISTRIBUTED SYSTEMS." Parallel Processing Letters 13, no. 02 (June 2003): 291–312. http://dx.doi.org/10.1142/s0129626403001288.

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The ability to produce malleable parallel applications that can be stopped and reconfigured during the execution can offer attractive benefits for both the system and the applications. The reconfiguration can be in terms of varying the parallelism for the applications, changing the data distributions during the executions or dynamically changing the software components involved in the application execution. In distributed and Grid computing systems, migration and reconfiguration of such malleable applications across distributed heterogeneous sites which do not share common file systems provides flexibility for scheduling and resource management in such distributed environments. The present reconfiguration systems do not support migration of parallel applications to distributed locations. In this paper, we discuss a framework for developing malleable and migratable MPI message-passing parallel applications for distributed systems. The framework includes a user-level checkpointing library called SRS and a runtime support system that manages the checkpointed data for distribution to distributed locations. Our experiments and results indicate that the parallel applications, with instrumentation to SRS library, were able to achieve reconfigurability incurring about 15-35% overhead.

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Ogle, D. M., K. Schwan, and R. Snodgrass. "Application-dependent dynamic monitoring of distributed and parallel systems." IEEE Transactions on Parallel and Distributed Systems 4, no. 7 (July 1993): 762–78. http://dx.doi.org/10.1109/71.238299.

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Čiegis, Raimondas, Vadimas Starikovičius, Natalija Tumanova, and Minvydas Ragulskis. "Application of distributed parallel computing for dynamic visual cryptography." Journal of Supercomputing 72, no. 11 (May 4, 2016): 4204–20. http://dx.doi.org/10.1007/s11227-016-1733-8.

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7

Chi, Song. "Application of MATLAB Parallel Programming Technology." Applied Mechanics and Materials 602-605 (August 2014): 3787–90. http://dx.doi.org/10.4028/www.scientific.net/amm.602-605.3787.

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The parallel application program development technology and process is analyzed based on the MATLAB parallel and distributed computing toolbox. Hereby, the comparison of the serial computing and the parallel computing is done by computer simulations, and the parallel computing program design and develop method is proposed. The simulations results show that, the parallel computing technology has many advantages in the calculation of high intensive and it is convenience of the parallel application development using MATLAB.

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8

Prylli, L., and B. Tourancheau. "Execution-Driven Simulation of Parallel Applications." Parallel Processing Letters 08, no. 01 (March 1998): 95–109. http://dx.doi.org/10.1142/s0129626498000122.

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This paper presents our work on the simulation of distributed memory parallel computers. We design a distributed simulator that takes as input an application written for a MIMD computer and run it on a workstations cluster with just a recompilation of the code. The hardware of the target machine is simulated so that the behavior of the application is identical to a native run on the simulated computer with virtual timings and trace file. Moreover, our analysis sets up the conditions required to achieve a good speedup as a function of the number of simulation hosts, the network latency and the granularity of the application.

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MORAJKO, ANNA, OLEG MORAJKO, JOSEP JORBA, TOMÀS MARGALEF, and EMILIO LUQUE. "AUTOMATIC PERFORMANCE ANALYSIS AND DYNAMIC TUNING OF DISTRIBUTED APPLICATIONS." Parallel Processing Letters 13, no. 02 (June 2003): 169–87. http://dx.doi.org/10.1142/s0129626403001227.

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The classical way of tuning parallel/distributed applications is based on the analysis of the monitoring information obtained from an execution of the application. However, this "measure and modify" approach is not feasible when the applications have a dynamic behavior. In this case, another approach is required to accomplish performance expectations. This paper presents a solution based on the dynamic tuning approach that addresses these issues. In this approach, an application is monitored, its performance bottlenecks are detected and the application is modified automatically during the execution, without stopping, recompiling or re-running it. The introduced modifications adapt the behavior of the application to dynamic variations.

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10

Sakariya, Harsh Bipinbhai, and Ganesh D. "Taxonomy of Load Balancing Strategies in Distributed Systems." International Journal of Innovative Research in Computer and Communication Engineering 12, no. 03 (March 25, 2024): 1796–802. http://dx.doi.org/10.15680/ijircce.2024.1203070.

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Large-scale parallel and distributed computing systems are becoming more popular as a result of falling hardware prices and improvements in computer networking technologies. Improved performance and resource sharing are potential benefits of distributed computing systems. We have provided a summary of distributed computing in this essay. The differences between parallel and distributed computing, terms related to distributed computing, task distribution in distributed computing, performance metrics in distributed computing systems, parallel distributed algorithm models, benefits of distributed computing, and distributed computing's application domain were all covered in this paper.

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11

Olszewski, Jan. "A flexible thinning algorithm allowing parallel, sequential, and distributed application." ACM Transactions on Mathematical Software 18, no. 1 (March 1992): 35–45. http://dx.doi.org/10.1145/128745.128748.

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Beg, M. M. Sufyan, and C. P. Ravikumar. "Application of Parallel and Distributed Data Mining in e-Commerce." IETE Technical Review 17, no. 4 (July 2000): 189–95. http://dx.doi.org/10.1080/02564602.2000.11416902.

