# Making a fast evaluation of a function and its gradient

**URL:** <https://discourse.julialang.org/t/making-a-fast-evaluation-of-a-function-and-its-gradient/68884>\
**Category:** Performance\
**Created:** [September 28, 2021, 3:55pm UTC](https://discourse.julialang.org/t/making-a-fast-evaluation-of-a-function-and-its-gradient/68884 "2021-09-28T15:55:12Z")\
**Posts on this page:** 1\
**Showing post:** 33

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**Author:** ![Elrod](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/elrod/32/22461_2.png) [@Elrod](https://discourse.julialang.org/u/Elrod)\
**Post date:** [October 11, 2021, 5:32pm UTC](https://discourse.julialang.org/t/making-a-fast-evaluation-of-a-function-and-its-gradient/68884/33 "2021-10-11T17:32:33Z")

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Note that LoopVectorization 0.12.83 and newer should automatically `using SIMDDualNumbers` for you if you `using LoopVectorization, ForwardDiff`.

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_[View the full topic](https://discourse.julialang.org/t/making-a-fast-evaluation-of-a-function-and-its-gradient/68884)._