# GPU support for Turing modeling with system of ODEs

**URL:** <https://discourse.julialang.org/t/gpu-support-for-turing-modeling-with-system-of-odes/77410>\
**Category:** Probabilistic Programming\
**Tags:** gpu, bayesian-inference, differentialequation\
**Created:** [March 4, 2022, 4:03pm UTC](https://discourse.julialang.org/t/gpu-support-for-turing-modeling-with-system-of-odes/77410 "2022-03-04T16:03:14Z")\
**Posts on this page:** 1\
**Showing post:** 2

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**Author:** ![ChrisRackauckas](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/chrisrackauckas/32/77_2.png) [@ChrisRackauckas](https://discourse.julialang.org/u/ChrisRackauckas)\
**Post date:** [June 4, 2022, 12:20pm UTC](https://discourse.julialang.org/t/gpu-support-for-turing-modeling-with-system-of-odes/77410/2 "2022-06-04T12:20:05Z")

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What did you try? If you just follow DiffEqGPU’s tutorials for example inside of a Turing.jl module it should just work. There’s no combined tutorial, but if you just stick a tutorial for GPU solving of ODEs with a tutorial of Turing.jl then you get both together.

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