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13

Li, Jinghong, Guoqi Xie, Keqin Li, and Zhuo Tang. "Enhanced Parallel Application Scheduling Algorithm with Energy Consumption Constraint in Heterogeneous Distributed Systems." Journal of Circuits, Systems and Computers 28, no. 11 (October 2019): 1950190. http://dx.doi.org/10.1142/s0218126619501901.

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Energy consumption has always been one of the main design problems in heterogeneous distributed systems, whether for large cluster computer systems or small handheld terminal devices. And as energy consumption explodes for complex performance, many efforts and work are focused on minimizing the schedule length of parallel applications that meet the energy consumption constraints currently. In prior studies, a pre-allocation method based on dynamic voltage and frequency scaling (DVFS) technology allocates unassigned tasks with minimal energy consumption. However, this approach does not necessarily result in minimal scheduling length. In this paper, we propose an enhanced scheduling algorithm, which allocates the same energy consumption for each task by selecting a relatively intermediate value among the unequal allocations. Based on the two real-world applications (Fast Fourier transform and Gaussian elimination) and the randomly generated parallel application, experiments show that the proposed algorithm not only achieves better scheduling length while meeting the energy consumption constraints, but also has better performance than the existing parallel algorithms.

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Mubarak, Misbah, Seegyoung Seol, Qiukai Lu, and Mark S. Shephard. "A Parallel Ghosting Algorithm for The Flexible Distributed Mesh Database." Scientific Programming 21, no. 1-2 (2013): 17–42. http://dx.doi.org/10.1155/2013/654971.

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Critical to the scalability of parallel adaptive simulations are parallel control functions including load balancing, reduced inter-process communication and optimal data decomposition. In distributed meshes, many mesh-based applications frequently access neighborhood information for computational purposes which must be transmitted efficiently to avoid parallel performance degradation when the neighbors are on different processors. This article presents a parallel algorithm of creating and deleting data copies, referred to as ghost copies, which localize neighborhood data for computation purposes while minimizing inter-process communication. The key characteristics of the algorithm are: (1) It can create ghost copies of any permissible topological order in a 1D, 2D or 3D mesh based on selected adjacencies. (2) It exploits neighborhood communication patterns during the ghost creation process thus eliminating all-to-all communication. (3) For applications that need neighbors of neighbors, the algorithm can creatennumber of ghost layers up to a point where the whole partitioned mesh can be ghosted. Strong and weak scaling results are presented for the IBM BG/P and Cray XE6 architectures up to a core count of 32,768 processors. The algorithm also leads to scalable results when used in a parallel super-convergent patch recovery error estimator, an application that frequently accesses neighborhood data to carry out computation.

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Chen, Wenjie, Qiliang Yang, Ziyan Jiang, Jianchun Xing, Shuo Zhao, Qizhen Zhou, Deshuai Han, and Bowei Feng. "SwarmL: A Language for Programming Fully Distributed Intelligent Building Systems." Buildings 13, no. 2 (February 12, 2023): 499. http://dx.doi.org/10.3390/buildings13020499.

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Fully distributed intelligent building systems can be used to effectively reduce the complexity of building automation systems and improve the efficiency of the operation and maintenance management because of its self-organization, flexibility, and robustness. However, the parallel computing mode, dynamic network topology, and complex node interaction logic make application development complex, time-consuming, and challenging. To address the development difficulties of fully distributed intelligent building system applications, this paper proposes a user-friendly programming language called SwarmL. Concretely, SwarmL (1) establishes a language model, an overall framework, and an abstract syntax that intuitively describes the static physical objects and dynamic execution mechanisms of a fully distributed intelligent building system, (2) proposes a physical field-oriented variable that adapts the programming model to the distributed architectures by employing a serial programming style in accordance with human thinking to program parallel applications of fully distributed intelligent building systems for reducing programming difficulty, (3) designs a computational scope-based communication mechanism that separates the computational logic from the node interaction logic, thus adapting to dynamically changing network topologies and supporting the generalized development of the fully distributed intelligent building system applications, and (4) implements an integrated development tool that supports program editing and object code generation. To validate SwarmL, an example application of a real scenario and a subject-based experiment are explored. The results demonstrate that SwarmL can effectively reduce the programming difficulty and improve the development efficiency of fully distributed intelligent building system applications. SwarmL enables building users to quickly understand and master the development methods of application tasks in fully distributed intelligent building systems, and supports the intuitive description and generalized, efficient development of application tasks. The created SwarmL support tool supports the downloading and deployment of applications for fully distributed intelligent building systems, which can improve the efficiency of building control management and promote the application and popularization of new intelligent building systems.

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Agrawal, Amrit, and Pranay Chaudhuri. "An Algorithm for Task Scheduling in Heterogeneous Distributed Systems Using Task Duplication." International Journal of Grid and High Performance Computing 3, no. 1 (January 2011): 89–97. http://dx.doi.org/10.4018/jghpc.2011010105.

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Task scheduling in heterogeneous parallel and distributed computing environment is a challenging problem. Applications identified by parallel tasks can be represented by directed-acyclic graphs (DAGs). Scheduling refers to the assignment of these parallel tasks on a set of bounded heterogeneous processors connected by high speed networks. Since task assignment is an NP-complete problem, instead of finding an exact solution, scheduling algorithms are developed based on heuristics, with the primary goal of minimizing the overall execution time of the application or schedule length. In this paper, the overall execution time (schedule length) of the tasks is reduced using task duplication on top of the Critical-Path-On-a-Processor (CPOP) algorithm.

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Chard, Kyle, James Muns, Richard Wai, and S. Tucker Taft. "Language support for parallel and distributed computing." ACM SIGAda Ada Letters 40, no. 2 (April 27, 2021): 51–54. http://dx.doi.org/10.1145/3463478.3463481.

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Language constructs that support parallel computing are relatively well recognized at this point, with features such as parallel loops (optionally with reduction operators), divide-and-conquer parallelism, and general parallel blocks. But what language features would make distributed computing safer and more productive? Is it helpful to be able to specify on what node a computation should take place, and on what node data should reside, or is that overspecification? We don't normally expect a user of a parallel programming language to specify what core is used for a given iteration of a loop, nor which data should be moved into which core's cache. Generally the compiler and the run-time manage the allocation of cores, and the hardware worries about the cache. But in a distributed world, communication costs can easily outweigh computation costs in a poorly designed application. This panel will discuss various language features, some of which already exist to support parallel computing, and how they could be enhanced or generalized to support distributed computing safely and efficiently.

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18

DUTOT, PIERRE-FRANÇOIS, LIONEL EYRAUD, GRÉGORY MOUNIÉ, and DENIS TRYSTRAM. "SCHEDULING ON LARGE SCALE DISTRIBUTED PLATFORMS: FROM MODELS TO IMPLEMENTATIONS." International Journal of Foundations of Computer Science 16, no. 02 (April 2005): 217–37. http://dx.doi.org/10.1142/s0129054105002954.

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Today, large scale parallel systems are available at low cost, Many powerful such systems have been installed all over the world and the number of users is always increasing. The difficulty of using them efficiently is growing with the complexity of the interactions between more and more architectural constraints and the diversity of the applications. The design of efficient parallel algorithms has to be reconsidered under the influence of new parameters of such platforms (namely, cluster, grid and global computing) which are characterized by a larger number of heterogeneous processors, often organized in several hierarchical sub-systems. At each step of the evolution of the parallel processing field, researchers designed adequate computational models whose objective was to abstract the real world in order to be able to analyze the behavior of algorithms. In this paper, we will investigate two complementary computational models that have been proposed recently: Parallel Task (PT) and Divisible Load (DL). The Parallel Task (i.e. tasks that require more than one processor for their execution) model is a promising alternative for scheduling parallel applications, especially in the case of slow communication media. The basic idea is to consider the application at a coarse level of granularity. Another way of looking at the problem (which is somehow a dual view) is the Divisible Load model where an application is considered as a collection of a large number of elementary – sequential – computing units that will be distributed among the available resources. Unlike the PT model, the DL model corresponds to a fine level of granularity. We will focus on the PT model, and discuss how to mix it with simple Divisible Load scheduling. As the main difficulty for distributing the load among the processors (usually known as the scheduling problem) in actual systems comes from handling efficiently the communications, these two models of the problem allow us to consider them implicitly or to mask them, thus leading to more tractable problems. We will show that in spite of the enormous complexity of the general scheduling problem on new platforms, it is still useful to study theoretical models. We will focus on the links between models and actual implementations on a regional grid with more than 500 processors.

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19

Janssen, Curtis L., Helgi Adalsteinsson, Scott Cranford, Joseph P. Kenny, Ali Pinar, David A. Evensky, and Jackson Mayo. "A Simulator for Large-Scale Parallel Computer Architectures." International Journal of Distributed Systems and Technologies 1, no. 2 (April 2010): 57–73. http://dx.doi.org/10.4018/jdst.2010040104.

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Efficient design of hardware and software for large-scale parallel execution requires detailed understanding of the interactions between the application, computer, and network. The authors have developed a macro-scale simulator (SST/macro) that permits the coarse-grained study of distributed-memory applications. In the presented work, applications using the Message Passing Interface (MPI) are simulated; however, the simulator is designed to allow inclusion of other programming models. The simulator is driven from either a trace file or a skeleton application. Trace files can be either a standard format (Open Trace Format) or a more detailed custom format (DUMPI). The simulator architecture is modular, allowing it to easily be extended with additional network models, trace file formats, and more detailed processor models. This paper describes the design of the simulator, provides performance results, and presents studies showing how application performance is affected by machine characteristics.

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Kumar, Naresh, Edward Segall, Peter Steenkiste, and Armistead G. Russell. "Parallel and distributed application of an urban-to-regional multiscale model." Computers & Chemical Engineering 21, no. 4 (December 1997): 399–408. http://dx.doi.org/10.1016/s0098-1354(96)00006-3.

