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Sempre ouço pessoas falando coisas como The issue here is that some of your numa nodes aren't populated with any memory Ou simplesmente seria uma abreviação?

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But the main difference between them is not cle. I get a bizzare readout when creating a tensor and memory usage on my rtx 3. Hopping from java garbage collection, i came across jvm settings for numa

Curiously i wanted to check if my centos server has numa capabilities or not

Is there a *ix command or utility that could. The numa_alloc_* () functions in libnuma allocate whole pages of memory, typically 4096 bytes Cache lines are typically 64 bytes Since 4096 is a multiple of 64, anything that comes back from numa_alloc_* () will already be memaligned at the cache level

Beware the numa_alloc_* () functions however It says on the man page that they are slower than a corresponding malloc (), which i'm sure is. Numa sensitivity first, i would question if you are really sure that your process is numa sensitive In the vast majority of cases, processes are not numa sensitive so then any optimisation is pointless

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Each application run is likely to vary slightly and will always be impacted by other processes running on the machine.

Your kernel may have been built without numa support asked 7 years, 2 months ago modified 2 years, 8 months ago viewed 42k times I've just installed cuda 11.2 via the runfile, and tensorflow via pip install tensorflow on ubuntu 20.04 with python 3.8

My Final Numa
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