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3rd International Scientific Conference on Intelligent Information Technologies for Industry (IITI)

作者： Voitsitskaya, Anastasia Fedulov, Alexader Fedulov, Yaroslav Natl Res Univ Moscow Power Engn Inst Moscow 111250 Russia Natl Res Univ Moscow Power Engn Inst Smolensk Branch Smolensk 214013 Russia

ISBN: (纸本)9783030018184

In this paper, the method of dispatching and optimal distribution of resources of various types in parallel computing systems is considered, based on preliminary processing of the individual problems parameters, construction of fuzzy evaluation systems and hybrid neural-fuzzy production systems. The application of this method provides advantages in conditions of inaccurate, incomplete and difficult to formalize information about the characteristics of performed tasks, taking into account initially established preferences and achieving the desired performance indicators for the tasks and selected planning strategy.

关键词： Fuzzy evaluation models Resource management Neuro-fuzzy production models Data preprocessing parallel computing systems

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A comparative study on resource allocation and energy efficient job scheduling strategies in large-scale parallel computing systems

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CLUSTER computing-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2014年第4期17卷 1349-1367页

作者： Chandio, Aftab Ahmed Bilal, Kashif Tziritas, Nikos Yu, Zhibin Jiang, Qingshan Khan, Samee U. Xu, Cheng-Zhong Chinese Acad Sci Shenzhen Inst Adv Technol Shenzhen Peoples R China Chinese Acad Sci Grad Univ Beijing Peoples R China Univ Sindh Inst Math & Comp Sci Jamshoro Pakistan N Dakota State Univ Dept Elect & Comp Engn Fargo ND 58105 USA Wayne State Univ Dept Elect & Comp Engn Detroit MI 48202 USA

In the large-scale parallel computing environment, resource allocation and energy efficient techniques are required to deliver the quality of services (QoS) and to reduce the operational cost of the system. Because the cost of the energy consumption in the environment is a dominant part of the owner's and user's budget. However, when considering energy efficiency, resource allocation strategies become more difficult, and QoS (i.e., queue time and response time) may violate. This paper therefore is a comparative study on job scheduling in large-scale parallel systems to: (a) minimize the queue time, response time, and energy consumption and (b) maximize the overall system utilization. We compare thirteen job scheduling policies to analyze their behavior. A set of job scheduling policies includes (a) priority-based, (b) first fit, (c) backfilling, and (d) window-based policies. All of the policies are extensively simulated and compared. For the simulation, a real data center workload comprised of 22385 jobs is used. Based on results of their performance, we incorporate energy efficiency in three policies i.e., (1) best result producer, (2) average result producer, and (3) worst result producer. We analyze the (a) queue time, (b) response time, (c) slowdown ratio, and (d) energy consumption to evaluate the policies. Moreover, we present a comprehensive workload characterization for optimizing system's performance and for scheduler design. Major workload characteristics including (a) Narrow, (b) Wide, (c) Short, and (d) Long jobs are characterized for detailed analysis of the schedulers' performance. This study highlights the strengths and weakness of various job scheduling polices and helps to choose an appropriate job scheduling policy in a given scenario.

关键词： parallel computing systems Job scheduling Workload characterization Data center Energy efficiency

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Algorithms for Solving Inverse Geophysical Problems on parallel computing systems

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NUMERICAL ANALYSIS AND APPLICATIONS 2013年第2期6卷 98-110页

作者： Akimova, E. N. Belousov, D. V. Misilov, V. E. Russian Acad Sci Inst Math & Mech Ural Branch Ul S Kovalevskoi 16 Ekaterinburg 620990 Russia Ural Fed Univ Ekaterinburg 620002 Russia

For solving inverse gravimetry problems, efficient stable parallel algorithms based on iterative gradient methods are proposed. For solving systems of linear algebraic equations with block-tridiagonal matrices arising in geoelectrics problems, a parallel matrix sweep algorithm, a square root method, and a conjugate gradient method with preconditioner are proposed. The algorithms are implemented numerically on a parallel computing system of the Institute of Mathematics and Mechanics (PCS-IMM), NVIDIA graphics processors, and an Intel multi-core CPU with some new computing technologies. The parallel algorithms are incorporated into a system of remote computations entitled "Specialized Web-Portal for Solving Geophysical Problems on Multiprocessor Computers." Some problems with "quasi-model" and real data are solved.

