# Which GPU should I ask for?

**URL:** <https://discourse.julialang.org/t/which-gpu-should-i-ask-for/43861>\
**Category:** GPU\
**Created:** [July 29, 2020, 9:03am UTC](https://discourse.julialang.org/t/which-gpu-should-i-ask-for/43861 "2020-07-29T09:03:39Z")\
**Posts on this page:** 5\
**Page:** 1

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**Author:** ![sylvaticus](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/sylvaticus/32/203883_2.png) [@sylvaticus](https://discourse.julialang.org/u/sylvaticus)\
**Post date:** [July 29, 2020, 9:03am UTC](https://discourse.julialang.org/t/which-gpu-should-i-ask-for/43861/1 "2020-07-29T09:03:39Z")

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Hello, we have a remote server (not VPS) and I would like to ask the company managing it to add a GPU for machine learning computations (using CUDA.jl I suppose).  
Is there a list of supported GPU?  
How they are organised ? Which serie in the entry/midrange would you suggest ? (but not too entry that it becomes worst that using good CPUs) ?

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**Author:** ![sylvaticus](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/sylvaticus/32/203883_2.png) [@sylvaticus](https://discourse.julialang.org/u/sylvaticus)\
**Post date:** [July 29, 2020, 9:26am UTC](https://discourse.julialang.org/t/which-gpu-should-i-ask-for/43861/2 "2020-07-29T09:26:37Z")

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I did found this: [The Best GPUs for Deep Learning in 2020 — An In-depth Analysis](https://timdettmers.com/2019/04/03/which-gpu-for-deep-learning/)

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**Author:** ![Iulian.Cioarca](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/iulian.cioarca/32/30166_2.png) [@Iulian.Cioarca](https://discourse.julialang.org/u/Iulian.Cioarca)\
**Post date:** [July 29, 2020, 10:08am UTC](https://discourse.julialang.org/t/which-gpu-should-i-ask-for/43861/3 "2020-07-29T10:08:53Z")

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In the end it depends on your budget, tasks and future julia ecosystem updates.  
If you’re more into the image processing-deep learning-cnn camp, here’s my(limited) thoughts:

My experience led me to buy a 12GB Titan X (second hand it was ~ 200$:)) because I encountered a lot of out of memory issues with large CNNs (if you search around the forum or Flux/Knet github issues, you will see users having such problems).  
The new 2xxx Nvidia gpus are cool, especially because of the 16bit compute capability. ~~As far as I know, no Julia deep learning library has 16 bit support so at the moment they might be a bit overkill (they’re also expensive).~~ [Knet](https://denizyuret.github.io/Knet.jl/latest/reference/#KnetArray) does not support fp16, according to the manual. If you have the budget and want to be future-proof, you could buy such a card, hoping that 16 bit support will arrive in the future.  
For me the memory issue was quite severe, having problems even on a 8GB GTX1070 during training networks like VGG16 or YOLO from scratch, so I bought the 12GB Titan.

In terms of software compatibility, CUDA.jl should support most of the NVIDIA GPUs from the last 6-7 years at least (mine is from 2015).

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**Author:** ![baggepinnen](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/baggepinnen/32/693_2.png) [@baggepinnen](https://discourse.julialang.org/u/baggepinnen)\
**Post date:** [July 29, 2020, 11:31am UTC](https://discourse.julialang.org/t/which-gpu-should-i-ask-for/43861/4 "2020-07-29T11:31:00Z")

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What problems are you facing with using 16 bit computations in Flux? As I understand, everything should be generic wrt the floating point type, but the default is 32 bits.

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**Author:** ![Iulian.Cioarca](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/iulian.cioarca/32/30166_2.png) [@Iulian.Cioarca](https://discourse.julialang.org/u/Iulian.Cioarca)\
**Post date:** [July 29, 2020, 1:43pm UTC](https://discourse.julialang.org/t/which-gpu-should-i-ask-for/43861/5 "2020-07-29T13:43:08Z")

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Whoops, sorry, that was a mistake. It’s Knet that supports only [64/32bit](https://denizyuret.github.io/Knet.jl/latest/reference/#KnetArray).