Paper
4 May 2012 ArrayFire: a GPU acceleration platform
James Malcolm, Pavan Yalamanchili, Chris McClanahan, Vishwanath Venugopalakrishnan, Krunal Patel, John Melonakos
Author Affiliations +
Abstract
ArrayFire is a GPU matrix library for the rapid development of general purpose GPU (GPGPU) computing applications within C, C++, Fortran, and Python. ArrayFire contains a simple API and provides full GPU compute capability on CUDA and OpenCL capable devices. ArrayFire provides thousands of GPU-tuned functions including linear algebra, convolutions, reductions, and FFTs as well as signal, image, statistics, and graphics libraries. We will further describe how ArrayFire enables development of GPU computing applications and highlight some of its key functionality using examples of how it works in real code.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
James Malcolm, Pavan Yalamanchili, Chris McClanahan, Vishwanath Venugopalakrishnan, Krunal Patel, and John Melonakos "ArrayFire: a GPU acceleration platform", Proc. SPIE 8403, Modeling and Simulation for Defense Systems and Applications VII, 84030A (4 May 2012); https://doi.org/10.1117/12.921122
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Cited by 32 scholarly publications.
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KEYWORDS
Visualization

C++

Computing systems

Computer programming

Matrix multiplication

Software development

Convolution

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