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parallel computing toolbox parallel processing support  (MathWorks Inc)


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    MathWorks Inc parallel computing toolbox parallel processing support
    Parallel Computing Toolbox Parallel Processing Support, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 95/100, based on 389 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/parallel+computing+toolbox+support/Parallel+Computing+Toolbox/10__1051_slash_sbuild_slash_2024005-130-68-75
    Average 95 stars, based on 389 article reviews
    parallel computing toolbox parallel processing support - by Bioz Stars, 2026-10
    95/100 stars

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    Article Title: Optimization method of building energy efficiency design based on decomposition multi objective and agent assisted model
    Article Snippet: .. The computation of the optimal solution of the aggregation function is shown in equation (14) min g xjle; z ð Þ 1⁄4 max 1 q R leqjfq xð Þ z q n o : ð14Þ Hardware configuration Intel Core i7-9700K, 16 GB RAM, NVIDIA GTX 1080 Intel Core i7-9700K, 16 GB RAM, NVIDIA GTX 1080 Software environment Windows 10, MATLAB R2020a, Parallel Computing Toolbox Windows 10, MATLAB R2020a, Parallel Computing Toolbox Parallel processing Support, using MATLAB’s parallel computing toolbox Support, using MATLAB’s parallel computing toolbox Maximum iteration number 25 30 Number of particles 60 60 CPU utilization rate 85 70 GPU utilization rate 75 65 Average running time 45 min 35 min In equation (14), le represents the e th weight vector and R is the weight vectors. z* is the objective function, z q represents the objective function of the agent model, and lq is the e th weight vector of the agent model. Where the objective function z* is calculated as shown in equation (15). z 1⁄4 min ˆfq xð Þjx∈V; q∈ 1; 2; :::;Rf g n o : ð15Þ In equation (15), V represents the range of values of the independent variable x. ..

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    Article Title: Optimization method of building energy efficiency design based on decomposition multi objective and agent assisted model
    Article Snippet: .. The computation of the optimal solution of the aggregation function is shown in equation (14) min g xjle; z ð Þ 1⁄4 max 1 q R leqjfq xð Þ z q n o : ð14Þ Hardware configuration Intel Core i7-9700K, 16 GB RAM, NVIDIA GTX 1080 Intel Core i7-9700K, 16 GB RAM, NVIDIA GTX 1080 Software environment Windows 10, MATLAB R2020a, Parallel Computing Toolbox Windows 10, MATLAB R2020a, Parallel Computing Toolbox Parallel processing Support, using MATLAB’s parallel computing toolbox Support, using MATLAB’s parallel computing toolbox Maximum iteration number 25 30 Number of particles 60 60 CPU utilization rate 85 70 GPU utilization rate 75 65 Average running time 45 min 35 min In equation (14), le represents the e th weight vector and R is the weight vectors. z* is the objective function, z q represents the objective function of the agent model, and lq is the e th weight vector of the agent model. Where the objective function z* is calculated as shown in equation (15). z 1⁄4 min ˆfq xð Þjx∈V; q∈ 1; 2; :::;Rf g n o : ð15Þ In equation (15), V represents the range of values of the independent variable x. ..



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    parallel computing toolbox parallel processing support  (MathWorks Inc)
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    MathWorks Inc parallel computing toolbox parallel processing support
    Parallel Computing Toolbox Parallel Processing Support, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 95/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/parallel+computing+toolbox+support/Parallel+Computing+Toolbox/10__1051_slash_sbuild_slash_2024005-130-68-75
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    parallel computing toolbox support  (MathWorks Inc)
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    parallel computing toolbox provides gpu programming support  (MathWorks Inc)
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    MathWorks Inc parallel computing toolbox provides gpu programming support
    Execution time for Jacobian calculation by conventional and Broyden method on C CPU, C <t>GPU,</t> <t>MATLAB</t> CPU, and MATLAB GPU platforms for mesh size (a) 3736, (b) 7465, and (c) 15031.
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    Execution time for Jacobian calculation by conventional and Broyden method on C CPU, C GPU, MATLAB CPU, and MATLAB GPU platforms for mesh size (a) 3736, (b) 7465, and (c) 15031.

    Journal: International Journal of Biomedical Imaging

    Article Title: High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System

    doi: 10.1155/2014/376456

    Figure Lengend Snippet: Execution time for Jacobian calculation by conventional and Broyden method on C CPU, C GPU, MATLAB CPU, and MATLAB GPU platforms for mesh size (a) 3736, (b) 7465, and (c) 15031.

    Article Snippet: MATLAB's Parallel Computing Toolbox provides GPU programming support to take advantage of GPUs from within high-level programming environments.

    Techniques:

    Breakup of the execution time of various computing blocks of the algorithm on C CPU, C GPU, MATLAB CPU, and MATLAB GPU platforms for mesh size (a) 3736, (b) 7465, and (c) 15031.

    Journal: International Journal of Biomedical Imaging

    Article Title: High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System

    doi: 10.1155/2014/376456

    Figure Lengend Snippet: Breakup of the execution time of various computing blocks of the algorithm on C CPU, C GPU, MATLAB CPU, and MATLAB GPU platforms for mesh size (a) 3736, (b) 7465, and (c) 15031.

    Article Snippet: MATLAB's Parallel Computing Toolbox provides GPU programming support to take advantage of GPUs from within high-level programming environments.

    Techniques:

    Execution time for an iteration on C CPU, C GPU, MATLAB CPU, and MATLAB GPU platforms for different mesh sizes.

    Journal: International Journal of Biomedical Imaging

    Article Title: High-Speed GPU-Based Fully Three-Dimensional Diffuse Optical Tomographic System

    doi: 10.1155/2014/376456

    Figure Lengend Snippet: Execution time for an iteration on C CPU, C GPU, MATLAB CPU, and MATLAB GPU platforms for different mesh sizes.

    Article Snippet: MATLAB's Parallel Computing Toolbox provides GPU programming support to take advantage of GPUs from within high-level programming environments.

    Techniques: