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gpu computing  (MathWorks Inc)


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    MathWorks Inc gpu computing
    Gpu Computing, 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/product/gpu+computing/pm40555683-43-2-30
    Average 90 stars, based on 1 article reviews
    gpu computing - by Bioz Stars, 2026-09
    90/100 stars

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    Article Title: A Probabilistic Bayesian Approach to Recover R 2 ∗ map and Phase Images for Quantitative Susceptibility Mapping
    Article Snippet: If GPU is available, a better option would be to take advantage of GPU computing in MATLAB to speed up the 3D recovery.

    Article Title: HyperXtract: Strategic Platform for Optimizing High-Bandwidth Nanopore Data Extraction Performance.
    Article Snippet: High-bandwidth amplifiers that offer measurement capabilities on the submicrosecond scale to resonate with shortlived events have recently gained tremendous traction in solid-state nanopore (SSN) sensing.. High acquisition rate data collection is a hallmark of such measurements, leading to oversized files.. Such experimental needs warrant high-performance analysis platforms that can analyze large files in a reasonable time frame.

    Article Title: Common lines modeling for reference free Ab-initio reconstruction in cryo-EM.
    Article Snippet: The algorithm for estimating common lines between pairs of class averages was implemented using Matlab’s support for GPU computing, running on a single Nvidia GeForce GTX 1080.

    Article Title: Comparison of Parametric and Semi-Parametric Binary Response Models
    Article Snippet: The computation in equation (13) can be realized efficiently by using graphic processing unit (GPU) computing with C/C++ in Matlab (Li (2011)), and its speed is about 400 time faster than the regular computing method such as in Gauss or Matlab itself.

    Article Title: 3D texture analysis for classification of second harmonic generation images of human ovarian cancer.
    Article Snippet: Here we employed GPU computing within the Matlab parallel computing toolbox to greatly decrease the computational time.



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    CPU Intel-Core i9 and  GPU  computation time in minutes for the different cases of N using the BHM approach for solving the CH equation in  3D  with random initial condition.

    Journal: AIMS mathematics

    Article Title: Efficient numerical approaches with accelerated graphics processing unit (GPU) computations for Poisson problems and Cahn-Hilliard equations

    doi: 10.3934/math.20241334

    Figure Lengend Snippet: CPU Intel-Core i9 and GPU computation time in minutes for the different cases of N using the BHM approach for solving the CH equation in 3D with random initial condition.

    Article Snippet: Finally, we also show how to speed up 3D simulations by performing graphics processing unit (GPU) computations by using simple MATLAB commands.

    Techniques: