# A implementation of ResNet-18 uses lot of GPU memory

**URL:** https://discourse.julialang.org/t/a-implementation-of-resnet-18-uses-lot-of-gpu-memory/36389
**Category:** Machine Learning
**Tags:** question, flux
**Created:** [March 23, 2020, 12:08pm UTC](https://discourse.julialang.org/t/a-implementation-of-resnet-18-uses-lot-of-gpu-memory/36389 "2020-03-23T12:08:50Z")
**Posts on this page:** 1
**Showing post:** 5

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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: [March 25, 2020, 8:55pm UTC](https://discourse.julialang.org/t/a-implementation-of-resnet-18-uses-lot-of-gpu-memory/36389/5 "2020-03-25T20:55:24Z")

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In my case your Flux implementation takes around 7 mins per epoch with batchsize of 64, but my GPU might not be as fast as yours. It’s quite busy, at 100%.  
Tensorflow trains in 6 min per epoch or total?

 ![batchsize64](https://global.discourse-cdn.com/julialang/original/3X/c/6/c63de29f4fdbdffb162faa8f501e89f323e8ef86.jpeg)

Edit: are you using FP16 on RTX2070?

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