You can watch the archived version of this webinar at http://www.mathworks.com/videos/large-data-in-matlab-a-seismic-data-processing-case-study-81792.html (recommended).
The demos show how to manage out of memory data using a memory mapped file and customizing the object for array indexing. This enables reuse of the memory mapped file inside functions or with parallel computing without needing to rewrite code or recreate the memory mapped file on each worker manually.
The data files are not inlcluded in this download. Read the README file to locate the public data sources on the internet.
The demo also shows how to speed up the solution of the wave equation (finite difference PDE) using a custom CUDA kernel. The relative speedup observed was around 1.6X.
The demos start with:
1 - and introduction to seismic analysis (Kirchhoff migration, reverse time migration)
2 - Large data extension of the functionality shown in (1) and parallel computing for speeding up the processing time
3 - GPU extension to (1) showing how to use a custom CUDA kernel to solve the wave equation compared to a MATLAB implementation (written in vectorized form)
Stuart Kozola (2023). Large Data in MATLAB: A Seismic Data Processing Case Study (https://www.mathworks.com/matlabcentral/fileexchange/30585-large-data-in-matlab-a-seismic-data-processing-case-study), MATLAB Central File Exchange. Recuperado .
Compatibilidad con la versión de MATLAB
Compatibilidad con las plataformasWindows macOS Linux
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