Three-Dimensional Inversion of the Time-Lapse Resistivity Method on the MPI Parallel Algorithm by Depeng Zhu, Youxing Yang, Lei Wen

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AVS3 intra frame prediction parallel algorithm based on minimum CU cost by ZHANG Quan, WANG Shun, LIU Yangyi, DUAN Chang, PENG Bo

“…To address the time-consuming issue of audio video coding standard 3(AVS3) intra frame prediction, an intra frame prediction parallel algorithm based on the cost of the minimum coding unit (CU) was proposed. …”
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PARALLEL ALGORITHM FOR THREE-DIMENSIONAL STOKES FLOW SIMULATION USING BOUNDARY ELEMENT METHOD by D. G. Pribytok, E. N. Seredin

“…For construction of the system and finding the velocity, the parallel algorithms using graphics CUDA cards programming technology have been developed and implemented. …”
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Coarse-Grained Column Agglomeration Parallel Algorithm for LU Factorization Using Multi-Threaded MATLAB by Osama Sabir, Reza Alebrahim

“…This paper studied a coarse-grained column agglomeration parallel algorithm in MATLAB to analyze the implementation performance among all the available computation resources. …”
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IMPLEMENTATION OF THE PARALLEL ALGORITHM OF NONISOTHERMAL HEAT AND MOISTURE MIGRATION TASK SIMULATION IN NATURAL DISPERSE ENVIRONMENTS by P. K. Shalkevich, S. P. Kundas, I. A. Gishkeluk

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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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A Parallel Algorithm for the Two-Dimensional Time Fractional Diffusion Equation with Implicit Difference Method by Chunye Gong, Weimin Bao, Guojian Tang, Yuewen Jiang, Jie Liu

“…A task distribution model and data layout with virtual boundary are designed for this parallel algorithm. The experimental results show that the parallel algorithm compares well with the exact solution. …”
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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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Parallel algorithm for sensitive sequence recognition from long-read genome data with high error rate by Cheng ZHONG, Hui SUN

“…To solve the problem that existing algorithms were difficult to effectively identify sensitive sequences in genomic data for long-read with high error rate, a recognition algorithm using hybrid CPU and GPU parallel computing, called CGPU-F3SR, was proposed.Firstly, the long-read in genomic data were partitioned into multiple short-read, and the Bloom filtering mechanism was used to avoid repeated calculation of the short-read.Secondly, the k-mer coding strategy was used to extract in parallel the error information of all short-read, the recognition accuracy was promoted by improving the sequence similarity calculation model.Finally, CPU and GPU were used to coordinate and parallel to accelerate the calculation of short-read similarity to improve recognition efficiency.As a result, both two types of sensitive sequences including short tandem repeats and disease related sequences could be identified efficiently and accurately from genome data for long-read with high error rate.The experimental results of recognizing sensitive sequences from genomic data for long-read with length 100～400 kbp each show that, compared with existing parallel algorithm, the average recognition accuracy and precision rate of proposed CPU/GPU parallel algorithm CGPU-F3SR are increased by 7.77% and 43.07% respectively, its average false positive rate is reduced by 7.41%, and its average recognition throughput is increased by 2.44 times.…”
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Interval-index technology of synthesis of the parallel algorithms for modular-point code conversion with the table-summation configuration by A. A. Kolyada, P. V. Kuchynski, A. F. Chernyavsky

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Parallel algorithm for sensitive sequence recognition from long-read genome data with high error rate by Cheng ZHONG, Hui SUN

“…To solve the problem that existing algorithms were difficult to effectively identify sensitive sequences in genomic data for long-read with high error rate, a recognition algorithm using hybrid CPU and GPU parallel computing, called CGPU-F3SR, was proposed.Firstly, the long-read in genomic data were partitioned into multiple short-read, and the Bloom filtering mechanism was used to avoid repeated calculation of the short-read.Secondly, the k-mer coding strategy was used to extract in parallel the error information of all short-read, the recognition accuracy was promoted by improving the sequence similarity calculation model.Finally, CPU and GPU were used to coordinate and parallel to accelerate the calculation of short-read similarity to improve recognition efficiency.As a result, both two types of sensitive sequences including short tandem repeats and disease related sequences could be identified efficiently and accurately from genome data for long-read with high error rate.The experimental results of recognizing sensitive sequences from genomic data for long-read with length 100～400 kbp each show that, compared with existing parallel algorithm, the average recognition accuracy and precision rate of proposed CPU/GPU parallel algorithm CGPU-F3SR are increased by 7.77% and 43.07% respectively, its average false positive rate is reduced by 7.41%, and its average recognition throughput is increased by 2.44 times.…”
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Numerical Simulation of Plasma Plume Sheath and Secondary Electron Emission Based on DSMC-PIC Parallel Algorithm by Fuxiang Yang, Jie Li, Wei Liu, Houling Chen

“…In this paper, a direct simulation Monte Carlo (DSMC) and particle-in-cell (PIC) hybrid parallel algorithm is employed for numerical simulation, which is a fully kinetic PIC method. …”
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Stable Parallel Algorithms for Interdisciplinary Computer-Based Online Education with Real Problem Scenarios for STEM Education by Liangfu Jiang, Haoran Yuan

“…In this paper, we analyse and study the interdisciplinary style of stable parallel algorithms for online computer education and real problem scenarios for STEM education. …”
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Retracted: Stable Parallel Algorithms for Interdisciplinary Computer-Based Online Education with Real Problem Scenarios for STEM Education by null Complexity

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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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The temolate for parallel branch algorithm by Milda Baravykaitė

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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.... by Vladimir Vasilyevich Vasilchikov

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CQS-Attention: Scaling Up the Standard Attention Computation for Infinitely Long Sequences by Yiming Bian, Arun K. Somani

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A parallel hybrid variable neighborhood descent algorithm for nonlinear optimal control problems by M. Salimi, A.H. Borzabadi, H.H. Mehne, A. Heydari

Subjects: “…parallel algorithm…”
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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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