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21

Sinkwitz, R. C. "Particle motion simulation — a parallel distributed workstation application for real-time." Future Generation Computer Systems 8, no. 1-3 (July 1992): 43–47. http://dx.doi.org/10.1016/0167-739x(92)90028-a.

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22

Sato, Yuji, and Mikiko Sato. "Parallelization and sustainability of distributed genetic algorithms on many-core processors." International Journal of Intelligent Computing and Cybernetics 7, no. 1 (March 4, 2014): 2–23. http://dx.doi.org/10.1108/ijicc-06-2013-0033.

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Purpose – The purpose of this paper is to propose a fault-tolerant technology for increasing the durability of application programs when evolutionary computation is performed by fast parallel processing on many-core processors such as graphics processing units (GPUs) and multi-core processors (MCPs). Design/methodology/approach – For distributed genetic algorithm (GA) models, the paper proposes a method where an island's ID number is added to the header of data transferred by this island for use in fault detection. Findings – The paper has shown that the processing time of the proposed idea is practically negligible in applications and also shown that an optimal solution can be obtained even with a single stuck-at fault or a transient fault, and that increasing the number of parallel threads makes the system less susceptible to faults. Originality/value – The study described in this paper is a new approach to increase the sustainability of application program using distributed GA on GPUs and MCPs.

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Chi, Zhen Hua, and Yin Dong Liu. "Research Based on the PDM Ship Parallel Collaborative Design." Applied Mechanics and Materials 389 (August 2013): 1026–30. http://dx.doi.org/10.4028/www.scientific.net/amm.389.1026.

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This paper analyzes the technology based on the PDM ship parallel collaborative design, studies the features of ship parallel collaborative design, describes the application of distributed database in the ship parallel collaborative design project.

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Noor, Fazal, and Hatem ElBoghdadi. "Neural Nets Distributed on Microcontrollers using Metaheuristic Parallel Optimization Algorithm." Annals of Emerging Technologies in Computing 4, no. 4 (October 1, 2020): 28–38. http://dx.doi.org/10.33166/aetic.2020.04.004.

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Metaheuristic algorithms are powerful methods for solving compute intensive problems. neural Networks, when trained well, are great at prediction and classification type of problems. Backpropagation is the most popular method utilized to obtain the weights of Neural Nets though it has some limitations of slow convergence and getting stuck in a local minimum. In order to overcome these limitations, in this paper, a hybrid method combining the parallel distributed bat algorithm with backpropagation is proposed to compute the weights of the Neural Nets. The aim is to use the hybrid method in applications of a distributed nature. Our study uses the Matlab® software and Arduino® microcontrollers as a testbed. To test the performance of the testbed, an application in the area of speech recognition is carried out. Due to the resource limitations of Arduino microcontrollers, the core speech pre-processing of LPC (linear predictive coding) feature extractions are done in Matlab® and only the LPC parameters are passed to the Neural Nets, which are implemented on Arduino microcontrollers. The experimental results show that the proposed scheme does produce promising results.

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Kotulski, Leszek, and Barbara Strug. "Multi-Agent System for Distributed Adaptive Design." Key Engineering Materials 486 (July 2011): 217–20. http://dx.doi.org/10.4028/www.scientific.net/kem.486.217.

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This paper deals with the design of a multi-agent system for distributed design. The design processes are often complex and require high computational costs. Yet in many situations many elements of a design process can be computed simultaneously and thus lowering the total time required to finish the design. In this paper an approach based on hypergraph representation and using a formal background of the parallel application of the graph transformation rules is presented (parallel derivation process). The system is illustrated with examples from the floor layout design system.

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SAADI, Ramzi, and Mohamed Yacine HAMMOUDI. "Parallel Distributed Compensation for Three-Phase pulse width modulation converter." Electrotehnica, Electronica, Automatica 71, no. 2 (May 15, 2023): 38–45. http://dx.doi.org/10.46904/eea.23.71.2.1108005.

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In applications such as industrial drive systems and power supply systems, the use of a three-phase voltage-source Rectifier pulse width modulation converter is becoming increasingly common. Examples of these types of applications include: Power Factor Corrections and the reduction of harmonics. The critical control requirements of an application involving a three-phase voltage-source Rectifier pulse width modulation converter are to achieve a unity power factor and to regulate the dc voltage. The unity power factor guarantees the highest possible efficiency, while the dc voltage regulation guarantees that the converter will operate as desired. In this study, a novel control method for stabilizing a Rectifier-Inverter pulse width modulation converter is designed and simulated to reach higher levels of stability while also improving dynamic performances. In the first step, the nonlinear equation system of the converter is transformed into a polytopic form. This is done with the help of the sector nonlinearity transformation. After that, a Takagi-Sugeno fuzzy controller that uses the parallel distributed compensation operating concept is applied. The design of the control system takes into account practical control requirements, such as a fast voltage tracking strategy and line-currents regulation. In order to obtain the controller gain, a series of linear matrix inequalities must be resolved. Simulations performed using Matlab/Simulink make it abundantly evident that the proposed method possesses excellent performance in terms of both voltage tracking control and unity power factor regulation.

