Numerical Analysis Tools

NVIDIA GPU's have extremely high numerical throughput, and applications with high arithmetic density can enjoy very high GPU acceleration. You help you leverage this capability there are many options.

Matlab  by Mathworks, has native support for CUDA in the Parallel Computing Toolbox. Enjoy GPU acceleration without having to write any CUDA Kernels.

Mathematicia by Wolfram is a comprehensive technical computing solution, enabling complex computational applications to be build, and with native GPU acceleration.

AccelerEyes ArrayFire Comprehensive GPU function library, including functions for math, signal and  image processing, statistics, and more.  Interfaces for C, C++, Fortran, and Python.

IMSL Fortran Numerical Library is a comprehensive set of mathematical and statistical functions that developers can embed into their Fortran software applications. 

LabView enables engineers and scientists to create applications using a powerful high level programming language and advanced tools, and now features GPU acceleration support.

Math Premium takes advantage of the NVIDIA CUDA architecture to dramatically accelerate mathematics on the .NET platform, including a 2-4x speed-up for many math functions without any code changes.

Looking for expert advice on how to best use the numerical capabilities of your GPU?
Try reviewing the documentation and educational materials below or get in touch with industry experts and NVIDIA engineers on the CUDA Developer forums

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