matlab gpu toolbox Search Results


matlab r2023a software  (MathWorks Inc)
90
MathWorks Inc matlab r2023a software
Matlab R2023a Software, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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plotting matlab 2018b  (MathWorks Inc)
90
MathWorks Inc plotting matlab 2018b
Plotting Matlab 2018b, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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matlab r2020a  (MathWorks Inc)
93
MathWorks Inc matlab r2020a
Hardware and software specification for model reproducibility.
Matlab R2020a, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 93/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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matlab/cuda-without-c++ code (mcc)  (MathWorks Inc)
90
MathWorks Inc matlab/cuda-without-c++ code (mcc)
Example process flow of the heterogeneous computing. In this figure, we create a sample MEXCUDA function for calculating the radius matrix of a scanned region to each transducer elements. The host code (CPU) is in charge of initialization and finalization blocks such as reading the input from <t>MATLAB,</t> performing condition checks, and allocating memory for input and output data. Device code in <t>GPU</t> is responsible for computing the radius matrix in parallel from required inputs (parallel computation block)
Matlab/Cuda Without C++ Code (Mcc), supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/matlab/cuda-without-c++ code (mcc)/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
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gtx 1080 gpu  (MathWorks Inc)
90
MathWorks Inc gtx 1080 gpu
Example process flow of the heterogeneous computing. In this figure, we create a sample MEXCUDA function for calculating the radius matrix of a scanned region to each transducer elements. The host code (CPU) is in charge of initialization and finalization blocks such as reading the input from <t>MATLAB,</t> performing condition checks, and allocating memory for input and output data. Device code in <t>GPU</t> is responsible for computing the radius matrix in parallel from required inputs (parallel computation block)
Gtx 1080 Gpu, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/gtx 1080 gpu/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
gtx 1080 gpu - by Bioz Stars, 2026-04
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matlab gpu coder  (MathWorks Inc)
90
MathWorks Inc matlab gpu coder
Example process flow of the heterogeneous computing. In this figure, we create a sample MEXCUDA function for calculating the radius matrix of a scanned region to each transducer elements. The host code (CPU) is in charge of initialization and finalization blocks such as reading the input from <t>MATLAB,</t> performing condition checks, and allocating memory for input and output data. Device code in <t>GPU</t> is responsible for computing the radius matrix in parallel from required inputs (parallel computation block)
Matlab Gpu Coder, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/matlab gpu coder/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
matlab gpu coder - by Bioz Stars, 2026-04
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matlab gpu program  (MathWorks Inc)
90
MathWorks Inc matlab gpu program
Example process flow of the heterogeneous computing. In this figure, we create a sample MEXCUDA function for calculating the radius matrix of a scanned region to each transducer elements. The host code (CPU) is in charge of initialization and finalization blocks such as reading the input from <t>MATLAB,</t> performing condition checks, and allocating memory for input and output data. Device code in <t>GPU</t> is responsible for computing the radius matrix in parallel from required inputs (parallel computation block)
Matlab Gpu Program, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/matlab gpu program/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
matlab gpu program - by Bioz Stars, 2026-04
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gpu-compatible operations  (MathWorks Inc)
90
MathWorks Inc gpu-compatible operations
Example process flow of the heterogeneous computing. In this figure, we create a sample MEXCUDA function for calculating the radius matrix of a scanned region to each transducer elements. The host code (CPU) is in charge of initialization and finalization blocks such as reading the input from <t>MATLAB,</t> performing condition checks, and allocating memory for input and output data. Device code in <t>GPU</t> is responsible for computing the radius matrix in parallel from required inputs (parallel computation block)
Gpu Compatible Operations, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/gpu-compatible operations/product/MathWorks Inc
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matlab 2014b  (MathWorks Inc)
90
MathWorks Inc matlab 2014b
Example process flow of the heterogeneous computing. In this figure, we create a sample MEXCUDA function for calculating the radius matrix of a scanned region to each transducer elements. The host code (CPU) is in charge of initialization and finalization blocks such as reading the input from <t>MATLAB,</t> performing condition checks, and allocating memory for input and output data. Device code in <t>GPU</t> is responsible for computing the radius matrix in parallel from required inputs (parallel computation block)
Matlab 2014b, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/matlab 2014b/product/MathWorks Inc
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matlab+gpu implementation  (MathWorks Inc)
90
MathWorks Inc matlab+gpu implementation
Example process flow of the heterogeneous computing. In this figure, we create a sample MEXCUDA function for calculating the radius matrix of a scanned region to each transducer elements. The host code (CPU) is in charge of initialization and finalization blocks such as reading the input from <t>MATLAB,</t> performing condition checks, and allocating memory for input and output data. Device code in <t>GPU</t> is responsible for computing the radius matrix in parallel from required inputs (parallel computation block)
Matlab+Gpu Implementation, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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matlab gpu-based cloud  (MathWorks Inc)
90
MathWorks Inc matlab gpu-based cloud
Example process flow of the heterogeneous computing. In this figure, we create a sample MEXCUDA function for calculating the radius matrix of a scanned region to each transducer elements. The host code (CPU) is in charge of initialization and finalization blocks such as reading the input from <t>MATLAB,</t> performing condition checks, and allocating memory for input and output data. Device code in <t>GPU</t> is responsible for computing the radius matrix in parallel from required inputs (parallel computation block)
Matlab Gpu Based Cloud, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/matlab gpu-based cloud/product/MathWorks Inc
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matlab gpu-based cloud - by Bioz Stars, 2026-04
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matlab gpu implementation  (MathWorks Inc)
90
MathWorks Inc matlab gpu implementation
Example process flow of the heterogeneous computing. In this figure, we create a sample MEXCUDA function for calculating the radius matrix of a scanned region to each transducer elements. The host code (CPU) is in charge of initialization and finalization blocks such as reading the input from <t>MATLAB,</t> performing condition checks, and allocating memory for input and output data. Device code in <t>GPU</t> is responsible for computing the radius matrix in parallel from required inputs (parallel computation block)
Matlab Gpu Implementation, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/matlab gpu implementation/product/MathWorks Inc
Average 90 stars, based on 1 article reviews
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Image Search Results