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Ishikawa, Masatoshi. "High-Speed Vision and its Applications Toward High-Speed Intelligent Systems." Journal of Robotics and Mechatronics 34, no. 5 (October 20, 2022): 912–35. http://dx.doi.org/10.20965/jrm.2022.p0912.

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Currently, high-speed vision based on parallel processing exists, and its various applications as high-speed intelligent systems have been proposed and implemented. The basic goal of high-speed vision is to realize vision capabilities and systems that operate at speeds necessary for intelligent systems, in which intelligence operating at the speed inherently required by the application system is achieved. This paper described the vision chip and parallel image processing architectures, presented outlines of system architectures, image-processing algorithms, and related peripheral technologies; described the concepts required to configure high-speed intelligent systems, such as hierarchical parallel distributed architecture, parallel decomposition, orthogonal decomposition, dynamics matching, latency minimization, high-speed 3D shape measurement, active vision, tracking vision, dynamic compensation, and dynamic projection mapping; and discussed a wide range of application systems in a systematic manner.

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ABRAMOV, O. V. "Application of parallel and distributed processing techniques for computer-aided design problems." Вестник ДВО РАН, no. 4 (2021): 110–18. http://dx.doi.org/10.37102/0869-7698_2021_218_04_12.

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Chesshire, G., and V. K. Naik. "An environment for parallel and distributed computation with application to overlapping grids." IBM Journal of Research and Development 38, no. 3 (May 1994): 285–300. http://dx.doi.org/10.1147/rd.383.0285.

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Kendall, Ricky A., Edoardo Aprà, David E. Bernholdt, Eric J. Bylaska, Michel Dupuis, George I. Fann, Robert J. Harrison, et al. "High performance computational chemistry: An overview of NWChem a distributed parallel application." Computer Physics Communications 128, no. 1-2 (June 2000): 260–83. http://dx.doi.org/10.1016/s0010-4655(00)00065-5.

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Chen, Chongcheng, Jiaxiang Lin, Xiaozhu Wu, and Jianwei Wu. "Parallel and Distributed Spatial Outlier Mining in Grid: Algorithm, Design and Application." Journal of Grid Computing 13, no. 2 (March 8, 2015): 139–57. http://dx.doi.org/10.1007/s10723-015-9326-y.

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Mironov, Andrew M. "A Mathematical Model of Parallel Programs and an Approach Based on it to Verification of MPI Programs." Modeling and Analysis of Information Systems 28, no. 4 (December 18, 2021): 394–412. http://dx.doi.org/10.18255/1818-1015-2021-4-394-412.

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The paper presents a new mathematical model of parallel programs, on the basis of which it is possible, in particular, to verify parallel programs presented on a certain subset of the parallel programming interface MPI. This model is based on the concepts of a sequential and distributed process. A parallel program is modeled as a distributed process in which sequential processes communicate by asynchronously sending and receiving messages over channels. The main advantage of the described model is the ability to simulate and verify parallel programs that generate an indefinite number of sequential processes. The proposed model is illustrated by the application of verification of the matrix multiplication MPI program.

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Winstead, Carl, Qiyan Sun, Paul G Hipes, Marco AP Lima, and Vincent McKoy. "Studies of Electron-Molecule Collisions on Distributed-memory Parallel Computers." Australian Journal of Physics 45, no. 3 (1992): 325. http://dx.doi.org/10.1071/ph920325.

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We review recent progress in the study of low-energy collisions between electrons and polyatomic molecules which has resulted from the application of distributed-memory parallel computing to this challenging problem. Recent studies of electronically elastic and inelastic scattering from several molecular systems, including ethene, propene, cyclopropane, and disilane, are presented. We also discuss the potential of ab initio methods combined with cost-effective parallel computation to provide critical data for the modeling of materials-processing plasmas.

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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 application by simply specialising a given set of classes and methods and using a set of added functionalities.

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Tang, D., X. Zhou, Y. Jing, W. Cong, and C. Li. "DESIGN AND VERIFICATION OF REMOTE SENSING IMAGE DATA CENTER STORAGE ARCHITECTURE BASED ON HADOOP." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (April 30, 2018): 1639–42. http://dx.doi.org/10.5194/isprs-archives-xlii-3-1639-2018.

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The data center is a new concept of data processing and application proposed in recent years. It is a new method of processing technologies based on data, parallel computing, and compatibility with different hardware clusters. While optimizing the data storage management structure, it fully utilizes cluster resource computing nodes and improves the efficiency of data parallel application. This paper used mature Hadoop technology to build a large-scale distributed image management architecture for remote sensing imagery. Using MapReduce parallel processing technology, it called many computing nodes to process image storage blocks and pyramids in the background to improve the efficiency of image reading and application and sovled the need for concurrent multi-user high-speed access to remotely sensed data. It verified the rationality, reliability and superiority of the system design by testing the storage efficiency of different image data and multi-users and analyzing the distributed storage architecture to improve the application efficiency of remote sensing images through building an actual Hadoop service system.

