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

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Enhancing Solar Convection Analysis With Multi‐Core Processors and GPUs by Arash Heidari, Zahra Amiri, Mohammad Ali Jabraeil Jamali, Nima Jafari Navimipour

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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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Parallel Newtonian Optimization without Hessian Approximation by Khalil Abbo

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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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Long Prediction Horizon FCS-MPC for Power Converters and Drives by Eduardo Zafra, Sergio Vazquez, Tobias Geyer, Ricardo P. Aguilera, Leopoldo G. Franquelo

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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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Efficient GPU Implementation of the McMurchie–Davidson Method for Shell-Based ERI Computations by Haruto Fujii, Yasuaki Ito, Nobuya Yokogawa, Kanta Suzuki, Satoki Tsuji, Koji Nakano, Victor Parque, Akihiko Kasagi

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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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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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Finding Multiple Optimal Solutions to an Integer Linear Program by Random Perturbations of Its Objective Function by Noah Schulhof, Pattara Sukprasert, Eytan Ruppin, Samir Khuller, Alejandro A. Schäffer

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Analysis of Algorithms for Detecting Users’ Behavioral Models based on Sessions Data by Vitaly Zabiniako, Toms Rožkalns, Erika Nazaruka, Jurijs Kornienko

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A Novel Method for Aircraft Structural Dynamic Strain Trend Signal Processing via Optimized Parallel Computing by Yongwei Tian, Fang Zhang, Jinhui Jiang, Zhe Fan

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

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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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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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Parallelization in combining the SOM and Sammon's mapping by Gintautas Dzemyda, Olga Kurasova, Virginijus Marcinkevičius

“… In this paper, we propose a parallel algorithm for multidimensional data visualization combining the neural network (the self-organizing map-SOM) and Sammon’s mapping. …”
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