How can I flush GPU memory using CUDA (physical reset is unavailable)

Question

My CUDA program crashed during execution, before memory was flushed. As a result, device memory remained occupied.

I'm running on a GTX 580, for which nvidia-smi --gpu-reset is not supported.

Placing cudaDeviceReset() in the beginning of the program is only affecting the current context created by the process and doesn't flush the memory allocated before it.

I'm accessing a Fedora server with that GPU remotely, so physical reset is quite complicated.

So, the question is - Is there any way to flush the device memory in this situation?

Sandbox

"As a result, device memory remains occupied" - How do you know this to be true? – Psychoneurosis

Although nvidia-smi --gpu-reset is not available, I can still get some information with nvidia-smi -q. In most fields it gives 'N/A', but some information is useful. Here is the relevant output: Memory Usage Total : 1535 MB Used : 1227 MB Free : 307 MB – Sandbox

Plus, I fail to allocate memory for variables, which are small enough – Sandbox

Is the process which was holding the context on the GPU still alive? Even catastrophic termination of a process should result in the driver destroying the context and releasing resources. – Psychoneurosis

It doesn't look like it is alive. At least, I don't see it alive on CPU. I guess, the process on GPU cannot be alive as well, since I can launch another kernel (concurrent execution is not available on my GPU). But the memory is still occupied, I can be sure about it because of the reasons described above – Sandbox

If you have root access, you can unload and reload the nvidia driver. – Zenia

Did it crash oh host side or while kernel was running? – Candracandy

If you do ps -ef |grep 'whoami' and the results show any processes that appear to be related to your crashed session, kill those. (the single quote ' should be replaced with backtick ` ) – Equable

Have you tried sudo rmmod nvidia? – Piggish

ksooklall has a great answer to find what is hogging the memory, even if it doesn't show on nvidia-smi. – Dermatitis

nvidia-smi -caa worked great for me to release memory on all GPUs at once. – Countermove

How do you clear the NVIDIA GPU memory in Windows? – Seadon

Answer 1

Although it should be unecessary to do this in anything other than exceptional circumstances, the recommended way to do this on linux hosts is to unload the nvidia driver by doing

$ rmmod nvidia 

with suitable root privileges and then reloading it with

$ modprobe nvidia

If the machine is running X11, you will need to stop this manually beforehand, and restart it afterwards. The driver intialisation processes should eliminate any prior state on the device.

This answer has been assembled from comments and posted as a community wiki to get this question off the unanswered list for the CUDA tag

Psychoneurosis

cannot process the above command, error says, CUDA in use. So killed the PID using the solution provided by https://mcmap.net/q/187966/-how-can-i-flush-gpu-memory-using-cuda-physical-reset-is-unavailable. Its works for me – Neurophysiology

Answer 2

check what is using your GPU memory with

sudo fuser -v /dev/nvidia*

Your output will look something like this:

                     USER        PID  ACCESS COMMAND
/dev/nvidia0:        root       1256  F...m  Xorg
                     username   2057  F...m  compiz
                     username   2759  F...m  chrome
                     username   2777  F...m  chrome
                     username   20450 F...m  python
                     username   20699 F...m  python

Then kill the PID that you no longer need on htop or with

sudo kill -9 PID.

In the example above, Pycharm was eating a lot of memory so I killed 20450 and 20699.

Ahem

Thank you! For some reason, I had a process hogging all my VRAM, not showing on nvidia-smi. – Dermatitis

I need to use this a lot when running deep learning in different jupyter notebooks. The only issue is knowing exactly which PID is which. Any tips on this? – Pip

is chrome --- the google chrome browser? if so what business does it have using a gpu? – Chigoe

@josh I kill them one at a time making a mental note of the COMMAND. – Ahem

@kRazzyR - It uses it for speeding up computations, I assume, for rendering graphics, but maybe also other things. This did cause me a lot of issues when I install Nvidia drivers, CUDA and cudnn. I had to turn a lot of it off. See here. – Pip

@ksooklall - I meant how do we know which jupyter notebook/process corresponds to which PID and therefore which one to kill... thanks. – Pip