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Bozkus, Zeki, Larry Meadows, Steven Nakamoto, Vincent Schuster, and Mark Young. "PGHPF – An Optimizing High Performance Fortran Compiler for Distributed Memory Machines." Scientific Programming 6, no. 1 (1997): 29–40. http://dx.doi.org/10.1155/1997/705102.

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High Performance Fortran (HPF) is the first widely supported, efficient, and portable parallel programming language for shared and distributed memory systems. HPF is realized through a set of directive-based extensions to Fortran 90. It enables application developers and Fortran end-users to write compact, portable, and efficient software that will compile and execute on workstations, shared memory servers, clusters, traditional supercomputers, or massively parallel processors. This article describes a production-quality HPF compiler for a set of parallel machines. Compilation techniques such as data and computation distribution, communication generation, run-time support, and optimization issues are elaborated as the basis for an HPF compiler implementation on distributed memory machines. The performance of this compiler on benchmark programs demonstrates that high efficiency can be achieved executing HPF code on parallel architectures.

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DECKER, K. M., C. JAYEWARDENA, and R. REHMANN. "Libraries and Development Environments for Monte Carlo Simulations of Lattice Gauge Theories on Parallel Computers." International Journal of Modern Physics C 02, no. 01 (March 1991): 316–21. http://dx.doi.org/10.1142/s0129183191000408.

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We describe the library lgtlib, and lgttool, the corresponding development environment for Monte Carlo simulations of lattice gauge theory on multiprocessor vector computers with shared memory. We explain why distributed memory parallel processor (DMPP) architectures are particularly appealing for compute-intensive scientific applications, and introduce the design of a general application and program development environment system for scientific applications on DMPP architectures.

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Sikora, Andrzej, and Ewa Niewiadomska-Szynkiewicz. "FR/ASimJava: a federated approach to parallel and distributed network simulation in practice." Journal of Telecommunications and Information Technology, no. 4 (December 30, 2006): 53–59. http://dx.doi.org/10.26636/jtit.2006.4.394.

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The paper addresses issues associated with the application of federations of parallel/distributed simulators to large scale networks simulation. We discuss two principal paradigms for constructing simulations today. Particular attention is paid to an approach for federating parallel/distributed simulators. We describe the design and performance of frame relay network simulator (FR/ASimJava) implemented based on a Java-based library for distributed simulation – ASimJava. Six practical examples – six networks operating under frame relay – are presented to illustrate the operation of the given software tool. The focus is on the efficiency of presented network simulator.

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Li, Shengbiao, and Jiankui Peng. "Implementation and Optimization of Probabilistic and Mathematical Statistical Algorithms under Distributive Architecture." Scalable Computing: Practice and Experience 25, no. 5 (August 1, 2024): 3841–49. http://dx.doi.org/10.12694/scpe.v25i5.3022.

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Statistical methods must be developed and optimized in distributed systems due to the increasing amount of data and processing demands in modern applications. The application and optimization of mathematical and probabilistic statistical methods in distributed computing settings is the main topic of this study. Algorithms like these have the potential to improve performance, scalability, and parallel processing abilities when integrated into distributed systems. We commence our investigation by reviewing current mathematical and probabilistic statistical algorithms, determining their advantages and disadvantages, and evaluating their suitability for distributed architectures. We then suggest new approaches for their smooth incorporation into distributed computing structures, making use of distributed storage and parallel processing to effectively manage massive datasets. Improving these algorithms’ performance in distributed environments is the focus of this research’s refinement phase. We seek to optimize the use of distributed infrastructures by minimizing latency and maximizing computational resources by investigating efficient communication protocols, load balancing mechanisms, and parallelization approaches. The suggested algorithms are put into practice inside a distributed structure for empirical confirmation, and their effectiveness is evaluated in comparison to more conventional, non-distributed competitors. We test the scaling, precision, and effectiveness of the methods in practical scenarios using a variety of datasets and use cases.

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Ioannidis, Sotiris, Umit Rencuzogullari, Robert Stets, and Sandhya Dwarkadas. "CRAUL: Compiler and Run-Time Integration for Adaptation under Load." Scientific Programming 7, no. 3-4 (1999): 261–73. http://dx.doi.org/10.1155/1999/603478.

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Clusters of workstations provide a cost‐effective, high performance parallel computing environment. These environments, however, are often shared by multiple users, or may consist of heterogeneous machines. As a result, parallel applications executing in these environments must operate despite unequal computational resources. For maximum performance, applications should automatically adapt execution to maximize use of the available resources. Ideally, this adaptation should be transparent to the application programmer. In this paper, we present CRAUL (Compiler and Run‐Time Integration for Adaptation Under Load), a system that dynamically balances computational load in a parallel application. Our target run‐time is software‐based distributed shared memory (SDSM). SDSM is a good target for parallelizing compilers since it reduces compile‐time complexity by providing data caching and other support for dynamic load balancing. CRAUL combines compile‐time support to identify data access patterns with a run‐time system that uses the access information to intelligently distribute the parallel workload in loop‐based programs. The distribution is chosen according to the relative power of the processors and so as to minimize SDSM overhead and maximize locality. We have evaluated the resulting load distribution in the presence of different types of load – computational, computational and memory intensive, and network load. CRAUL performs within 5–23% of ideal in the presence of load, and is able to improve on naive compiler‐based work distribution that does not take locality into account even in the absence of load.

