# How to track total memory usage of Julia process over time

**URL:** https://discourse.julialang.org/t/how-to-track-total-memory-usage-of-julia-process-over-time/91167
**Category:** Profiling
**Tags:** memory-allocation
**Created:** [December 3, 2022, 6:06am UTC](https://discourse.julialang.org/t/how-to-track-total-memory-usage-of-julia-process-over-time/91167 "2022-12-03T06:06:13Z")
**Posts on this page:** 1
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### Author: ![jmair](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/jmair/32/35117_2.png) [@jmair](https://discourse.julialang.org/u/jmair)
#### Post date: [December 4, 2022, 5:48am UTC](https://discourse.julialang.org/t/how-to-track-total-memory-usage-of-julia-process-over-time/91167/2 "2022-12-04T05:48:44Z")

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The allocation profiler may be useful here to visualise the memory footprint of your application during runtime. There’s a good Julia Con talk - [Hunting down allocations with Julia 1.8's Allocation Profiler | JuliaCon 2022](https://live.juliacon.org/talk/YHYSEM)

I don’t think this will be exactly what you want, and I’m interested to see what others suggest.

As a quick question, if you are using a single node, is it possible to use multithreading instead of MPI, as I think Trixi supports that? I suspect this will have a much lower memory footprint, and less likely to run out of memory. I wouldn’t be surprised if each process uses at least 500-1000MB depending on the size of the packages loaded, this isn’t uncommon.

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