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...Together we can fulfill The ArrayFire Mission under an excellent Code of Conduct that promotes a respectful and friendly building experience. Rigorous benchmarks and tests ensuring top performance and numerical accuracy. Cross-platform compatibility with support for CUDA, OpenCL, and native CPU on Windows, Mac, and Linux. Built-in visualization functions through Forge.
CUDA library for continuous optimization and light field analysis
Library for continuous convex optimization in image analysis, together with a command line tool and Matlab interface.
Implements several recent algorithms for inverse problems and image segmentation with total variation regularizers and vectorial multilabel transition costs.
Also included is a suite for variational light field analysis, which ties into the HCI light field benchmark set and givens reference implementations for a number of our recently published algorithms.
*** NOTE: ...
...The library depends on Aparapi (https://code.google.com/p/aparapi/). Any GPU supporting OpenCL should be supported (including low-end GPUs without double-precision fp support), and there is automatic fallback to pure java implementations for all operations in the event that there is no OpenCL support available.
A high-level API allows for very easy use from AWT/Swing, whilst the low-level array-based API allows integration with any imaging framework (e.g. from Android or SWT).