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Benchara, Fatéma Zahra, and Mohamed Youssfi. "A New Distributed Type-2 Fuzzy Logic Method for Efficient Data Science Models of Medical Informatics." Advances in Fuzzy Systems 2020 (August 25, 2020): 1–10. http://dx.doi.org/10.1155/2020/6539123.

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The paper aims to propose a distributed method for machine learning models and its application for medical data analysis. The great challenge in the medicine field is to provide a scalable image processing model, which integrates the computing processing requirements and computing-aided medical decision making. The proposed Fuzzy logic method is based on a distributed approach of type-2 Fuzzy logic algorithm and merges the HPC (High Performance Computing) and cognitive aspect on one model. Accordingly, the method is assigned to be implemented on big data analysis and data science prediction models for healthcare applications. The paper focuses on the proposed distributed Type-2 Fuzzy Logic (DT2FL) method and its application for MRI data analysis under a massively parallel and distributed virtual mobile agent architecture. Indeed, the paper presents some experimental results which highlight the accuracy and efficiency of the proposed method.

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Castiglione, F., M. Bernaschi, and S. Succi. "Simulating the Immune Response on a Distributed Parallel Computer." International Journal of Modern Physics C 08, no. 03 (June 1997): 527–45. http://dx.doi.org/10.1142/s0129183197000424.

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The application of ideas and methods of statistical mechanics to problems of biological relevance is one of the most promising frontiers of theoretical and computational mathematical physics.1,2 Among others, the computer simulation of the immune system dynamics stands out as one of the prominent candidates for this type of investigations. In the recent years immunological research has been drawing increasing benefits from the resort to advanced mathematical modeling on modern computers.3,4 Among others, Cellular Automata (CA), i.e., fully discrete dynamical systems evolving according to boolean laws, appear to be extremely well suited to computer simulation of biological systems.5 A prominent example of immunological CA is represented by the Celada–Seiden automaton, that has proven capable of providing several new insights into the dynamics of the immune system response. To date, the Celada–Seiden automaton was not in a position to exploit the impressive advances of computer technology, and notably parallel processing, simply because no parallel version of this automaton had been developed yet. In this paper we fill this gap and describe a parallel version of the Celada–Seiden cellular automaton aimed at simulating the dynamic response of the immune system. Details on the parallel implementation as well as performance data on the IBM SP2 parallel platform are presented and commented on.

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Shi, Xian Cheng, Yu Cheng Feng, Jin Song Zeng, and Ke Fu Chen. "Distributed Cross-Direction Control System Based on CAN-Bus." Applied Mechanics and Materials 705 (December 2014): 345–49. http://dx.doi.org/10.4028/www.scientific.net/amm.705.345.

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A distributed cross-direction control system based on CAN-bus was designed to solve the large-scale cross-direction control problem for paper machine. Multiple Master-Slave CAN networks were constructed in parallel to coordinate and control multiple array actuators, and the Ethernet/CAN converter was used to connect the monitoring station with the field intelligent actuators. The monitoring station accesses measured data and field data via OPC technology. A CAN application layer protocol and corresponding underlying communication software were designed according to the characteristics of the cross-direction control processes. Finally, the feasibility and reliability of the system were verified with practical applications.

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Jeong, Eunjin, Dowhan Jeong, and Soonhoi Ha. "Dataflow Model–based Software Synthesis Framework for Parallel and Distributed Embedded Systems." ACM Transactions on Design Automation of Electronic Systems 26, no. 5 (June 5, 2021): 1–38. http://dx.doi.org/10.1145/3447680.

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Existing software development methodologies mostly assume that an application runs on a single device without concern about the non-functional requirements of an embedded system such as latency and resource consumption. Besides, embedded software is usually developed after the hardware platform is determined, since a non-negligible portion of the code depends on the hardware platform. In this article, we present a novel model-based software synthesis framework for parallel and distributed embedded systems. An application is specified as a set of tasks with the given rules for execution and communication. Having such rules enables us to perform static analysis to check some software errors at compile-time to reduce the verification difficulty. Platform-specific programs are synthesized automatically after the mapping of tasks onto processing elements is determined. The proposed framework is expandable to support new hardware platforms easily. The proposed communication code synthesis method is extensible and flexible to support various communication methods between devices. In addition, the fault-tolerant feature can be added by modifying the task graph automatically according to the selected fault-tolerance configurations by the user. The viability of the proposed software development methodology is evaluated with a real-life surveillance application that runs on six processing elements.

