AD Tool: FastAD
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FastAD


Summary:
FastAD is a C++ template library of automatic differentiation supporting both forward and reverse mode to compute gradients and Hessians. It utilizes the latest features in C++17 and expression templates for efficient computation.

URL: https://github.com/JamesYang007/FastAD

Developers:
  • James Yang
  • Kent Hall

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

Features:
- Provides both forward and reverse mode.
- Supports gradient and Hessian computation.
- Elementary functions have same name as their STL counterpart.
- Supports similar syntax as STL.
- MIT licensed.

Supported Platforms:
  • Unix/Linux
  • Mac
  • Application Server


Licensing: open source

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

The following diagram shows these entries versus the year of the publication.

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