关键词： inverse gravimetry problems parallel algorithms direct and iterative methods parallel computing systems

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parallel Inference for Real-Time Machine Learning Applications

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Journal of Computer and Communications 2024年第1期12卷 139-146页

作者： Sultan Al Bayyat Ammar Alomran Mohsen Alshatti Ahmed Almousa Rayyan Almousa Yasir Alguwaifli College of Computer Science and Information Technology Imam Abdulrahman Bin Faisal University Dammam Saudi Arabia

Hyperparameter tuning is a key step in developing high-performing machine learning models, but searching large hyperparameter spaces requires extensive computation using standard sequential methods. This work analyzes the performance gains from parallel versus sequential hyperparameter optimization. Using scikit-learn’s Randomized SearchCV, this project tuned a Random Forest classifier for fake news detection via randomized grid search. Setting n_jobs to -1 enabled full parallelization across CPU cores. Results show the parallel implementation achieved over 5× faster CPU times and 3× faster total run times compared to sequential tuning. However, test accuracy slightly dropped from 99.26% sequentially to 99.15% with parallelism, indicating a trade-off between evaluation efficiency and model performance. Still, the significant computational gains allow more extensive hyperparameter exploration within reasonable timeframes, outweighing the small accuracy decrease. Further analysis could better quantify this trade-off across different models, tuning techniques, tasks, and hardware.

关键词： Machine Learning Models Computational Efficiency parallel computing systems Random Forest Inference Hyperparameter Tuning Python Frameworks (TensorFlow PyTorch Scikit-Learn) High-Performance computing

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A parallel programming assessment for stream processing applications on multi-core systems

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COMPUTER STANDARDS & INTERFACES 2023年 84卷 1页

作者： Andrade, Gabriella Griebler, Dalvan Santos, Rodrigo Fernandes, Luiz Gustavo Pontifical Catholic Univ Rio Grande Sul PUCRS Sch Technol Parallel Applicat Modeling Grp GMAP Porto Alegre Brazil Tres De Maio Fac Setrem Lab Adv Res Cloud Comp LARCC Tres De Maio Brazil Fed Univ State Rio De Janeiro UNIRIO Dept Appl Informat Rio De Janeiro Brazil

Multi-core systems are any computing device nowadays and stream processing applications are becoming recurrent workloads, demanding parallelism to achieve the desired quality of service. As soon as data, tasks, or requests arrive, they must be computed, analyzed, or processed. Since building such applications is not a trivial task, the software industry must adopt parallel APIs (Application Programming Interfaces) that simplify the exploitation of parallelism in hardware for accelerating time-to-market. In the last years, research efforts in academia and industry provided a set of parallel APIs, increasing productivity to software developers. However, a few studies are seeking to prove the usability of these interfaces. In this work, we aim to present a parallel programming assessment regarding the usability of parallel API for expressing parallelism on the stream processing application domain and multi-core systems. To this end, we conducted an empirical study with beginners in parallel application development. The study covered three parallel APIs, reporting several quantitative and qualitative indicators involving developers. Our contribution also comprises a parallel programming assessment methodology, which can be replicated in future assessments. This study revealed important insights such as recurrent compile-time and programming logic errors performed by beginners in parallel programming, as well as the programming effort, challenges, and learning curve. Moreover, we collected the participants' opinions about their experience in this study to understand deeply the results achieved.

关键词： parallel software parallel computing systems Programming productivity Programming effort Stream parallelism Programming usability

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LiFlow web service for quick launch of large experiment series on supercomputers 7

LiFlow web service for quick launch of large experiment seri...

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7th Annual International Young Scientists Conference on Computational Science (YSC)

作者： Kuklin, Evgeniy Pravdin, Sergei Krasovskii Inst Math & Mech Ekaterinburg Russia Ural Fed Univ Ekaterinburg Russia

In many fields of research, for example in simulations of living systems, the automatic execution of many numerical experiments with varying parameters is a crucial task. We propose a web-based multiplatform service for launching a series of experiments on a supercomputer. The service interface allows the user to set parameters and run jobs on a supercomputer without working in the command line. The system minimizes the number of user actions required for launching a large series of experiments. Using the built-in database, one of the previously conducted experiments can be picked up and quickly restarted with new settings. We provide the architecture of interaction between a computing cluster, a database, and an external web application, as well as the algorithm for generating tuples from sets of values of individual parameters, and features of the graphical user interface. The system actively carries out computational experiments to study the drift of spiral waves in the myocardium on the Uran supercomputer, Ekaterinburg. (C) 2018 The Authors. Published by Elsevier B.V.

