A few really important questions regarding Jetson memory system

Autonomous Machines Jetson & Embedded Systems Jetson Nano
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Hi! While investigating how to accommodate a rather memory demanding application into Jetson Nano 4gb of RAM, I wrote a test program that just allocates memory (host, device, pinned, unified types) and initializes it, so that I could understand how allocation behaves on the Jetson.

What I got is interesting and I’d like to ask:

  1. If I allocate large amounts of memory (let’s say 2-3 gb) via pinned/unified/device method, I also get CPU RAM consumption that raises for about 400mb. Are those page/allocation tables in the driver? (It doesn’t matter how many allocations I use: one or many, it’ll be around +400mb of CPU RAM usage).

  2. Does GPU memory oversubscription (via mallocmanaged) work on Jetson?

  3. When the test app goes up around 3gb, device allocations become REALLY slow. Is that because zram swap activates and eats up time?

  4. It looks like I can’t allocate more than ~3gb or GPU ram (+/- some), the app is just get killed by oom. Is there a way to squeeze a little more by tuning OS? For example I need to allocate 3.2gb, but only ~3.0-3.1 is doable. Compact

Thank you!

Env: Jetson Nano (4gb RAM), Ubuntu 18.04, Jetpack 32.4.4, jetson_stats for collecting information.

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Up. Thanks!

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Attached the test program here due to many user can’t open it.

NSUQump7.cpp (2.9 KB)

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Now only questions 1 and 2 are still actual. Thanks!

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Answerin [1] & [2]
[1] Please check if “NvMapMemFree + NvMapMemUsed” is increased by the amount near to the amount by which “MemFree” is reduced. You can use the below command to get data.
$ egrep -i ‘MemFree|NvMapMemUsed’ /proc/meminfo

[2] No

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