ADEL

Summary:
ADEL is an open-source C++ template library for Automatic Differentiation in forward mode. Works with CUDA out of the box.

URL: http://github.com/eleks/ADEL

Developers:

• ELEKS

Mode:	Forward
Method:	Operator overloading
Supported Language:	C/C++

Features:
ADEL is an easy to use forward mode automated differentiation library using C++ templates.

In this version:
- Automatic differentiation (forward mode) using C++ templates
- CUDA support
- Gradient and Hessian for partial derivatives
- Newton-Raphson method

The library is distributed under MIT license. Your feedback and contribution are highly appreciated.

Supported Platforms:

• Windows
• Unix/Linux

Licensing: open source

Entries in our publication database that actually use ADEL in the numerical experiments:  0

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