关键词： parallel computing systems supercomputers experiment series execution computational experiment reproducibility GUI living system simulation

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LiFlow web service for quick launch of large experiment series on supercomputers

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Procedia Computer Science 2018年 136卷 44-51页

作者： Evgeniy Kuklin Sergei Pravdin Krasovskii Institute of Mathematics and Mechanics Ekaterinburg Russia Ural Federal University Ekaterinburg Russia

关键词： parallel computing systems supercomputers experiment series execution computational experiment reproducibility GUI living system simulation

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Obtaining the optimal configuration of high-radix Combined switches

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JOURNAL OF parallel AND DISTRIBUTED computing 2013年第9期73卷 1239-1250页

作者： Villar, Juan A. Andujar, Francisco J. Sanchez, Jose L. Alfaro, Francisco J. Gamez, Jose A. Duato, Jose Univ Castilla La Mancha Dept Sistemas Informat Albacete 02071 Spain Univ Politecn Valencia Dept Informat Sistemas & Comp Valencia 46022 Spain

High-radix switches reduce network cost and improve network performance, especially in large switch-based interconnection networks. However, there are some problems related to the integration scale to implement such switches in a single chip. An interesting alternative for building high-radix switches consists of combining several current smaller single-chip switches to obtain switches with a greater number of ports. A key design issue of this kind of high-radix switches is the internal switch configuration, specifically, the correspondence between the ports of these high-radix switches and the ports of their smaller internal single-chip switches. In this paper we use artificial intelligence and data mining techniques in order to obtain the optimal internal configuration of all the switches in the network of large supercomputers running parallel applications. Simulation results show that using the resultant switch configurations, it is possible to achieve similar performance as with single-chip switches with the same radix, which would be unfeasible with the current integration scale. (C) 2013 Elsevier Inc. All rights reserved.

关键词： parallel computing systems Interconnection networks High-radix switches Search algorithms

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Refined Numerical Simulation of Three-Dimensional Riveting in Laminated Composites

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JOURNAL OF AIRCRAFT 2011年第4期48卷 1434-1443页

作者： Yoon, Tae Ho Kim, Seung Jo Seoul Natl Univ Sch Mech & Aerosp Engn Seoul 151744 South Korea

Riveting in laminated composites is not carried out, because the riveting process can easily induce failure and form a nonuniform interference fit. An electromagnetic riveting riveter provides a relatively uniform interference fit with no direct failure in the riveted joint. Finite element numerical simulation of three-dimensional riveting is conducted by considering the sine wave of force history for the electromagnetic riveting riveter. To reflect the physical phenomenon of the complicated contact of riveting in laminated composites, a refined modeling of the washer inner fillet is considered, and the parallel computations using LS-DYNA are used. Refined simulation is validated by experiments reported in the literature. The electromagnetic riveting is properly applied for riveting in laminated composites. Optimized maximum riveting force is obtained for relative uniform interference based on the criterion of relative interference for fatigue life extension. A parametric study of the washer effects during the riveting process is investigated to obtain a proper riveted joint in laminated composites.

关键词： Fiber Volume Fraction Numerical Simulation Maximum Shear Stresses Composite Structures Fatigue Life parallel computing Environment parallel computing systems Numerical Analysis Yield Stress computing Technology

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Real-World Distributed Computer with Ibis

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COMPUTER 2010年第8期43卷 54-62页

作者： Bal, Henri E. Maassen, Jason van Nieuwpoort, Rob V. Drost, Niels Kemp, Roelof van Kessel, Timo Palmer, Nick Wrzesinska, Gosia Kielmann, Thilo van Reeuwijk, Kees Seinstra, Frank J. Jacobs, Ceriel J. H. Verstoep, Kees Vrije Univ Amsterdam Dept Comp Sci High Performance Distributed Syst Res Grp Amsterdam Netherlands

The use of parallel and distributed computing systems is essential to meet the ever-increasing computational demands of many scientific and industrial applications. Ibis allows easy programming and deployment of compu... 详细信息

关键词： Distributed programming Distributed systems Ibis Java Scientific computing systems engineering computational demands distributed computing systems industrial applications parallel computing systems parallel programming real-world distributed computer scientific applications

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