# Differential Equations running out of GPU memory

**URL:** <https://discourse.julialang.org/t/differential-equations-running-out-of-gpu-memory/101048>\
**Category:** Modelling & Simulations\
**Tags:** question\
**Created:** [July 1, 2023, 10:07am UTC](https://discourse.julialang.org/t/differential-equations-running-out-of-gpu-memory/101048 "2023-07-01T10:07:44Z")\
**Posts on this page:** 1\
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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:** [July 1, 2023, 2:23pm UTC](https://discourse.julialang.org/t/differential-equations-running-out-of-gpu-memory/101048/2 "2023-07-01T14:23:05Z")

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> [@Tommy\_Fischer](#):
>
> `solve(prob, callback=cb, tstops = savepoints, save_on=false)`

What solver do you need here? If you need something with stiff ODEs, do you have a sparse Jacobian? This is the same exact conclusion of [Minimising DifferentialEquations GPU memory allocation](https://discourse.julialang.org/t/minimising-differentialequations-gpu-memory-allocation/99050)

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