Hardware and software specification for model reproducibility.

Journal: PLOS Computational Biology

Article Title: Coupling and heterogeneity modulate pacemaking capability in healthy and diseased two-dimensional sinoatrial node tissue models

doi: 10.1371/journal.pcbi.1010098

Figure Lengend Snippet: Hardware and software specification for model reproducibility.

Article Snippet: Simulation , MATLAB R2019b; MATLAB GPU coder , Simulation , MATLAB R2020a; CUDA 8.0; Visual Studio 2015.

Techniques: Software

Example process flow of the heterogeneous computing. In this figure, we create a sample MEXCUDA function for calculating the radius matrix of a scanned region to each transducer elements. The host code (CPU) is in charge of initialization and finalization blocks such as reading the input from MATLAB, performing condition checks, and allocating memory for input and output data. Device code in GPU is responsible for computing the radius matrix in parallel from required inputs (parallel computation block)

Journal: Visual Computing for Industry, Biomedicine and Art

Article Title: Optimizing photoacoustic image reconstruction using cross-platform parallel computation

doi: 10.1186/s42492-018-0002-5

Figure Lengend Snippet: Example process flow of the heterogeneous computing. In this figure, we create a sample MEXCUDA function for calculating the radius matrix of a scanned region to each transducer elements. The host code (CPU) is in charge of initialization and finalization blocks such as reading the input from MATLAB, performing condition checks, and allocating memory for input and output data. Device code in GPU is responsible for computing the radius matrix in parallel from required inputs (parallel computation block)

Article Snippet: Validating images are then reconstructed using the MATLAB/CUDA-without-C++ code (MCC), MATLAB-without-GPU code (MWGC), and our MCCC in this study.

Techniques: Blocking Assay

a Comparison of reconstruction time between MCC, MCCC and MWGC and b a close look into reconstruction time difference between MCC and MCCC codes with different RF

Journal: Visual Computing for Industry, Biomedicine and Art

Article Title: Optimizing photoacoustic image reconstruction using cross-platform parallel computation

doi: 10.1186/s42492-018-0002-5

Figure Lengend Snippet: a Comparison of reconstruction time between MCC, MCCC and MWGC and b a close look into reconstruction time difference between MCC and MCCC codes with different RF

Article Snippet: Validating images are then reconstructed using the MATLAB/CUDA-without-C++ code (MCC), MATLAB-without-GPU code (MWGC), and our MCCC in this study.

Techniques: Comparison