# Multi-GPU single host training example

**URL:** <https://discourse.julialang.org/t/multi-gpu-single-host-training-example/73689>\
**Category:** GPU\
**Created:** [December 27, 2021, 11:16pm UTC](https://discourse.julialang.org/t/multi-gpu-single-host-training-example/73689 "2021-12-27T23:16:30Z")\
**Posts on this page:** 1\
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**Author:** ![j\_u](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/j_u/32/219081_2.png) [@j\_u](https://discourse.julialang.org/u/j_u)\
**Post date:** [December 28, 2021, 4:37pm UTC](https://discourse.julialang.org/t/multi-gpu-single-host-training-example/73689/2 "2021-12-28T16:37:09Z")

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> [@avilay](#):
>
> Can somebody point me to an end-to-end example of training a deep learning model using multiple GPUs?

Maybe you find the information included in those two threads / sites useful: [How to use multiple GPUs on a single node · Issue #69 · jonathan-laurent/AlphaZero.jl · GitHub](https://github.com/jonathan-laurent/AlphaZero.jl/issues/69) and [GitHub - fabricerosay/AlphaGPU: Alphazero on GPU thanks to CUDA.jl](https://github.com/fabricerosay/AlphaGPU), especially in the first link, however, I have to admit that I am not sure if this is leveraging GPU-to-GPU comms, completely omitting CPUs.

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