# CUDA memory isn't freed and cannot be backtracked

**URL:** <https://discourse.julialang.org/t/cuda-memory-isnt-freed-and-cannot-be-backtracked/83292>\
**Category:** General Usage\
**Tags:** cuda\
**Created:** [June 24, 2022, 7:18am UTC](https://discourse.julialang.org/t/cuda-memory-isnt-freed-and-cannot-be-backtracked/83292 "2022-06-24T07:18:44Z")\
**Posts on this page:** 1\
**Showing post:** 5

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**Author:** ![maleadt](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/maleadt/32/10097_2.png) [@maleadt](https://discourse.julialang.org/u/maleadt)\
**Post date:** [June 26, 2022, 11:27am UTC](https://discourse.julialang.org/t/cuda-memory-isnt-freed-and-cannot-be-backtracked/83292/5 "2022-06-26T11:27:57Z")

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> [@Marcell\_Havlik](#):
>
> ```julia
> julia> CUDA.memory_status()
> Effective GPU memory usage: 99.57% (5.758 GiB/5.783 GiB)
> Memory pool usage: 5.951 MiB (5.188 GiB reserved)
> 
> ```

This is a perfectly normal report: you’re only using 5MB of GPU memory, while the underlying pool (which allocations are made in) is currently sized around 5GB, thus consuming most of the physical memory on your device. This does not mean that the memory is unavailable, you can allocate 5GB-5MB. So this isn’t indicative of an OOM, or a memory leak.

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