An Efficient Workload-balancing Algorithm for a Parallel Environment Using Hybrid Spatio-temporal Indexes by Claudio Gutiérrez-Soto, Marco A. Palomino, Patricio Galdames

Subjects: “…Parallel Algorithms…”
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A Theoretical Bound Which Improves the Performance of Compilation-Based Multi-Agent Path Finding by Rodrigo Lopez, Roberto Asin-Acha, Jorge A. Baier

Subjects: “…Parallel algorithms…”
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TSC-IBR: A Variant of Interval-Based Memory Reclamation Using CPU’s Time-Stamp Counter by Chen Zhang, Wendong Li, Xinghui Zhu

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IMPROVING THE EFFICIENCY OF THE METHOD OF SPECULATIVE MULTI-THREADING FOR DYNAMIC PARALLELIZING by Marina A. Bakuleva, Alexander V. Bakulev

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On а Recursive-Parallel Algorithm for Solving the Knapsack Problem by Vladimir V. Vasilchikov

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Model of a Parallel-Pipeline Computational Process for Solving a System of Grid Equations by V. N. Litvinov, N. B. Rudenko, N. N. Gracheva

Subjects: “…parallel algorithm…”
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Corrigendum to: V. V. Vasilchikov, “Parallel Algorithm for Solving the Graph Isomorphism Problem”, Modeling and analysis of information systems, vol. 27, no. 1, pp. 86–94, 2020. DO... by Vladimir Vasilyevich Vasilchikov

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Recursive-Parallel Algorithm for Solving the Graph-Subgraph Isomorphism Problem by Vladimir V. Vasilchikov

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Recursive-Parallel Algorithm for Solving the Maximum Common Subgraph Problem by Vladimir V. Vasilchikov

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On the Optimization and Parallelizing Little Algorithm for Solving the Traveling Salesman Problem by V. V. Vasilchikov

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PARALLEL ALGORITHM SEARCHING OF THE OBJECTIVE FUNCTION MAXIMUM BY DYNAMIC PROGRAMMING METHOD USING CUDA TECHNOLOGY by E. N. Seredin

Subjects: “…parallel algorithm…”
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Verification of systems with behavior parallelism on the basis of the graph of reachable states by Yu. V. Pottosin, V. I. Romanov, L. D. Cheremisinova

Subjects: “…parallel algorithm…”
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Comparative analysis of audio-MAE and MAE-AST models for real-time audio classification by Lesia Mochurad

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Distributionally robust microgrid formation for service restoration in distribution systems against extended extreme events by Ran Zhu, Hongzhe Liu, Wenwu Yu, Wei Gu, Jin Zhao

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GPU-Accelerated Fock Matrix Computation with Efficient Reduction by Satoki Tsuji, Yasuaki Ito, Haruto Fujii, Nobuya Yokogawa, Kanta Suzuki, Koji Nakano, Victor Parque, Akihiko Kasagi

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Application of Graphics Processor Unit Computing Resources to Solution of Incompressible Fluid Dynamics Problems by Redha Benhadj-Djilali, Arturas Gulevskis, Konstantin Volkov

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A parallel program for the simulation of flooding by Anurak Busaman, Rhysa McNeil, Somporn Chuai-Aree, Mayuening Eso

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Study and Implementation of Multi-GPU Parallel Algorithm for 3D Borehole Acoustic Field Simulation by WANG Hua, HE Weibing, QIANG Xiaoyong, WANG Qiang, HUANG Fang, LI Meng

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On the resonances of an inhomogeneous dielectric ball, coated with graphene by O.S. Skvortsov

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ADVANCED SCHEDULER FOR COOPERATIVE EXECUTION OF THREADS ON MULTI-CORE SYSTEM by O. N. Karasik, A. A. Prihozhy

Subjects: “…three architectures of the cooperative thread scheduler in a multithreaded application that is executed on a multi-core system are considered. architecture a0 is based on the synchronization and scheduling facilities, which are provided by the operating system. architecture a1 introduces a new synchronization primitive and a single queue of the blocked threads in the scheduler, which reduces the interaction activity between the threads and operating system, and significantly speed up the processes of blocking and unblocking the threads. architecture a2 replaces the single queue of blocked threads with dedicated queues, one for each of the synchronizing primitives, extends the number of internal states of the primitive, reduces the inter- dependence of the scheduling threads, and further significantly speeds up the processes of blocking and unblocking the threads. all scheduler architectures are implemented on windows operating systems and based on the user mode scheduling. important experimental results are obtained for multithreaded applications that implement two blocked parallel algorithms of solving the linear algebraic equation systems by the gaussian elimination. the algorithms differ in the way of the data distribution among threads and by the thread synchronization models. the number of threads varied from 32 to 7936. architecture a1 shows the acceleration of up to 8.65% and the architecture a2 shows the acceleration of up to 11.98% compared to a0 architecture for the blocked parallel algorithms computing the triangular form and performing the back substitution. on the back substitution stage of the algorithms, architecture a1 gives the acceleration of up to 125%, and architecture a2 gives the acceleration of up to 413% compared to architecture a0. the experiments clearly show that the proposed architectures, a1 and a2 outperform a0 depending on the number of thread blocking and unblocking operations, which happen during the execution of multi-threaded applications. the conducted computational experiments demonstrate the improvement of parameters of multithreaded applications on a heterogeneous multi-core system due the proposed advanced versions of the thread scheduler.…”
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