I notice that I kill one then it start a new one. I tried to pkill -9 -t pts/1 to log out,still not working – Cape

Try kill -9 or kill -15, not pkill – Ahem

In my case, sudo is not necessary. – Waylonwayman

Answer 3

First type

nvidia-smi

then select the PID that you want to kill

sudo kill -9 PID

Trilbi

Brilliant, this one actually worked for me. PID should be replaced with the.. PID number of the process that uses the GPU (which you can figure by nvidia-smi) – Cockneyfy

the command nvidia-smi returns Failed to initialize NVML: Driver/library version mismatch – Gastrotomy

nvidia-smi gives me two processes and when I go to kill them, it says no such process. processes are both called Xwayland – Circus

Answer 4

for the ones using python:

import torch, gc
gc.collect()
torch.cuda.empty_cache()

Westberg

This cannot in any way to what the questioner was asking about – Psychoneurosis

nevertheless answered my problem (which is admittedly not the exact same as the OP asked, but matches the title while searching) – Dreadfully

same here, any help is appreciated :) – Quartern

Answer 5

I also had the same problem, and I saw a good solution in quora, using

sudo kill -9 PID.

see https://www.quora.com/How-do-I-kill-all-the-computer-processes-shown-in-nvidia-smi

Gunderson

Worked a treat when I accidentally opened and loaded two different jupyter notebooks with VGG16. Warning: it kills the notebooks. I guess you could pick one to free up some memory for the other but I dont know how you select the PID for a given notebook. – Pip

Answer 6

One can also use nvtop, which gives an interface very similar to htop, but showing your GPU(s) usage instead, with a nice graph. You can also kill processes directly from here.

Here is a link to its Github : https://github.com/Syllo/nvtop

Tom

Answer 7

to kill all processess on GPU:

sudo fuser -v /dev/nvidia* -k

Alessandro

Instead of simply providing the answer directly, try writing a detailed comment that explains the solution, as long as the explanation is not too lengthy. @Alessandro . – Mess

Answer 8

on macOS (/ OS X), if someone else is having trouble with the OS apparently leaking memory:

• https://github.com/phvu/cuda-smi is useful for quickly checking free memory
• Quitting applications seems to free the memory they use. Quit everything you don't need, or quit applications one-by-one to see how much memory they used.
• If that doesn't cut it (quitting about 10 applications freed about 500MB / 15% for me), the biggest consumer by far is WindowServer. You can Force quit it, which will also kill all applications you have running and log you out. But it's a bit faster than a restart and got me back to 90% free memory on the cuda device.

Immunogenetics

Answer 9

Normally I just use nvidia-smi, but for some problems it's not enough (something still in cuda memory)

The nvidia-smi kill all is:

nvidia-smi | grep 'python' | awk '{ print $5 }' | xargs -n1 kill -9

If you're still hitting unexpected memory errors or similar problems then try:

sudo fuser -v /dev/nvidia* | cut -d' ' -f2- | sudo xargs -n1 kill -9

Maryn

Answer 10

For OS: UBUNTU 20.04 In the terminal type

nvtop

If the direct killing of consuming activity doesn't work then find and note the exact number of activity PID with most GPU usage.

sudo kill PID -number

Kauffman

Answer 11

If you have the problem that after killing one process the next starts (Comment)- like for example when you have a bash script that calls multiple python scripts and you want to kill them but can't find its PID you can use ps -ef where you'll find the PID of your "problematic" process and also its PPID (parent PID). Use kill PPID or kill -9 PPID or sudo kill PPID to stop the processes.

Bayberry

Answer 12

If all of this does not work, I found another answer here:

How to kill process on GPUs with PID in nvidia-smi using keyword?

nvidia-smi | grep 'python' | awk '{ print $X }' | xargs -n1 kill -9

Note that X (in the 'awk' expression) corresponds to the Xth column of your nvidia-smi command. If your nvidia-smi command looks like this, you should then replace X by 5.

Polder

Answer 13

I just started a new terminal and closed the old one and it worked out pretty well for me.

Brag