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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 parallel training of artificial neural networks and to determine the optimal combination of technologies and nodes of devices to increase speed and enable real-time decision-making capabilities in spatial navigation for autonomous vehicles. Method. The research establishes that the utilization of computer vision and neural networks for road lane segmentation proves to be an effective method for spatial orientation of autonomous vehicles. For multi-core computing systems, the application of parallel programming technology, OpenMP, for neural network training on processors with varying numbers of parallel threads increases the algorithm’s execution speed. However, the use of CUDA technology for neural network training on a graphics processing unit significantly enhances prediction speeds compared to OpenMP. Additionally, the feasibility of employing PyTorch Distributed Data Parallel (DDP) technology for training the neural network across multiple graphics processing units (nodes) simultaneously was explored. This approach further improved prediction execution times compared to using a single graphics processing unit. Results. An algorithm for training and prediction of an artificial neural network was developed using two independent nodes, each equipped with separate graphics processing units, and their synchronization for exchanging training results after each epoch, employing PyTorch Distributed Data Parallel (DDP) technology. This approach allows for scalable computations across a higher number of resources, significantly expediting the model training process. Conclusions. The conducted experiments have affirmed the effectiveness of the proposed algorithm, warranting the recommendation of this research for further advancement in autonomous vehicles and enhancement of their navigational capabilities. Notably, the research outcomes can find applications in various domains, encompassing automotive manufacturing, logistics, and urban transportation infrastructure. The obtained results are expected to assist future researchers in understanding the most efficient hardware and software resources to employ for implementing AI-based navigation systems in autonomous vehicles. Prospects for future investigations may encompass refining the accuracy of the proposed parallel algorithm without compromising its efficiency metrics. Furthermore, there is potential for experimental exploration of the proposed algorithm in more intricate practical scenarios of diverse nature and dimensions.

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GASCARD, ERIC, and LAURENCE PIERRE. "FORMAL PROOF OF APPLICATIONS DISTRIBUTED IN SYMMETRIC INTERCONNECTION NETWORKS." Parallel Processing Letters 13, no. 01 (March 2003): 3–18. http://dx.doi.org/10.1142/s0129626403001094.

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This paper focuses on the formal proof of parallel programs dedicated to distributed memory symmetric interconnection networks; communications are realized by message passing. We have developed a method to formally verify the computational correctness of this kind of application. Using the notion of Cayley graphs to model the networks in the Nqthm theorem prover, we have formally specified and mechanically proven correct a large set of collective communication primitives. Our compositional approach allows us to reuse these libraries of pre-proven procedures to validate complex application programs within Nqthm. This is illustrated by three examples.

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Velarde Martínez, Apolinar. "Parallelization of Array Method with Hybrid Programming: OpenMP and MPI." Applied Sciences 12, no. 15 (July 31, 2022): 7706. http://dx.doi.org/10.3390/app12157706.

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For parallelization of applications with high processing times and large amounts of storage in High Performance Computing (HPC) systems, shared memory programming and distributed memory programming have been used; a parallel application is represented by Parallel Task Graphs (PTGs) using Directed Acyclic Graphs (DAGs). For the execution of PTGs in HPC systems, a scheduler is executed in two phases: scheduling and allocation; the execution of the scheduler is considered an NP-complete combinatorial problem and requires large amounts of storage and long processing times. Array Method (AM) is a scheduler to execute the task schedule in a set of clusters; this method was programmed sequentially, analyzed and tested using real and synthetic application workloads in previous work. Analyzing the proposed designs of this method in this research work, the parallelization of the method is extended using hybrid OpenMP and MPI programming in a server farm and using a set of geographically distributed clusters; at the same time, a novel method for searching free resources in clusters using Lévy random walks is proposed. Synthetic and real workloads have been experimented with to evaluate the performance of the new parallel schedule and compare it to the sequential schedule. The metrics of makespan, waiting time, quality of assignments and search for free resources were evaluated; the results obtained and described in the experiments section show a better performance with the new version of the parallel algorithm compared to the sequential version. By using the parallel approach with hybrid programming applied to the extraction of characteristics of the PTGs, applied to the search for geographically distributed resources with Lévy random walks and applied to the metaheuristic used, the results of the metrics are improved. The makespan is decreased even when the loads increase, the times of the tasks in the waiting queue are decreased, the quality of assignments in the clusters is improved by causing the tasks with their subtasks to be assigned in the same clusters or in cluster neighbors and, finally, the searches for free resources are executed in different geographically distributed clusters, not sequentially.

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Aihara, K. "Chaos engineering and its application to parallel distributed processing with chaotic neural networks." Proceedings of the IEEE 90, no. 5 (May 2002): 919–30. http://dx.doi.org/10.1109/jproc.2002.1015014.

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Ruiz-Cabello N., Miguel, Maksims Abaļenkovs, Luis M. Diaz Angulo, Clemente Cobos Sanchez, Franco Moglie, and Salvador G. Garcia. "Performance of parallel FDTD method for shared- and distributed-memory architectures: Application tobioelectromagnetics." PLOS ONE 15, no. 9 (September 11, 2020): e0238115. http://dx.doi.org/10.1371/journal.pone.0238115.

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Chang, Fangzhe, Vijay Karamcheti, and Zvi Kedem. "Exploiting Application Tunability for Efficient, Predictable Resource Management in Parallel and Distributed Systems." Journal of Parallel and Distributed Computing 60, no. 11 (November 2000): 1420–45. http://dx.doi.org/10.1006/jpdc.2000.1660.

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